Intechno Journal : Information Technology Journal
type: channel
description: Intechno Journal : Information Technology Journal is a peer-reviewed open-access journal published in every six months, namely in July and December. We invite researchers, academics, and practitioners to submit their original research articles to our SINTA 4 indexed journal in the field of Information Technology. Intechno Journal (e-ISSN 2655-1438 | p-ISSN 2655-1632) published by Universitas Amikom Yogyakarta in collaboration with Indonesian Computer, Electronics and Instrumentation Support Society (IndoCEISS) to promote high-quality Information Technology (IT) research among academics and practitioners alike, including computer scientists, Software Engineering & Big Data, Multimedia, Networking, IT professionals, and other stakeholders in the IT industry. Contributed papers must be original (similarity score <= 30%) and offer an impactful contribution. At least two independent reviewers will review each manuscript in the relevant field to ensure the publication of only top-quality contributions. Intechno Journal offers an open-access license (CC-BY) while retaining the copyright for the authors.
publisher: Universitas Amikom Yogyakarta
language: en
publication name: Intechno Journal : Information Technology Journal
issn: 2655-1632
items: User Satisfaction with E-BRAY Digital Library: An Integrated EUCS and TAM Analysis Using PLS-SEM
items: A Comparative Analysis of Decision Tree, Logistic Regression, and Support Vector Machine Algorithms in Sentiment Analysis of Threads App Reviews
items: Implementation of a 3D Animation Production Pipeline for a Psychological Well-Being Trailer : Visualizing Self-Acceptance Using Autodesk Maya
items: An Advanced Deep Learning Approach for Automatic Disease Recognition and Classification in paddy leaf disease detection
items: The Effectiveness of Dropout Layers in LSTM Architecture for Reducing Overfitting in Sony Stock Prediction
items: Development of a Web-Based Teacher Attendance System in Government Agencies: A Case Study at the Ministry of Religious Affairs
items: Integrating CVSS, OWASP, and APPI for a Comprehensive Risk Analysis of SQL Injection Vulnerabilities in E-Commerce
items: Application of the SAW Method in a Decision Support System to Determine the Best Public Transportation Mode for UPN “Veteran” Jakarta Students
items: Decision Support System for Selecting the Best University for Vocational School Graduates Majoring in Multimedia Using the TOPSIS Method
items: Comparative Analysis of Live Action Film Production Management Using Critical Path Method (CPM) Versus Conventional Production Processes
items: Prototype for Implementing Data Exchange with The FHIR-HL7 Standard in The Personal Health Record Application
items: EEG Emotion Recognition using Deep Neural Network (DNN) in Virtual Reality Environments
items: Reverse Engineering GitHub CoPilot: Creating an OpenAI-Compatible Endpoint for Enhanced Developer Integration
items: Forecasting A Major Banking Corporation Stock Prices Using LSTM Neural Networks
items: Quality Evaluation of Ticketing Management System Using ISO/IEC25010:2023 Standards and AHP Method
items: Testing of Usability and Correctness Aspects in Marketing and Ordering Information Systems
items: EEG Signal Classification Using Low Temporal Information in Virtual Reality Environments
items: Implementasi Metode Waterfall Pada Perancangan Website Seminar Nasional KOMA
items: Analysis System Presensi Menggunakan RFID Card Dengan Modul Mifire RC522 Berbasis Arduino Uno
items: Analisis Dan Implementasi Website Dengan Metode Prototyping Sebagai Media Informasi Pada Dusun Dondong
items: Perancangan Media Pembelajaran Bahasa Indonesia untuk Anak Sekolah Dasar
items: Analisis Sentiment Kepuasan Masyarakat Terhadap Identitas Kependudukan Digital Dengan Multinomial Naïve Bayes
items: Rancang Bangun E-Learning Penggolongan Jenis Napza Menggunakan Metode Waterfall
items: Strategi Optimisasi Kata Kunci dalam Meningkatkan Visibilitas di Mesin Pencari
items: Implementasi Algoritma SVM Dalam Pengembangan Sistem Presensi Berbasis Face Recognition
items: Implementasi Voice To Text Pada Invoice Checking Berbasis Web
items: Aplikasi Monitoring Laporan Data Hasil Pengolahan TBS Kelapa Sawit Berbasis Mobile Pada PT. Perkebunan Nusantara VII
items: Sistem Informasi Peramalan Stok Barang Toko Al Umm Menggunakan Metode Single Moving Average
items: Implemantasi Autentikasi Hotspot Menggunakan Radius Server Mikrotik Router Pada Rumah Sakit Misi Lebak
items: Penerapan Metode Simple Additive Weighting Untuk Menentukan Siswa Penerima Bantuan Dana SMK PL Leonardo Klaten

User Satisfaction with E-BRAY Digital Library: An Integrated EUCS and TAM Analysis Using PLS-SEM
type: item
description: Purpose: This study aims to evaluate user satisfaction with the E-BRAY digital library by integrating the End-User Computing Satisfaction (EUCS) model and the Technology Acceptance Model (TAM), with a particular focus on identifying key determinants of end-user satisfaction in a regional digital library context. Methods/Study design/approach: Data were collected through an online survey involving 106 active users of the E-BRAY digital library system. The relationships between system quality dimensions (accuracy, content, security), perceived usefulness, perceived ease of use, and user satisfaction were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Result/Findings: The results indicate that perceived usefulness has the strongest and statistically significant effect on user satisfaction (B = 0.712, p < 0.01), supporting the central assumption of the TAM framework. Perceived ease of use shows a positive but weaker and statistically insignificant influence on satisfaction, while other system quality dimensions—accuracy, content, and security—exhibit negligible direct effects. These findings confirm that perceived usefulness plays a critical mediating role between system quality and end-user satisfaction in the digital library environment. Novelty/Originality/Value: This study contributes theoretically by empirically validating perceived usefulness as a key mediating construct linking EUCS system quality dimensions to user satisfaction within a regional digital library setting—an area that remains underexplored in prior research. Practically, the findings provide actionable insights for digital library managers, emphasizing the importance of enhancing system usefulness through improved search functionality, metadata completeness, and research-support features, alongside strengthening security mechanisms to foster long-term user trust.
subject: Articles
  topic: section
subject: Perpustakaan Digital
  topic: keywords
subject: Kepuasan Pengguna
  topic: keywords
subject: EUCS
  topic: keywords
subject: TAM
  topic: keywords
subject: PLS-SEM
  topic: keywords
creator: Ferdinand Murni Hamundu
creator: Muhammad Dimas Rusdarianto
creator: Putri Eka Wulandari Alam
creator: Selin Rahmadani
creator: Deswita Maharani
creator: Khusnul Qhatimah Khamaisyah
rights: Copyright (c) 2026 Intechno Journal : Information Technology Journal https://creativecommons.org/licenses/by/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 56
ending page: 64
doi: 10.24076/intechnojournal.2025v7i2.2499

