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Journal : Bulletin of Computer Science Research

Implementasi Langchain dan Large Language Models Dalam Automatic Question Generation Untuk Computer Assisted Test Novri Rahman; Harahap, Nazruddin Safaat; Affandes, Muhammad; Pizaini
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.558

Abstract

The advancement of Artificial Intelligence (AI), particularly Large Language Models (LLM), presents new opportunities in transforming educational assessment systems. This study aims to implement the LangChain framework integrated with LLM for an Automatic Question Generation (AQG) system within a Computer Assisted Test (CAT) platform, using eleventh-grade Biology subject matter as a case study. The methodology includes data collection from PDF-based instructional materials, text embedding using Facebook AI Similarity Search (FAISS) as the knowledge base, and automatic question generation through the GPT-4o model. The system is developed using a microservices architecture comprising frontend and backend services built with the Next.js, FastAPI, and Express.js frameworks. System evaluation was conducted using the User Acceptance Test (UAT) and the DeepEval framework. The evaluation results show a teacher satisfaction rate of 92.7% and a positive response from students at 67.5%. Meanwhile, the DeepEval assessment reported average scores of 3,69% for hallucination, 97,44% for contextual precision, 83,30% for contextual relevancy, 70,63% for answer relevancy, and 92,47% for prompt alignment. These findings indicate that the integration of LangChain and LLM is effective in generating contextually accurate and relevant questions, although improvements are still needed in answer relevancy. This study is expected to provide an efficient solution for digital-based educational assessment and contribute to future developments in educational AI.
Pengelompokan Wilayah Bencana Banjir di Indonesia Menggunakan Algoritma K-Means Wenny Tarisa Oktaviany; Fitri Insani; Alwis Nazir; Pizaini
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.608

Abstract

Floods are one of the natural disasters that often occur in Indonesia, especially during the rainy season. This disaster is caused by various factors, both natural and caused by human activities, such as high rainfall, poor drainage systems, land conversion, and suboptimal spatial planning. The impact of floods is very detrimental, both physically and psychologically, including loss of life and damage to property. Therefore, a method is needed to group areas based on their level of vulnerability to flooding. This study aims to group flood disaster areas in Indonesia using the K-Means algorithm. The data used comes from the BNPB Geoportal covering flood events from January 2020 to December 2024, with a total of 7,487 events from 498 areas. Based on the test results obtained using the Silhouette Coefficient, it shows that 2 clusters were selected as the best number of clusters with a Silhouette Coefficient value of 0.8461 which is included in the strong clustering structure. Of the 2 clusters obtained, cluster 1 is a high-risk category consisting of 35 areas, while cluster 2 is a low-risk category consisting of 463 areas. The results of this study can provide information for related parties to improve the efficiency of flood disaster management.
Co-Authors Abdillah, Rahmad Adha, Martin Aditya Dyan Ramadhan Afdhalel Vickro Agung Teguh Wibowo Almais Ahmad Fauzan Akhyar, Amany Albis Ya Albi Alwis Nazir Alwis Nazir Andrian Wahyu Arvansyah, M Afdhol Aslis Wirda Hayati Ayu Fransiska Bebi Oktaviani Che Hussin, Ab Razak citra ainul mardhia putri Deny Dewana Hastanto Dhymas Julyan Riyanto Eka Pandu Cynthia Elin Haerani Elvia Budianita Fadhilah Syafria Fahmi Kasri Fajar Febriyadi Fakhrezi, Muhammad Dzaki Faris Apriliano Eka Fardianto Faris Fauzan Ray T Febi Yanto Fitra Kurnia Fitri Insani Fitri Insani Fitri Insani Fitri, Dina Deswara Gusti, Siska Kurnia Haikal Zikri Hasibuan, Ilham Habibi Heru Sukoco Husnan Husnan Ibrahim Armadian Pujakesuma Iwan Iskandar Iwan Iskandar Iwan Iskandar Iwan Iskandar Iwan Jasril Jasril Jesi Alexander Alim Jesi Alexander Alim Kana Saputra S Khonofi, Khoidir Lestari Handayani Lola Oktavia m azwan M Wandi Dwi Wirawan M. Saski Mandiro, Mulia Anton Muhammad Affandes Muhammad Affandes Muhammad Fauzan Muhammad Fikry Muhammad Irsyad Muhammad Irsyad Muhammad Ridha Mulia Anton Mandiro Musa Thahir Muslimin, Al’hadiid Najmi, Risna Lailatun Nanda Sepriadi Nazir, Alwis Nazruddin Safaat H Neni Hermita Novi Yanti Novialdi T Novri Rahman Novriyanto Novriyanto Nur Iza Nuradha Liza Utami Okfalisa Okfalisa Okfalisa Okfalisa Putri, Adilah Atikah Rahmad Abdillah Rahmad Kurniawan Reski Mai Candra Reski Mai Chandra Rometdo Muzawi, Rometdo Roziana Roziana, Roziana Saktioto Saktioto Suci Rahayu Sugi Guritman Sukma Evadini Surya Agustian Suwanto Sanjaya Syarifuddin Syarifuddin Teddie Darmizal Thahir, Musa Tommy Tanu Wijaya Umar Syarif Vebrianto, Rian Wenny Tarisa Oktaviany Wirdiani, Putri Syakira Yelfi Vitriani Yusra Yusra, Yusra Zuriati Ardila Safitri