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All Journal Jurnal Teknologi Informasi dan Pendidikan Formosa Journal of Sustainable Research (FJSR)
Apridal, Fauzi Isyrin
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Industrial & Manufacturing Engineering Social Sciences

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Naimaecosync as a Waste Management Aggregator in Supporting Extended Producer Responsibility for Industries in Indonesia Dewi, Mutia Rahmi; Islamy, Imam Teguh; Apridal, Fauzi Isyrin; Sy, Yulia Jihan; Atma, Yori Adi; Vadreas, Andrew Kurniawan
Formosa Journal of Sustainable Research Vol. 4 No. 1 (2025): January 2025
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/fjsr.v4i1.13799

Abstract

Extended Producer Responsibility (EPR) is a program that holds industries accountable for their products' environmental impact throughout their lifecycle. To guide EPR implementation, Indonesia's Ministry of Environment and Forestry issued Regulation P.75/2019 on waste reduction by producers. One key government initiative is optimizing partnerships for post-consumer packaging waste collection through Waste Banks, TPST3R, Recycling Centers, and digital platforms. This research introduces NaimaEcoSync, a platform designed to streamline waste take-back by integrating waste management data and mapping reports for industries. Developed using the Scrum methodology, NaimaEcoSync achieved a usability score of 96.07%. The platform contributes to industry sustainability by reducing waste and supporting EPR implementation in Indonesia
Development of an Interactive Chatbot Using Sahabat-AI Model with Retrieval-Augmented Generation Method Apridal, Fauzi Isyrin; Humaira; Nova, Fitri
Jurnal Teknologi Informasi dan Pendidikan Vol. 19 No. 1 (2026): Jurnal Teknologi Informasi dan Pendidikan
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jtip.v19i1.1105

Abstract

The rapid advancement of language-based artificial intelligence, particularly Large Language Models, has enabled the development of adaptive and context-aware virtual assistants. This research aims to develop an interactive chatbot for Politeknik Negeri Padang utilizing the Sahabat-AI model (Gemma2 9B CPT), a large-scale model specialized in Bahasa Indonesia and local dialects (Javanese, Sundanese), combined with the Retrieval-Augmented Generation (RAG) method to enhance document-based answer accuracy. The system architecture integrates a Streamlit-based user interface supporting text/voice input and multilingual output, an automated web-scraping module using Scrapy to update institutional data, a structured knowledge base in Supabase, and a semantic vector search with FAISS. The development process followed a systematic design and implementation approach, with the RAG pipeline incorporating all-indo-e5-small-v4 embeddings to ensure semantic relevance. Performance evaluation using LangSmith demonstrated that Sahabat-AI outperformed Llama 3, achieving an average score of 0.84 (correctness: 0.89, relevance: 0.90, groundedness: 0.80, retrieval quality: 0.77) in Indonesian language testing. The chatbot exhibited strong local language understanding, scoring 0.74 for Javanese and 0.71 for Sundanese, while reducing hallucinations through RAG integration. Black-box testing confirmed the reliability of multimodal features such as speech-to-text and text-to-speech. The findings contribute to the development of the first Sahabat-AI–based multilingual chatbot for Politeknik Negeri Padang, integrating automated document retrieval and embedding pipelines for efficient information services.
Co-Authors Andrew Kurniawan Vadreas Fitri Nova, Fitri humaira Islamy, Imam Teguh Mutia Rahmi Dewi SY, Yulia Jihan Yori Adi Atma