A Comparative Analysis of Decision Tree, Logistic Regression, and Support Vector Machine Algorithms in Sentiment Analysis of Threads App Reviews
type: item
description: Purpose: This study aims to analyze user sentiment regarding the Threads application by comparing the performance of different machine learning models. As a relatively new social media platform, understanding user feedback is crucial for identifying service gaps and improving user retention. The research seeks to determine which algorithm provides the highest precision in classifying user reviews into positive and negative sentiments. Methods: The research utilized a dataset of 3,000 user reviews scraped from the Google Play Store. The methodology followed a systematic text mining workflow, including preprocessing stages such as noise removal, tokenization, stopword removal, and stemming. Feature extraction was performed using the Term Frequency-Inverse Document Frequency (TF IDF) method. Three machine learning algorithms—Support Vector Machine (SVM), Decision Tree, and Logistic Regression—were implemented and evaluated using K-Fold Cross Validation to ensure statistical reliability. Result: The experimental results indicate that the Support Vector Machine (SVM) consistently outperformed the other two models. SVM achieved a superior average accuracy of 88.18%, with a peak performance reaching 92.69% during K-Fold testing. Logistic Regression and Decision Tree showed lower accuracy and less stability in handling the high-dimensional text data. These figures confirm that SVM is the most effective model for analyzing the linguistic nuances found in Threads app reviews. Novelty/Originality/Value: This research contributes to the field of software evaluation by providing an empirical comparison of classification algorithms specifically for newly launched social media platforms like Threads. The findings offer practical value for developers to automate the monitoring of user satisfaction. The study demonstrates that integrating rigorous TF-IDF weighting with SVM significantly enhances the accuracy of sentiment detection in short-form mobile application reviews.
subject: Articles
  topic: section
subject: Policies
  topic: category
subject: Support Vector Machine (SVM)
  topic: keywords
subject: Decision Tree
  topic: keywords
subject: Threads
  topic: keywords
subject: Analisis Sentiment
  topic: keywords
subject: Logistic Regression
  topic: keywords
creator: Rahmat Hidayat
creator: Farhan Aminulhaq
rights: Copyright (c) 2026 Intechno Journal : Information Technology Journal https://creativecommons.org/licenses/by/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 45
ending page: 55
doi: 10.24076/intechnojournal.2025v7i2.2497

Implementation of a 3D Animation Production Pipeline for a Psychological Well-Being Trailer : Visualizing Self-Acceptance Using Autodesk Maya
type: item
description: Purpose: This study aims to investigate the implementation of a structured 3D animation production pipeline in the creation of a 3D animation trailer themed around psychological well-being with a self-acceptance dimension. The research addresses the lack of academic studies that specifically discuss the technical and procedural aspects of 3D animation trailer production, as most previous works emphasize narrative messages or educational outcomes rather than the production workflow itself. Methods: A practice-based research approach was applied by implementing a three-stage animation production pipeline consisting of pre-production, production, and post-production. Pre-production included concept development, scriptwriting, storyboard and concept art creation, and dubbing. The production stage involved material collecting, studio setup, and keyframe-based animation using Autodesk Maya. Post-production comprised frame-by-frame rendering using Arnold, compositing and editing with Adobe After Effects, internal evaluation, expert-based beta testing, and publishing via YouTube. All stages were systematically documented to ensure clarity and reproducibility. Result: The results show that the implemented pipeline enabled efficient task distribution, consistent visual quality, and accurate synchronization between animation and audio across 15 scenes with a total duration of 97 seconds. Internal evaluation confirmed that all scenes met predefined technical, visual, and narrative standards. Furthermore, expert-based evaluation by media professionals yielded a feasibility score of 92% across five aspects: animation quality, camera movement, lighting, sound design, and narrative timing. These findings indicate that the proposed pipeline effectively supports short 3D animation trailer production by reducing workflow ambiguity and improving coordination between visual and audio components. Novelty: The novelty of this research lies in its detailed and reproducible documentation of…
subject: Articles
  topic: section
subject: Policies
  topic: category
subject: Animation Pipeline
  topic: keywords
subject: 3D Animation
  topic: keywords
subject: Psychological Well-Being
  topic: keywords
subject: Self-Acceptance
  topic: keywords
subject: Autodesk Maya
  topic: keywords
creator: Yoseph Satria Praka
creator: Rifki Setiawan
creator: Syasya Amalia
creator: Annisa Eka Danti
creator: Candi Rahayu Tri Prameswari
creator: Desna Romarta Tambun
creator: Indah Sari Mukkaramah
rights: Copyright (c) 2026 Intechno Journal : Information Technology Journal https://creativecommons.org/licenses/by/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 65
ending page: 76
doi: 10.24076/intechnojournal.2025v7i2.2485

An Advanced Deep Learning Approach for Automatic Disease Recognition and Classification in paddy leaf disease detection
type: item
description: Purpose: Accurate detection of paddy leaf diseases is essential to ensure optimal crop yield and effective disease management. Methods/Study design/approach: In this study, we propose a hybrid deep learning model combining Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), and an Attention mechanism for paddy leaf disease classification using the Paddy Doctor dataset. The CNN layers extract spatial features from leaf images, the LSTM captures contextual relationships between these features, and the Attention mechanism emphasizes the most relevant patterns for accurate classification. Result/Findings: Experimental results show that the proposed CNN+LSTM+Attention model achieves 95.5% accuracy, 98.12% precision, 98.3% recall, and 0.994 macro AUC, outperforming a simple CNN-3 layer while offering competitive performance compared to state-of-the-art architectures such as ResNet34 and Xception. Novelty/Originality/Value: These results demonstrate that the proposed model is highly effective in detecting paddy leaf diseases with minimal false negatives, providing a reliable and practical solution for automated paddy disease monitoring systems
subject: Articles
  topic: section
subject: Policies
  topic: category
subject: Deep Learning, Convolutional Neural Network, Long Short-Term Memory, Attention mechanism, Paddy leaf disease detection
  topic: keywords
creator: Robert Marco
creator: Alva Hendi Muhammad
creator: Nur Aini
creator: Yana Hendriana
rights: Copyright (c) 2026 Intechno Journal : Information Technology Journal https://creativecommons.org/licenses/by/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 86
ending page: 94
doi: 10.24076/intechnojournal.2025v7i2.2482

The Effectiveness of Dropout Layers in LSTM Architecture for Reducing Overfitting in Sony Stock Prediction
type: item
description: This study investigates the effectiveness of dropout layers in reducing overfitting within Long Short-Term Memory (LSTM) neural networks for Sony stock price prediction. Financial time series forecasting presents significant challenges due to market volatility and noise, often leading to models that overfit historical data while failing to generalize to unseen market conditions. We implemented two LSTM models: one without dropout layers and another with dropout layers (rate=0.2) applied after each LSTM layer. Using historical Sony stock data from 2015-2025, we evaluated both models using Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) metrics. The model with dropout demonstrated superior performance on testing data, achieving RMSE of 0.5971, MAE of 0.4411, and MAPE of 2.1502%, compared to the model without dropout which obtained RMSE of 0.7124, MAE of 0.5636, and MAPE of 2.6684%. Furthermore, the dropout model exhibited significantly reduced overfitting, with smaller performance gaps between training and testing datasets across all metrics, particularly in MAPE where the difference approached zero (0.0509%). This research provides empirical evidence that dropout regularization effectively enhances LSTM model generalization for stock prediction, offering practical value for developing more reliable financial forecasting models. Future research could explore optimal dropout rates for different market conditions and investigate combinations of dropout with other regularization techniques.
subject: Articles
  topic: section
subject: Long Short-Term Memory
  topic: keywords
subject: Dropout
  topic: keywords
subject: Stock Prediction
  topic: keywords
subject: Overfitting
  topic: keywords
subject: Financial Time Series
  topic: keywords
creator: Roni Saputra
creator: Dian Ade Kurnia
creator: Yudhistira Arie Wijaya
rights: Copyright (c) 2026 Intechno Journal : Information Technology Journal https://creativecommons.org/licenses/by/4.0
date: 2025-12-31
publication date: 2025-12-31
starting page: 77
ending page: 85
doi: 10.24076/intechnojournal.2025v7i2.2369

