TECHNOFAC: APLIKASI ANDROID PENCARIAN FASILITAS KAMPUS BERBASIS SPEECH-TO-TEXT DAN NATURAL LANGUAGE PROCESSING (STUDI KASUS: UNIVERSITAS INDO GLOBAL MANDIRI)

Siti Ayu Hermaliah; Shinta Puspasari; Indah Permatasari

doi:10.24252/instek.v10i2.60822

Authors

Siti Ayu Hermaliah Universitas Indo Global Mandiri
Shinta Puspasari Universitas Indo Global Mandiri
Indah Permatasari Universitas Indo Global Mandiri

DOI:

https://doi.org/10.24252/instek.v10i2.60822

Keywords:

hybrid keyword-based, NER, NLP, speech-to-text, SUS, technofac

Abstract

Aplikasi Technofac dikembangkan untuk memudahkan pencarian fasilitas kampus Universitas Indo Global Mandiri (IGM) dengan integrasi Speech-to-Text dan Natural Language Processing (NLP) melalui metode Hybrid Keyword-Based. Pipeline sistem meliputi Automatic Speech Recognition, preprocessing (normalization, Punctuation Removal, Tokenization, Synonym Mapping, dan Abbreviation Expansion), intent detection berbasis keyword matching, dan Named Entity Recognition (pattern matching, POS tagging, dictionary, serta fuzzy matching). Evaluasi kinerja NLP menunjukkan metode Hybrid Keyword-Based mencapai precision 0.9346, recall 0.9263, dan F1-Score 0.9297 (kategori very good), sedangkan metode Substring Matching mencapai precision 0.7879, recall 0.7512, dan F1-Score 0.7655 (kategori OK). Pengujian blackbox terhadap 13 fitur menunjukkan seluruh fungsi berjalan sesuai spesifikasi. Evaluasi usability menggunakan System Usability Scale pada 20 responden (n=20) menghasilkan skor 82.87 dengan Grade A (Acceptable) dan confidence interval 95% pada rentang 80.8–85.2. Meskipun sistem menunjukkan performa baik, terdapat 16 kasus False Negative akibat query ambigu dan 14 kasus False Positive akibat misclassification entitas. Penelitian ini menunjukkan potensi rule-based NLP untuk aplikasi pencarian fasilitas kampus, namun masih memerlukan dialog management system (follow-up question) dan hierarchical entity recognition untuk menurunkan kesalahan FP/FN.

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