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All Journal KALBISIANA Jurnal Sains, Bisnis dan Teknologi INOVTEK Polbeng - Seri Informatika
Muhammad Adrinta Abdurrazzaq
Universitas Kalbis
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering Social Sciences

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An Indonesian Chatbot for Disease Diagnosis Using Retrieval-Augmented Generation Muhammad Adrinta Abdurrazzaq; Edwin Lesmana Tjiong; Aulia Fasya; Michelle Hiu; Joses Tanuwidjaya
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/9nnkn955

Abstract

The rapid advancement of Large Language Models (LLMs) has enabled their use in medical information systems, although challenges such as hallucinations, domain mismatches, and the lack of a verified knowledge base remain significant, particularly in low-source languages ​​like Indonesian. This study introduces an Indonesian-language medical chatbot based on the open-source GPT-OSS-20B model enhanced through a Retrieval-Augmented Generation (RAG) pipeline. The system combines semantic retrieval using jina-embeddings-v3, lexical re-ranking with the BM25 algorithm, and a lightweight Logistic Regression-based domain filter as an initial filter to prevent out-of-domain LLM usage. Evaluation using Indonesian medical articles and annotated patient-doctor conversations shows that the domain filter works well on synthetic data but results in misclassification of natural queries. A hybrid weighted reranker (FAISS L2 + BM25) performed the best with a Top-30 accuracy of 0.699. Black-box testing indicates that the system flow functions as designed, although the response quality has not been validated by clinical experts. These findings suggest that RAG-based open-source LLMs can improve access to Indonesian-language medical information, but still have important limitations such as the lack of clinical validation, potential errors in scraped data, and suboptimal robustness of domain filters.
Pengembangan Aplikasi Pencatatan Keuangan dan Pengecekan Stok Toko Kue LHJ Kue Berbasis Android Ferdi Riansyah; Muhammad Adrinta Abdurrazzaq
KALBISIANA Jurnal Sains, Bisnis dan Teknologi Vol. 12 No. 1 (2026): Kalbisiana
Publisher : UNIVERSITAS KALBIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53008/nvsvkr56

Abstract

This study aims to analyze the application of android-based financial applications to the results of the financial statements of LHJ Cake Shop. So far, LHJ Cake Shop often has difficulty in recording finances, the problems that often occur are the length of recording and frequent errors in recording. This research uses the Rational Unified Process (RUP) method as the software development cycle and Android Studio in making the application. To test the application, this research uses blackbox testing and feedback from users. Based on the test results, it is found that financial recording using the Android Financial Application on the smartphone of the owner of the LHJ Cake Shop is proven to facilitate business transactions in the form of purchases-sales, accounts payable, payment of operational expenses and others. Financial reports on Android-based smartphones are easy to use at any time. Real time information in this system helps operations move more effectively and efficiently.
Co-Authors Aulia Fasya Edwin Lesmana Tjiong Ferdi Riansyah Joses Tanuwidjaya Michelle Hiu