Development of a Web-Based Teacher Attendance System in Government Agencies: A Case Study at the Ministry of Religious Affairs
type: item
description: Objective: This study addresses the issues of inefficiency and lack of transparency in manual attendance recording systems in government institutions, particularly in the Ministry of Religious Affairs. The study aims to develop a web-based teacher attendance information system that addresses the inaccuracy and susceptibility to manipulation found in conventional paper-based methods, while improving administrative accountability. Method: The system was developed using an iterative software engineering approach that integrates comprehensive needs analysis, modular design architecture, and functional testing stages. The methodology combines web-based technology with user-centered interface design, accommodating the needs of administrative staff and teaching staff. The development phase includes gathering stakeholder requirements, planning the system architecture, implementation using the Django framework, and systematic validation procedures. Results: The implemented system successfully demonstrated improved accuracy in attendance recording, automatic validation of working hours, comprehensive absence history tracking, and Excel data export capabilities. Initial testing revealed increased reporting efficiency and a significant reduction in administrative processing time. The system achieved seamless integration with existing government workflows while maintaining data integrity and security standards. Contribution: This research contributes innovative solutions specifically tailored to Indonesian government institutions, bridging the integration of information technology with human resource management governance. The study presents a strategic digital transformation approach for public sector administrative services, offering a replicable model for similar government organizations seeking to modernize their attendance management systems.
subject: Articles
  topic: section
subject: Policies
  topic: category
subject: Sistem Absensi Digital Aplikasi Web Pengelolaan Kepegawaian Validasi Waktu Kementerian Agama Django
  topic: keywords
creator: Farwah Assyifaurrohmah
creator: Ahmad Fuzul Mubin
creator: Ahmad Tabrani Tabrani
rights: Copyright (c) 2025 Intechno Journal : Information Technology Journal
date: 2025-07-31
publication date: 2025-07-31
starting page: 24
ending page: 33
doi: 10.24076/intechnojournal.2025v7i1.2233

Integrating CVSS, OWASP, and APPI for a Comprehensive Risk Analysis of SQL Injection Vulnerabilities in E-Commerce
type: item
description: Purpose: By integrating the technical severity evaluation provided by the Common Vulnerability Scoring System (CVSS), the business risk assessment framework of the OWASP Risk Rating Methodology, and the legal compliance standards outlined in Japan’s Act on the Protection of Personal Information (APPI), this study aims to conduct a holistic risk analysis of SQL injection vulnerabilities within e-commerce platforms. The primary objective is to offer stakeholders a robust and actionable model for enhancing the security of online shopping environments. Methods/Study design/approach: This study employed a mixed-methods experimental case study approach. A custom-built, intentionally vulnerable e-commerce web application was subjected to a simulated SQL injection attack to extract fictitious user and transaction data. The technical severity of the vulnerability was quantified using CVSS v3.1, while the OWASP Risk Rating Methodology was applied to assess the associated business risks. Additionally, the legal implications were evaluated in accordance with Japan’s Act on the Protection of Personal Information (APPI). Result/Findings: The simulation confirmed that a SQL injection attack could extract sensitive personal and transactional data. The vulnerability was rated “Critical” with a CVSS v3.1 score of 9.1, and the OWASP assessment indicated a “High” business risk due to financial impact, APPI non-compliance, and privacy violations. The leaked purchase history was classified under APPI as “Personal Information Requiring Special Attention.” Novelty/Originality/Value: This study’s main contribution is its integrated methodology that links CVSS, OWASP, and APPI frameworks to assess cyber threats. It offers a multidimensional view, showing how a technical vulnerability can lead to serious legal and business consequences under specific data protection laws.
subject: Articles
  topic: section
subject: SQL Injection
  topic: keywords
subject: Risk Assessment
  topic: keywords
subject: CVSS
  topic: keywords
subject: OWASP
  topic: keywords
subject: APPI (Act on the Protection of Personal Information)
  topic: keywords
creator: Muhammad Kholilul Adrian
creator: Prajna Deshanta Ibnugraha
creator: Hilal Hudan Nuha
rights: Copyright (c) 2025 Intechno Journal : Information Technology Journal
date: 2025-07-31
publication date: 2025-07-31
starting page: 17
ending page: 23
doi: 10.24076/intechnojournal.2025v7i1.2184

Application of the SAW Method in a Decision Support System to Determine the Best Public Transportation Mode for UPN “Veteran” Jakarta Students
type: item
description: Purpose: The high use of private vehicles in Jakarta exacerbates traffic congestion, making public transportation a vital alternative, especially for students of the National Development University "Veteran" Jakarta (UPNVJ). However, with numerous options available, many students struggle to select the most suitable mode of transport. This study aims to aid this decision-making process by developing a Decision Support System (DSS) to evaluate and recommend the most optimal public transportation mode. Methods/Study design/approach: This research implements a DSS using the Simple Additive Weighting (SAW) method. Five transportation modes were analyzed: MRT, KRL, TransJakarta, Jaklingko, and Online Motorcycle Taxi. The evaluation was based on five criteria: cost, speed, comfort, accessibility, and safety. Primary data was collected through questionnaires distributed to students, which were then processed using normalization and weighting based on the perceived importance of each criterion. Result/Findings: The analysis revealed that Online Motorcycle Taxi is the top choice among students (score: 0.859), followed by MRT (score: 0.853) and TransJakarta (score: 0.837). The results indicate that each mode has distinct advantages; for instance, MRT excels in comfort and safety, while Jaklingko is perceived as the most economical option. Novelty/Originality/Value: This study demonstrates that flexibility and accessibility are the primary considerations for students when choosing transportation. The findings provide a useful, structured reference for students to select efficient transport that meets their needs, moving beyond anecdotal decision-making. The research effectively applies the SAW method to offer a practical solution to a common student mobility challenge.
subject: Articles
  topic: section
subject: Transportasi Umum
  topic: keywords
subject: Sistem Pendukung Keputusan
  topic: keywords
subject: SAW
  topic: keywords
creator: Fausta Sarah Nareswari
creator: Rafa Muhammad Ghifar Ramadhan
creator: Muhammad Hanif Al-Ghifari
creator: Zatin Niqotaini
rights: Copyright (c) 2025 Intechno Journal : Information Technology Journal
date: 2025-07-31
publication date: 2025-07-31
starting page: 1
ending page: 7
doi: 10.24076/intechnojournal.2025v7i1.2125

Decision Support System for Selecting the Best University for Vocational School Graduates Majoring in Multimedia Using the TOPSIS Method
type: item
description: Purpose: According to Statistics Indonesia (2023), there are around 1.6 million vocational secondary school (SMK) graduates in Indonesia, over 30% of whom come from the Information and Communication Technology field, particularly the Multimedia major. However, more than 40% of them do not proceed to higher education (Tracer Study, Kemendikbud Ristek, 2023), partly due to difficulties in selecting universities that align with their practical skills. This study aims to develop a decision support system that helps Multimedia graduates choose higher education institutions that match their vocational background. Methods/Study design/approach: The study applies the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, using six evaluation criteria: program accreditation, multimedia facilities, industry partnerships, alumni reputation, tuition fees, and internship opportunities. Data were gathered from official secondary sources such as BAN-PT and PDDikti. The TOPSIS method was then used to rank university alternatives based on weighted criteria. Result/Findings: The highest-scoring alternative obtained a preference score of 0.6968, representing an institution with superior accreditation, strong industry collaboration, and complete multimedia infrastructure. Sensitivity analysis showed consistent rankings for some alternatives, while others shifted depending on changes in criteria weights. Novelty/Originality/Value: This study offers a replicable and adaptable decision support system that enables vocational school graduates to make informed, data-driven decisions in selecting relevant higher education pathways. The framework can be customized for other vocational fields or regional applications, providing practical value for both students and education planners.
subject: Articles
  topic: section
subject: Sistem Pendukung Keputusan
  topic: keywords
subject: Pemilihan Perguruan Tinggi
  topic: keywords
subject: Metode TOPSIS
  topic: keywords
subject: SMK Multimedia
  topic: keywords
subject: Pendidikan Vokasi
  topic: keywords
creator: Lisa Febriyanti
creator: Mahdiyyah Febrinazahra
creator: Yoga Aditya Ramasahdan
creator: Zatin Niqotaini
rights: Copyright (c) 2025 Intechno Journal : Information Technology Journal
date: 2025-07-31
publication date: 2025-07-31
starting page: 8
ending page: 16
doi: 10.24076/intechnojournal.2025v7i1.2108

