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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) MEDIA ELEKTRIKA Semantik Jurnal Transformatika Al-Ta'rib : Jurnal Ilmiah Program Studi Pendidikan Bahasa Arab UIN Palangka Raya TRANSISTOR Elektro dan Informatika Empowerment : Jurnal Pengabdian Masyarakat Jurnal Ekonomi & Keuangan Islam Jurnal Ilmu Manajemen Advantage Prosiding Seminar Riset Mahasiswa Jurnal Ilmiah Sultan Agung Jurnal Rekayasa Sistem Informasi dan Teknologi Journal of Computer Science and Information Technology Technema: Journal of Intelligent Engineering and Computing
Moch Taufik
Universitas Islam Sultan Agung
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Nursing Public Health Social Sciences Other

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Development of a Question Answering System Using the Best Matching 25 (BM25) Method to Support Final Project Completion for Informatics Engineering Students at UNISSULA Iqbal Nur Al Sandi; Ndaru Senopati Nusa; Muhammad Farrel Ardan; Bagus Satrio Waluyo Poetro; Moch Taufik
Technema: Journal of Intelligent Engineering and Computing Vol. 1 No. 3 (2026): Technema: Journal of Intelligent Engineering and Computing
Publisher : CV SCRIPTA INTELEKTUAL MANDIRI

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Abstract

This study developed and evaluated a BM25-based question-answering system to support final-project information retrieval for Informatics Engineering students at Universitas Islam Sultan Agung. The system used the official Final Project Guidebook and Supervision Logbook as its knowledge corpus and integrated document reconstruction, heading-aware chunking, paragraph overlap, lexical preprocessing, synonym-based query expansion, heading-weighted indexing, BM25 ranking, and source-grounded answer presentation. Evaluation was conducted using 50 manually mapped ground-truth queries and measured through Recall@1, Recall@3, Recall@5, and Mean Reciprocal Rank. The results showed that 41 queries retrieved the relevant passage at rank 1, eight at rank 2, and one at rank 3. Recall@1 reached 82.00%, while Recall@3 and Recall@5 both achieved 100.00%, with an MRR of 0.9067. These findings indicate that the proposed lexical retrieval architecture can reliably recover authoritative academic information while maintaining transparency, interpretability, and source traceability. The remaining limitation concerns first-rank discrimination among procedurally similar passages, suggesting that future improvements should prioritize reranking or hybrid retrieval without sacrificing complete Top-3 coverage. The approach also provides a reproducible baseline for evaluating more complex semantic retrieval methods in academic information environments.  
Co-Authors Adib Ulil Anwar Afriadi, Fiqih Afy Wahyu Wibowo Afy Amalia, Nabila Nailil Amin Purnawan Asbarin, Asbarin Dedy Kurniadi Fitri Sagantha Gigih Pangudi Arta Hermawan, Hildan Mulyo Huda, Rizky Miftachul Ike Mawarni Imam Much Ibnu Subroto Iqbal Nur Al Sandi Johan Hamuda Mohammad Taufiqurrohman Muhammad Farrel Ardan Muhammad Khosyi’in Muhammad Qomaruddin Muhammad Sholahuddin Mustafa, Mustafa Ndaru Senopati Nusa Nova Catur Anggi Cahyo Poetro, Bagus Satrio Waluyo Rachmad Gabels Riansyah, Andi Rifdah Abadiyah Saifurrohman, Ahmad Sam Farisa Chaerul Haviana Siti Ummu Adillah Sri . Handayani Sri Mulyono Sumartik Suparno Dedy Prastyo Umi Machmudah Uswatun Chasanah Yusaena Yusuf