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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Teknik Informatika UNIKA Santo Thomas Jurnal Mantik Brilliance: Research of Artificial Intelligence Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Digital Transformation Technology (Digitech) INCOME: Indonesian Journal of Community Service and Engagement Scientific Journal of Informatics
Anisyah, Ani
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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A Pengembangan Chatbot Informasi Kesehatan Ibu dan Anak Jawa Barat Berbasis Hybrid RAG dan TextToSQL Basallamah, Muhammad Alam; Riza, Lala Septem; Anisyah, Ani
Jurnal Komputer Teknologi Informasi Sistem Informasi (JUKTISI) Vol. 4 No. 3 (2026): Februari 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v4i3.783

Abstract

The high Maternal Mortality Rate and stunting prevalence in West Java hinder the achievement of SDGs. Information accessibility remains a key constraint as data is scattered in narrative formats within Health Profiles and MCH Books. This study develops a hybrid chatbot based on Retrieval-Augmented Generation (RAG) and Text-to-SQL using the Google Gemini Large Language Model. The system integrates hierarchical chunking, intelligent routing, conversational memory, and automatic data visualization to present factual and statistical information precisely. System evaluation demonstrates high performance: Text-to-SQL reached 93.33% execution accuracy and 85% Router accuracy. In the RAG module, testing on 60 questions yielded scores of 0.990 Faithfulness, 0.883 Context Recall, and 0.950 Answer Relevancy. The system achieved a perfect score of 1.000 for out-of-context handling, proving safety from hallucinations. User Acceptance Testing (UAT) recorded a 80% success rate, where the chart feature was rated significant in aiding data understanding. The study concludes that the hybrid approach effectively enhances health insight accessibility for the public and stakeholders, although complex table extraction requires further optimization.
Co-Authors Achmaddifa, Deffin Ade Mulyana, Ade Ahmaddifa, Deffin Al Fathin, Deva Shofa Al Husaeni, Dwi Novia Amadudin, Muhammad Nur Yasin Asep Wahyudin Atqiya, Muhammad Azka Basallamah, Muhammad Alam Bisulthon, Ibrahim Danial Eddy Prasetyo Nugroho Erlangga Firdaus, Ayesha Ali Herbert Husain, Mohammad Labib Irawan Afrianto Isya, Nadhief Athallah Julianti, Sukma Junaeti, Enjun Jundurrahmaan, Irham Kanaya, Salsabila Kusnendar, Jajang Kusumawardani, Sekar Madu Lala Septem Riza M. Yusuf Bahtiar, M. Yusuf Mi'raj, Rafi Arsalan Munir Munir, Munir Octaverin, Ghifari Piantari, Erna Ramadhani, Muhammad Satria Rasim, Rasim Rizky Rachman Judhie Putra Rosa Ariani Sukamto Siregar, Herbert Wibisono, Yudi Yosafat