Comparative Analysis of Live Action Film Production Management Using Critical Path Method (CPM) Versus Conventional Production Processes
type: item
description: The production of the film “Kinah dan Redjo”, by Universitas Amikom and MSV Sinema, has been completed, prompting researchers to conduct an analysis and evaluation of the production management applied. The focus of this study is on time and cost, which are critical factors supporting film production. An extended production duration was identified as a challenge, as it reduces effectiveness and leads to cost overruns. Therefore, this study aims to compare project management strategies for successful planning and control, using both conventional methods and the Critical Path Method (CPM). This analysis is expected to yield faster project completion and establish efficient, productive standards for future productions. The conventional approach indicated a total production duration of 681 days, comprising 120 days for pre-production, 18 days for production, and 551 days for post-production. Upon analysis using the CPM method, the total duration was reduced to 459 days, including 113 days for pre-production, 152 days for production, and 191 days for post-production. The graphical comparison of methods shows significant cost fluctuations across each production phase with the conventional method, especially increased costs during production despite the shorter duration. Conversely, the CPM method demonstrates more controlled and measurable durations and costs. This study underscores the importance of cost optimization, standardization of the Work Breakdown Structure (WBS), and hybrid modeling to enhance efficiency in dynamic film projects. Furthermore, this analysis serves as a foundational reference for the architectural planning of future applications incorporating artificial intelligence (AI) integration. AI has the potential to accelerate scheduling, optimize resource allocation, and streamline cost management and production design, thereby improving overall project efficiency.
subject: Articles
  topic: section
subject: Film Production
  topic: keywords
subject: Project Management
  topic: keywords
subject: Critical Path Method
  topic: keywords
subject: Optimization
  topic: keywords
subject: Scheduling
  topic: keywords
creator: Agung Nugroho
creator: Mohammad Suyanto
creator: Dhani Ariatmanto
rights: Copyright (c) 2025 Intechno Journal : Information Technology Journal
date: 2025-07-31
publication date: 2025-07-31
starting page: 34
ending page: 44
doi: 10.24076/intechnojournal.2025v7i1.2019

Prototype for Implementing Data Exchange with The FHIR-HL7 Standard in The Personal Health Record Application
type: item
description: Monitoring health is essential for early disease detection, prevention, and managing chronic conditions. Active tracking empowers patients to make informed decisions and adhere to treatments, improving outcomes. However, fragmented medical records across facilities can lead to incomplete information. Integrating records through interoperable systems provides patients and providers with a comprehensive health overview, ensuring continuity, reducing redundancies, and enhancing collaboration. Centralized health data enables better monitoring for patients and more personalized, efficient care from healthcare professionals. This study focuses on developing a prototype for data exchange implementation using the FHIR-HL7 standard in a Personal Health Record (PHR) application. The prototype is tested with selected resources: Patient, Encounter, Observation, and Condition. The data flow involves obtaining patient medical records from an Electronic Health Record (EHR) and displaying them in a Personal Health Record application, ensuring secure access via National Identification Number (NIK) matching as Personal Identification Number. The approach includes mapping FHIR resources to relevant data structures, modifying both EHR and PHR applications to support the data exchange process. The results demonstrate that patient medical records stored in EHR can be accessed by patients through the PHR apps. Specific FHIR resources enable the exchange of various data types: patient demographics using the Patient resource, diagnoses using the Condition resource, and vital signs (e.g., systolic/diastolic blood pressure, weight, height) using the Observation resource. This prototype highlights the feasibility of integrating FHIR-HL7 standards for interoperable health data exchange, enhancing patient engagement and data accessibility.
subject: Articles
  topic: section
subject: FHIR-HL7
  topic: keywords
subject: PHR
  topic: keywords
subject: Interoperability
  topic: keywords
subject: Data exchange
  topic: keywords
subject: EHR
  topic: keywords
creator: Hendri Kurniawan Prakosa
creator: Hasan Nurul Ibad
creator: Saiful Anwar
rights: Copyright (c) 2024 Intechno Journal : Information Technology Journal
date: 2024-12-31
publication date: 2024-12-31
starting page: 122
ending page: 129
doi: 10.24076/intechnojournal.2024v6i2.1902

EEG Emotion Recognition using Deep Neural Network (DNN) in Virtual Reality Environments
type: item
description: Purpose: The purpose of this study is to explore the integration of EEG technology with virtual reality (VR) systems to enhance therapeutic interventions, improve cognitive state recognition, and develop personalized immersive experiences. Specifically, it investigates the classification of EEG signals in a VR environment using machine learning models and identifies the most effective methods for individual-level analysis. Methods: The study utilized EEG data collected from 31 participants using the Muse 2016 headset, with electrodes positioned according to the 10-20 international system. EEG signals were analyzed for features such as statistical metrics (mean, median, standard deviation, skewness, and kurtosis) and Hjorth parameters (activity, mobility, complexity). Machine learning models, including K-Nearest Neighbors (KNN), Random Forest (RF), and Support Vector Machine (SVM), were evaluated for their performance in classifying emotional and cognitive states in a VR environment. Result: The results indicate that the Deep Neural Network (DNN) outperformed SVM and KNN models, achieving the highest average classification accuracy. SVM demonstrated consistent performance, with accuracy values consistently above 0.8 across subjects, while KNN showed greater variability and lower overall performance. DNN's architecture, incorporating two hidden layers with ReLU activation and a softmax output layer, demonstrated superior capability in modeling complex EEG patterns. The findings emphasize the effectiveness of DNN in handling high-dimensional and non-linear data, particularly for multi-class classification tasks. Novelty: This study is novel in its focus on personalized machine learning model performance in a VR-EEG setup. Instead of a one-size-fits-all approach, it emphasizes individualized analysis, identifying the most effective model for each participant.
subject: Articles
  topic: section
subject: Policies
  topic: category
subject: EEG
  topic: keywords
subject: DNN
  topic: keywords
subject: VR
  topic: keywords
subject: Brain Signal
  topic: keywords
subject: Emotion Classification
  topic: keywords
creator: I Made Artha Agastya
creator: Robert Marco
creator: Dini Oktarina Dwi Handayani
rights: Copyright (c) 2024 Intechno Journal : Information Technology Journal
date: 2024-12-31
publication date: 2024-12-31
starting page: 114
ending page: 121
doi: 10.24076/intechnojournal.2024v6i2.1903

