PEMANFAATAN LLM UNTUK ELISITASI FITUR APLIKASI PEMESANAN KOPI
DOI:
https://doi.org/10.24076/joism.2026v8i1.2845Keywords:
elisitasi kebutuhan, pemesanan kopi, Large Language Model, flow tree, rekayasa perangkat lunakAbstract
Pengembangan aplikasi pemesanan kopi menuntut elisitasi kebutuhan fungsional yang akurat. Namun, metode elisitasi konvensional kerap memakan waktu, rentan terhadap bias subjektif, dan belum mengkaji pola fitur dari aplikasi komersial berskala besar yang telah sukses di pasar. Ketiadaan acuan dasar (baseline) ini berisiko menghasilkan sistem yang gagal memenuhi ekspektasi pengguna modern. Untuk mengatasi kesenjangan tersebut, penelitian ini bertujuan untuk mengekstraksi, memvalidasi, dan menganalisis standar fitur aplikasi pemesanan kopi berbasis mobile. Kebaruan penelitian ini terletak pada pemanfaatan Large Language Model (LLM) untuk otomatisasi dekomposisi fitur yang divalidasi secara silang dengan Voice of Customer (VoC) berbasis ulasan pengguna. Data deskriptif ditarik dari empat aplikasi populer: Fore Coffee, Cotti Coffee, Starbucks Indonesia, dan TOMORO COFFEE. Hasil pengujian menunjukkan ekstraksi berbasis LLM sangat andal, dengan Precision dan Recall mencapai 88%. Triangulasi dengan VoC mengonfirmasi bahwa arsitektur fungsional inti dari aplikasi tersebut berlandaskan pada Technology Acceptance Model (TAM), kustomisasi massal, dan gamifikasi. Lebih lanjut, studi ini memetakan feature gap strategis, meliputi personalisasi AI, model langganan otomatis (subscription), dan fitur komunitas. Secara praktis, luaran penelitian ini dapat langsung diadaptasi oleh pengembang perangkat lunak sebagai baseline penyusunan Software Requirements Specification (SRS) dan Minimum Viable Product (MVP) yang lebih adaptif dan user-centric.
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