Reverse Engineering GitHub CoPilot: Creating an OpenAI-Compatible Endpoint for Enhanced Developer Integration
type: item
description: This paper presents the reverse engineering of GitHub CoPilot to develop an OpenAI-compatible endpoint, enabling broader access and integration possibilities for AI-assisted code completion. By analyzing CoPilot's communication protocols and creating a proxy server that translates OpenAI API requests to CoPilot's internal API, we bridge the gap between proprietary tools and open standards. The implementation, allows developers to utilize CoPilot's capabilities within their preferred environments using the familiar OpenAI API interface. We detail the system architecture, authentication mechanisms, request processing pipeline, and performance optimization techniques. Our results demonstrate successful integration, with robust performance metrics, including low response times and high compatibility rates. This work opens avenues for enhanced developer productivity and flexibility in AI-assisted coding tools.
subject: Articles
  topic: section
subject: Policies
  topic: category
subject: Reverse Engineering
  topic: keywords
subject: OpenAI
  topic: keywords
creator: Nur Arifin Akbar
creator: Ardian Webi Krida
creator: Akbar Setiawan
rights: Copyright (c) 2024 Intechno Journal : Information Technology Journal
date: 2024-12-31
publication date: 2024-12-31
starting page: 95
ending page: 107
doi: 10.24076/intechnojournal.2024v6i2.1895

Forecasting A Major Banking Corporation Stock Prices Using LSTM Neural Networks
type: item
description: The increasing complexity of stock market predictions necessitates advanced computational techniques to address the unique challenges posed by financial data's non-linear and volatile nature. This study aims to leverage Long Short-Term Memory (LSTM) neural networks to accurately forecast stock prices, using historical data collected from a major banking corporation as a primary source. The LSTM model excels at processing sequential time-series data, allowing it to predict monthly stock closing prices over a one-year horizon with a high degree of precision. Our findings indicate a Root Mean Squared Error (RMSE) of 3.2, underscoring the model's efficiency and reliability in financial forecasting tasks. The novelty of this research lies in the systematic incorporation of preprocessing techniques and fine-tuned hyperparameters to optimize model performance. Furthermore, this study explores the practical implications of implementing LSTM models in real-world trading scenarios, analyzing their adaptability to dynamic market conditions and their potential integration into automated trading systems. These findings contribute to the growing body of knowledge in financial analytics and demonstrate the viability of machine learning-based solutions for accurate and robust market predictions.
subject: Articles
  topic: section
subject: Policies
  topic: category
subject: Stock Market Prediction
  topic: keywords
subject: LSTM
  topic: keywords
subject: Time-Series Analysis
  topic: keywords
subject: Neural Network
  topic: keywords
subject: Forecasting
  topic: keywords
creator: Budi Wijaya Rauf
rights: Copyright (c) 2024 Intechno Journal : Information Technology Journal
date: 2024-12-31
publication date: 2024-12-31
starting page: 108
ending page: 113
doi: 10.24076/intechnojournal.2024v6i2.1888

Quality Evaluation of Ticketing Management System Using ISO/IEC25010:2023 Standards and AHP Method
type: item
description: Purpose: Information Technology plays a crucial role in supporting education service systems. When system-related issues arise, a Ticket Management System (TMS) becomes essential to address various software and hardware problems. Evaluating the performance and quality of TMS applications is necessary to ensure their effectiveness. This study assesses the quality of a TMS application developed by University of Amikom Yogyakarta, using ISO/IEC 25010:2023. Methods/Study design/approach: The Analytic Hierarchy Process method is employed to prioritize three key ISO/IEC 25010 characteristics by engaging TMS application users. Following the ranking, the study conducts quality measurements using questionnaires and black box testing. The questionnaire results are assessed using a Likert scale to determine scores for the TMS application based on the sub-characteristics of the three selected ISO/IEC 25010:2023 characteristics and the AHP-derived rankings. Result/Findings: The findings indicate that the TMS application achieved a quality score of 4.354. This shows that the TMS application is in the good category. Novelty/Originality/Value: The study highlights the need for performance efficiency improvements, specifically in the Time Behavior sub-characteristic, to enhance the overall quality of the TMS application.
subject: Articles
  topic: section
subject: Policies
  topic: category
subject: Software Evaluation
  topic: keywords
subject: Quality Assurance
  topic: keywords
subject: Ticket Management System
  topic: keywords
subject: ISO/IEC 25010
  topic: keywords
subject: Analytic Hierarchy Process
  topic: keywords
creator: Puji Ariningsih
creator: Alva Hendi Muhammad
rights: Copyright (c) 2024 Intechno Journal : Information Technology Journal
date: 2024-12-31
publication date: 2024-12-31
starting page: 86
ending page: 94
doi: 10.24076/intechnojournal.2024v6i2.1870

Testing of Usability and Correctness Aspects in Marketing and Ordering Information Systems
type: item
description: Purpose: This research systematically evaluates the quality of the web-based marketing and ordering information systems at UD. Percetakan Citra Satria by focusing on the aspects of usability and correctness, aiming to determine the effectiveness of the system in meeting user needs. Methods/Study design/approach: Data collection was conducted through observation and questionnaires. The observation aimed to identify issues during the use of the marketing and ordering information systems at UD. Percetakan Citra Satria, while the questionnaire, using a Likert scale, involved 8 employees and 70 customers to assess usability and correctness. The system was implemented and tested by allowing users to interact with it, with evaluations analyzed using the McCall model. The testing focused on usability, reflecting ease of use, and correctness, ensuring information accuracy, both critical for enhancing user experience and operational effectiveness. Result/Findings: The test results indicate that the overall quality of the web-based marketing and ordering information systems at UD. Citra Satria Printing achieved a score of 85% for the usability aspect and 85.3% for correctness. These scores are classified as very good according to the quality factor percentage scale. Novelty/Originality/Value: This study introduces novelty in applying quality testing for a web-based marketing and ordering information systems using the McCall method, focusing on two main aspects: usability and correctness. The novelty lies in its specific application context, namely in the printing industry (UD. Percetakan Citra Satria), as well as the use of questionnaires to directly incorporate the perspectives of employees and customers.
subject: Articles
  topic: section
subject: Policies
  topic: category
subject: Testing
  topic: keywords
subject: Information Systems
  topic: keywords
subject: McCall
  topic: keywords
subject: Usability
  topic: keywords
subject: Correctness
  topic: keywords
creator: Nabilah Faqita Masyora
creator: Nahrun Hartono
creator: Rahman Rahman
rights: Copyright (c) 2024 Intechno Journal : Information Technology Journal
date: 2024-12-31
publication date: 2024-12-31
starting page: 73
ending page: 85
doi: 10.24076/intechnojournal.2024v6i2.1807

EEG Signal Classification Using Low Temporal Information in Virtual Reality Environments
type: item
description: Purpose: This research systematically compares the performance of K-Nearest Neighbors (KNN), Random Forest (RF), and Support Vector Machine (SVM) in recognizing emotional and cognitive states from EEG data in a virtual reality (VR) environment. It aims to identify the model with the highest accuracy for each participant. Methods: EEG data were collected from four channels (TP9, AF7, AF8, TP10) with a data range of 0.0 - 1682.815 µV and a sampling rate of 2 Hz. The sampling rate is shallow compared to the standard EEG datasets. Features extracted included statistical measures (mean, standard deviation, skewness, kurtosis) and Hjorth parameters (activity, mobility, complexity), classifier (SVM, RF, KNN). Each classifier’s performance was evaluated using accuracy, indicating the proportion of correctly classified instances. Result: RF achieved the highest average accuracy but showed more significant variability. SVM demonstrated a high median accuracy with consistent performance, as indicated by a narrow interquartile range (IQR) and few outliers. KNN exhibited the lowest median accuracy and highest variability, suggesting sensitivity to data characteristics and parameters. These findings highlight RF’s potential for consistent performance with careful tuning and SVM’s reliability. Novelty: The research’s novelty lies in its personalized performance analysis, evaluating each model’s accuracy individually for participants. This tailored approach reveals the best-performing model for each person, emphasizing customized machine-learning applications in VR-EEG systems. The study’s detailed, participant-specific evaluation enhances emotion and cognitive state recognition precision, advancing individualized VR therapeutic interventions and cognitive research methodologies.
subject: Articles
  topic: section
subject: Policies
  topic: category
subject: EEG
  topic: keywords
subject: VR
  topic: keywords
subject: Brain Signal
  topic: keywords
subject: Signal Classification
  topic: keywords
subject: Machine Learning
  topic: keywords
creator: I Made Artha Agastya
creator: Robert Marco
creator: Mohamad Firdaus
rights: Copyright (c) 2024 Intechno Journal (Information Technology Journal)
date: 2024-07-31
publication date: 2024-07-31
starting page: 1
ending page: 9
doi: 10.24076/intechnojournal.2024v6i1.1698

Implementasi Metode Waterfall Pada Perancangan Website Seminar Nasional KOMA
type: item
description: Teknologi informasi telah menjadi bagian yang tak terpisahkan dari berbagai aspek kehidupan manusia. Kegiatan seperti seminar nasional tidak lepas dari pengaruh teknologi informasi dalam penyelenggarannya. Seminar Nasional KOMA telah menggunakan Google Form sebagai platform untuk pendaftaran dan penyampaian informasi umum. Penggunaan google form memiliki kelemahan yaitu panitia harus menyesuaikan alur pendaftaran dengan sistem yang ada pada google form. Salah satu cara untuk meningkatkan efektivitas penyelenggaraan seminar nasional adalah dengan memanfaatkan teknologi, khususnya pengembangan website. Salah satu metode pengembangan perangkat lunak yaitu metode waterfall. Metode ini melibatkan serangkaian tahapan yang meliputi analisis kebutuhan, perancangan, pengembangan, pengujian, dan implementasi. Dalam konteks pengembangan website untuk seminar nasional KOMA, penggunaan metode waterfall dapat memberikan kerangka kerja yang terstruktur dan jelas untuk merencanakan serta mengembangkan solusi yang tepat sesuai dengan kebutuhan yang ada. Penelitian ini berhasil mengimplementasikan metode waterfall dalam perancangan website seminar nasional "KOMA" yang dapat mengakomodasi kebutuhan informasi seminar proses pendaftaran dan pengelolaan administrasi. Pengujian Black Box Testing hasil black box telah sesuai dengan hasil yang diharapkan. Berdasarkan pengujian yang dilakukan menggunakan System Usability Scale (SUS) diperoleh nilai 83 yang termasuk ke dalam kategori acceptable dengan grade B.
subject: Articles
  topic: section
subject: Policies
  topic: category
subject: website
  topic: keywords
subject: seminar
  topic: keywords
subject: waterfall
  topic: keywords
subject: SUS
  topic: keywords
creator: Irma Rofni Wulandari
creator: Firman Diatullah Guna Darma
creator: Subektiningsih Subektiningsih
creator: Kartikadyota Kusumaningtyas
creator: Ninik Tri Hartanti
rights: Copyright (c) 2024 Intechno Journal (Information Technology Journal)
date: 2024-07-31
publication date: 2024-07-31
starting page: 27
ending page: 35
doi: 10.24076/intechnojournal.2024v6i1.1696

Analysis System Presensi Menggunakan RFID Card Dengan Modul Mifire RC522 Berbasis Arduino Uno
type: item
description: Penelitian ini membahas tentang penggunaan sistem presensi elektronik RFID Card yang dikombinasikan dengan teknologi Arduino Uno. Metode yang digunakan adalah penelitian kualitatif dengan pendekatan studi kasus dinas lingkungan hidup dan kehutanan Kabupaten Mamasa, provinsi Sulawesi Barat. Penelitian ini menemukan bahwa Secara keseluruhan, hasil studi literatur menunjukkan bahwa RFID card yang dikombinasikan dengan teknologi Arduino Uno adalah teknologi inovatif yang efektif dan efisien untuk digunakan sebagai sistem presensi di berbagai tempat kerja dan institusi pemerintahan.
subject: Articles
  topic: section
subject: Policies
  topic: category
subject: System presensi
  topic: keywords
subject: RFID CARD
  topic: keywords
subject: Arduino
  topic: keywords
creator: Elliantosya Anugrah Putra
creator: Uyock Anggoro Saputro
creator: Wahyu Sindu Prasetya
rights: Copyright (c) 2024 Intechno Journal (Information Technology Journal)
date: 2024-07-31
publication date: 2024-07-31
starting page: 56
ending page: 65
doi: 10.24076/intechnojournal.2024v6i1.1672

Analisis Dan Implementasi Website Dengan Metode Prototyping Sebagai Media Informasi Pada Dusun Dondong
type: item
description: Dalam era yang sangat modern ini masyarakat dituntut untuk mengetahui dan mengerti perkembangan tentang teknologi yang ada. Teknologi memberikan kemudahan untuk membantu setiap kegiatan manusia baik dunia akademik, pembangunan dan lain sebagainya termasuk di bidang pemerintahan. Bidang pemerintahan termasuk pemerintah desa. Pada saat ini Dusun Dondong masih belum ada sistem yang untuk memberikan informasi yang pada akhirnya masyarakat tidak dapat memperoleh informasi, sehingga banyak sekali informasi yang tidak diketahui. Tujuan dari penelitian ini adalah membangun sistem informasi Dusun Dondong. Sistem informasi berbasis web ini dibangun menggunakan metode prototype. Sistem ini nanti nya akan memiliki beberapa fitur dan informasi-informasi yang terkait di Dusun Dondong. Hasil dari penelitian ini adalah sistem informasi yang memberikan informasi kepada masyarakat luas dan mengetahui Dusun Dondong mempunyai ikonik yang ada.
subject: Articles
  topic: section
subject: system informasi
  topic: keywords
subject: website
  topic: keywords
subject: prototyping
  topic: keywords
subject: media informasi
  topic: keywords
creator: Untung Dwi Handoko
creator: Lukman Lukman
creator: Bhanu Sri Nugraha
creator: Eddy Nurraharjo
rights: Copyright (c) 2024 Intechno Journal (Information Technology Journal)
date: 2024-07-31
publication date: 2024-07-31
starting page: 36
ending page: 42
doi: 10.24076/intechnojournal.2024v6i1.1685

Perancangan Media Pembelajaran Bahasa Indonesia untuk Anak Sekolah Dasar
type: item
description: Pendidikan pada tingkat Sekolah Dasar (SD) merupakan dasar penting dalam pembentukan karakter dan kemampuan intelektual siswa. Tetapi, banyak SD yang kurang maksimal dalam penyampaian materinya karena masih menggunakan metode pembelajaran yang konvensional sehingga siswa cepat merasa bosan dalam pembelajaran. oleh karena itu, dibuatlah media pembelajaran Bahasa Indonesia. Penelitian ini bertujuan untuk membuat media pembelajaran yang dapat meningkatkan motivasi belajar siswa khususnya dalam materi bahasa indonesia. Penelitian ini menggunakan metode ADDIE (Analysis, Design, Development, Implementasi, Evaluation). Media pembelajaran bahasa indonesia berbasis website pada penelitian ini dibuat menggunakan adobe animate. Hasil dari perhitungan kelayakan media ini menghasilkan persentase sebesar 84% yang termasuk kategori sangat layak.
subject: Articles
  topic: section
subject: Policies
  topic: category
subject: SD
  topic: keywords
subject: media pembelajaran
  topic: keywords
subject: bahasa indonesia
  topic: keywords
subject: ADDIE
  topic: keywords
subject: adobe animate
  topic: keywords
creator: Ardhika Taruna Eras Sasongko
creator: Wahid Wijaya
creator: Riyan Abdul Aziz
rights: Copyright (c) 2024 Intechno Journal (Information Technology Journal)
date: 2024-07-31
publication date: 2024-07-31
starting page: 19
ending page: 26
doi: 10.24076/intechnojournal.2024v6i1.1691

Analisis Sentiment Kepuasan Masyarakat Terhadap Identitas Kependudukan Digital Dengan Multinomial Naïve Bayes
type: item
description: Baru baru ini pemerintah menerbitkan sebuah kebijakan baru yaitu KTP Digital. Penggunaan KTP digital ini bertujuan untuk meningkatakan efisiensi dan keamanan data penduduk. Maka dari itu peneliti akan menganalisa kepuasan masyarakat yang sudah menggunakan Aplikasi KTP Digital atau IKD dengan menggunakan Metode Naïve Bayes. Penelitian ini juga bertujuan untuk bisa mengetahui kelemahan dari aplikasi IKD menurut pengguna dan diharapkan penelitian ini bisa menjadi sebuah pedoman untuk pemerintah jika ingin melakukan upgrade sistem IKD.
subject: Articles
  topic: section
subject: Analisis Sentiment
  topic: keywords
subject: Apliaksi IKD
  topic: keywords
subject: Multinomial Naïve Bayes
  topic: keywords
subject: kepuasan
  topic: keywords
creator: Miko Kastomo Putro
creator: Ali Mustopa
creator: Joko Dwi Santoso
creator: Eka Wahyu Sholeha
rights: Copyright (c) 2024 Intechno Journal (Information Technology Journal)
date: 2024-07-31
publication date: 2024-07-31
starting page: 10
ending page: 18
doi: 10.24076/intechnojournal.2024v6i1.1687

Rancang Bangun E-Learning Penggolongan Jenis Napza Menggunakan Metode Waterfall
type: item
description: In the context of Sleman Regency, Indonesia, the rate of drug abuse is increasing due to insufficient dissemination of information about the types of drugs and the negative impacts resulting from drug abuse. One of the contributing factors is the lack of socialization among the community, leading to their limited knowledge about the types of drugs and the dangers of improper use or using medication without a doctor's prescription. The approach applied to combat this problem is a systematic method that involves planning the system, analysis, design, implementation, testing, and maintenance. These steps must be carried out in a sequential manner. The system itself will be developed using programming languages such as PHP, JavaScript, and MySQL server for data processing
subject: Articles
  topic: section
subject: Policies
  topic: category
subject: Perancangan
  topic: keywords
subject: E-Learning
  topic: keywords
subject: NAPZA
  topic: keywords
subject: Waterfall
  topic: keywords
creator: Devi Wulandari
creator: Pasipikus Yosua Agun
creator: Ferian Fauzi Abdulloh
creator: Abdul Muin
rights: Copyright (c) 2024 Intechno Journal (Information Technology Journal)
date: 2024-07-31
publication date: 2024-07-31
starting page: 43
ending page: 55
doi: 10.24076/intechnojournal.2024v6i1.1661

Strategi Optimisasi Kata Kunci dalam Meningkatkan Visibilitas di Mesin Pencari
type: item
description: Teknologi memungkinkan akses informasi yang cepat dan efisien menjadi kunci penting dalam memenuhi kebutuhan informasi di era digital. Mesin pencari digital seperti Google, memainkan peran krusial dalam memberikan akses cepat dan akurat terhadap informasi yang diinginkan. Pengguna hanya perlu memasukkan kata kunci tertentu, dan dalam sekejap, berbagai sumber informasi relevan akan ditampilkan memberikan gambaran cepat tentang topik yang dicari tanpa harus membuka setiap laman. Mesin pencari menggunakan algoritma canggih untuk menilai relevansi dan kredibilitas laman web berdasarkan kata kunci yang dimasukkan oleh pengguna yang juga mempengaruhi posisi laman dalam hasil pencarian. Optimisasi kata kunci menjadi strategi penting bagi pemilik laman web untuk meningkatkan visibilitas mereka. Penelitian ini bertujuan untuk mengeksplorasi dampak kata kunci terhadap hasil pencarian di mesin pencari dari berbagai perspektif peneliti, dengan fokus pada bagaimana penggunaan kata kunci memengaruhi relevansi, akurasi, dan kepercayaan terhadap informasi yang diperoleh. Melalui tinjauan ini, diharapkan diperoleh pemahaman mengenai strategi optimasi kata kunci dan dampaknya dalam konteks pencarian informasi digital.
subject: Articles
  topic: section
subject: Policies
  topic: category
subject: Kata kunci
  topic: keywords
subject: Optimasi Kata kunci
  topic: keywords
subject: Strategi SEO
  topic: keywords
subject: Mesin Pencari
  topic: keywords
subject: Laman web
  topic: keywords
creator: Toto Indriyatmoko
creator: Arvin claudy Forbenius
creator: Mohammad Santosa Mulyo Diningrat
rights: Copyright (c) 2024 Intechno Journal (Information Technology Journal)
date: 2024-07-31
publication date: 2024-07-31
starting page: 66
ending page: 72
doi: 10.24076/intechnojournal.2024v6i1.1693

Implementasi Algoritma SVM Dalam Pengembangan Sistem Presensi Berbasis Face Recognition
type: item
description: Sistem presensi Universitas Amikom Yogyakarta memiliki potensi untuk dikembangkan. Dari sistem yang sudah ada kami menemukan sebuah ide untuk meng-implementasikan face recognition dalam sistem tersebut. Sistem presensi dengan menggunakan face recognition akan lebih mempermudah mahasiswa/i untuk melakukan presensi. Mengingat permasalahan yang ada seperti menggunakan QR Code yang masih susah dideteksi pada barisan-barisan tertentu. Maka, dalam penelitian ini menggunakan metode Support Vector Machine (SVM) sebagai metode untuk klasifikasi gambar yang sudah diconvert menjadi Numpy Array dengan meng-uji coba beberapa sampel foto mahasiswa/i Universitas Amikom Yogyakarta lalu mengidentifikasi satu persatu data baru untuk mendapatkan sebuah hasil yang berupa pengenalan sebuah wajah dengan tampilan berupa identitas pengenal dari mahasiswa/i tersebut. Diakhir penelitian ini kami menemukan bahwa keakurasian face recognition dengan menggunakan metode SVM menghasilkan rata-rata 93,46% yang berarti bahwa sebuah image yang dapat diproses untuk melakukan sebuah presensi.
subject: Articles
  topic: section
subject: Policies
  topic: category
subject: Face Recognition
  topic: keywords
subject: Presensi
  topic: keywords
subject: Numpy Array
  topic: keywords
subject: Support Vector Machine (SVM)
  topic: keywords
creator: Zanuarestu Ramadhani
creator: Livia Safira
creator: Anggit Dwi Hartanto
creator: Hartatik Hartatik
rights: Copyright (c) 2022 Intechno Journal (Information Technology Journal)
date: 2022-12-31
publication date: 2022-12-31
starting page: 42
ending page: 47
doi: 10.24076/intechnojournal.2022v4i2.1561

Implementasi Voice To Text Pada Invoice Checking Berbasis Web
type: item
description: INDOMASCOT adalah perusahaan yang bergerak di bidang konveksi kostum badut maskot. Tim sales-nya seringkali mengalami kerepotan untuk mengirim invoice kepada customer khususnya ketika berada di workshop. Maka dari itu, perlu adanya satu solusi dalam bentuk aplikasi invoice checking yang dapat mengurangi beban pekerjaan tim sales dalam pengiriman invoice kepada customer. Selain itu, sebagai fitur tambahannya baik sekali untuk disematkan pengimplementasian AI dalam bentuk voice-to-text agar customerdapat menginput email & no. invoice-nya dari sumber suara. Dari beberapa kali percobaan, Web Speech APIini kurang memuaskan untuk mengenali alamat email. Namun, memiliki hasil memuaskan untuk mengenali no. invoice yang berbentuk angka. Fitur voice-to-text ini memanfaatkan Web Speech API yang saat tulisan ini dibuat masih dalam status experimental.
subject: Articles
  topic: section
subject: voice-to-text
  topic: keywords
subject: speech recognition
  topic: keywords
subject: web speech API
  topic: keywords
subject: web app
  topic: keywords
creator: Gangsar Swapurba
creator: Irfan Pratama
rights: Copyright (c) 2023 Intechno Journal (Information Technology Journal)
date: 2023-12-31
publication date: 2023-12-31
starting page: 65
ending page: 74
doi: 10.24076/intechnojournal.2023v5i2.1391

Aplikasi Monitoring Laporan Data Hasil Pengolahan TBS Kelapa Sawit Berbasis Mobile Pada PT. Perkebunan Nusantara VII
type: item
description: The process of recording data processing reports from units to the PTPN VII head office has used a website-based application. This allows each unit to upload a report of processing data. In an effort to optimize applications, especially in presenting information that can be accessed in real-time for stakeholders to report palm oil processing results, it is necessary to develop a mobile-based application. At PTPN VII. This data collection activity was carried out at PTPN VII, Bandar Lampung head office from March to June 2023. The process of monitoring reports on processing data for Oil Palm Fresh Fruit Plants (FFB) can measure the quality and quantity of processing, as well as make strategic decisions in making decisions quickly and efficiently. accurate. The development of this application uses the Flutter framework, the PHP programming language and the MySql database. The results of the data obtained are the Mobile-Based Palm Oil FFB Processing Data Report Monitoring Application at PTPN VII.
subject: Articles
  topic: section
subject: Policies
  topic: category
subject: Aplikasi
  topic: keywords
subject: Monitoring
  topic: keywords
subject: Android
  topic: keywords
subject: Mobile
  topic: keywords
subject: Laporan
  topic: keywords
creator: Haldian Haldian
creator: Oki Arifin
creator: Eko Win Kenali
rights: Copyright (c) 2023 Intechno Journal (Information Technology Journal)
date: 2023-12-31
publication date: 2023-12-31
starting page: 43
ending page: 55
doi: 10.24076/intechnojournal.2023v5i2.1388

Sistem Informasi Peramalan Stok Barang Toko Al Umm Menggunakan Metode Single Moving Average
type: item
description: Toko Al Umm merupakan toko grosir dan eceran busana muslim yang menyediakan berbagai macam alat ibadah seperti sarung, mukena, peci serta selimut. Dengan adanya berbagai macam barang yang ada pada toko Al Umm, maka pemilik toko pun kesulitan mengetahui stok barang yang tersedia pada tokonya dengan pasti. Untuk mendata stok barang tersebut pemilik toko masih mencatatnya secara manual sehingga pemilik tidak mengetahui dengan pasti berapa jumlah stok barang yang masih tersedia pada toko. Oleh karena itu panulis berinisiatif membangun sebuah aplikasi untuk melakukan peramalan stok barang yang ada pada Toko Al-Umm menggunakan bahasa pemrograman PHP dengan framework CodeIgniter 3. Penulis juga menggunakan metode peramalan single moving average yang mana metode peramalan ini digunakan untuk mengetahui besaran atau banyaknya stok barang yang perlu di suplai pada toko Al-Umm.
subject: Articles
  topic: section
subject: Policies
  topic: category
subject: peramalan
  topic: keywords
subject: single moving average
  topic: keywords
subject: stok barang
  topic: keywords
creator: Moch Khoirul Muna
rights: Copyright (c) 2023 Intechno Journal (Information Technology Journal)
date: 2023-12-31
publication date: 2023-12-31
starting page: 87
ending page: 97
doi: 10.24076/intechnojournal.2023v5i2.825

Implemantasi Autentikasi Hotspot Menggunakan Radius Server Mikrotik Router Pada Rumah Sakit Misi Lebak
type: item
description: The Lebak misi hospital area currently mostly using wireless networks where usage is increasing and bandwidth is uneven. Between one user and another and the admin only provides password protection for existing access points. which will cause instability between one user and another, therefore the author uses the Radius server as a bandwidth divider as well as security with user authentication and adding a QR code to the authentication. and the author uses the NDLC (Network Development Life Circle) method. As a reference for the radius server configuration using a proxy router. and the results obtained are the percentage of user bandwidth before using the server radius of 0.99Mbps on download and upload of 1.19Mbps for smartphones on laptops of 6.72Mbps for download and upload of 2.21Mbps then after using the radius of the server the average bandwidth speed using user and password of 0.75Mbps for download and 0.80Mbps upload and the success status is very good, all devices can authenticate. and those who can use a QR code of 0.36Mbps for download and 0.44Mbps for Upload with a poor success status because some devices are not compatible for authentication using a QR code by scanning webqr.com.
subject: Articles
  topic: section
subject: Policies
  topic: category
subject: Server Radius
  topic: keywords
subject: MikroTik
  topic: keywords
subject: Authentication
  topic: keywords
subject: Networking
  topic: keywords
subject: NDLC Metode
  topic: keywords
creator: Alexander Gonzaga
creator: Andriyan Dwi Putra
rights: Copyright (c) 2023 Intechno Journal (Information Technology Journal)
date: 2023-12-31
publication date: 2023-12-31
starting page: 56
ending page: 64
doi: 10.24076/intechnojournal.2023v5i2.644

Penerapan Metode Simple Additive Weighting Untuk Menentukan Siswa Penerima Bantuan Dana SMK PL Leonardo Klaten
type: item
description: SMK PL Leonardo Klaten has a program that is held every month to provide relief fund to students. Decision making in the selection process is currently still done manually, thus requiring more time and allowing for inaccurate selection results due to a lack of thoroughness which can lead to wrong targeting. To solve this problem, a decision support system was designed using the Simple Additive Weighting (SAW) method so that the selection process would be more accurate, efficient and easier for the SMK PL Leonardo Klaten to determine which students are entitled to receive relief fund. The implementation of this decision support system has succeeded in displaying a ranking that can be used as consideration for determining students who receive relief fund at SMK PL Leonardo Klaten. The level of match between the results of manual calculations and the results of system calculations is the same and produces an accuracy of 100% which indicates that the calculation of the SAW method on the system is correct.
subject: Articles
  topic: section
subject: Decision Support System
  topic: keywords
subject: Relief Fund
  topic: keywords
subject: Simple Additive Weighting
  topic: keywords
subject: SAW
  topic: keywords
creator: Robertus Aldrin Pangemanan
creator: Erni Seniwati
rights: Copyright (c) 2023 Intechno Journal (Information Technology Journal)
date: 2023-12-31
publication date: 2023-12-31
starting page: 75
ending page: 86
doi: 10.24076/intechnojournal.2023v5i2.572