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All Journal Tekno - Pedagogi : Jurnal Teknologi Pendidikan Teknika TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Jurnal CoreIT Journal of Natural Science and Integration Seminar Nasional Teknologi Informasi Komunikasi dan Industri J I M P - Jurnal Informatika Merdeka Pasuruan Applied Information System and Management Jurnal Nasional Komputasi dan Teknologi Informasi JURIKOM (Jurnal Riset Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal IDAMAN (Induk Pemberdayaan Masyarakat Pedesaan) Building of Informatics, Technology and Science Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Zonasi: Jurnal Sistem Informasi INFORMASI (Jurnal Informatika dan Sistem Informasi) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Teknik Informatika (JUTIF) Jurnal Computer Science and Information Technology (CoSciTech) Jurnal Pendidikan dan Teknologi Indonesia Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Knowbase : International Journal of Knowledge in Database Malcom: Indonesian Journal of Machine Learning and Computer Science SATIN - Sains dan Teknologi Informasi Jurnal Pengembangan Teknologi Informasi dan Komunikasi (JUPTIK)
Pizaini Pizaini
Universitas Islam Negeri Sultan Syarif Kasim Riau
Aerospace Engineering Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Expert Validation: Development of an Ethnoscience-Based E-Module to Improve Students' Critical Thinking Skills and Environmental Awareness Yovita, Yovita; Pizaini, Pizaini; Berlian, Mery; Tahir, Musa; Vebrianto, Rian
Tekno - Pedagogi : Jurnal Teknologi Pendidikan Vol. 16 No. 2 (2026): Tekno-Pedagogi
Publisher : Program Magister Teknologi Pendidikan Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to develop an ethnoscience-based e-module on the subject of Living Things and Their Environment to improve critical thinking skills and environmental awareness of junior high school students. The background of this study is based on the weaknesses of conventional learning which is still teacher-centered, abstract, and does not integrate local cultural values thus hampering active student involvement and their understanding of environmental issues. The study used the Research and Development (R&D) method with the ADDIE (Analysis, Design, Development, Implementation, Evaluation) development model. The subjects were junior high school students in Pekanbaru City. The instruments used included a validity questionnaire from media & technology experts, material & pedagogical experts, linguists, and ethnoscience experts; as well as a questionnaire on teacher practicality and student practicality. The results of validation by media, language, material, and ethnoscience experts showed that the e-module had a very good validity level with an average of 88.25%, as well as a very good practicality value with an average of 85%. Thus, this ethnoscience- based e-module is declared feasible, practical, and effective as a contextual learning medium that integrates scientific concepts with local wisdom and supports 21st-century learning
Implementasi Langchain dan Large Language Models Dalam Automatic Question Generation Untuk Computer Assisted Test Novri Rahman; Nazruddin Safaat Harahap; Muhammad Affandes; Pizaini 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 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.
Implementasi Fine Tuning Menggunakan Metode QLoRA Pada Sistem Tanya Jawab Hadits Muhammad Azmi; Fitra Kurnia; Nazruddin Safaat Harahap; Muhammad Irsyad; Pizaini; Arif Marsal
Jurnal Pengembangan Teknologi Informasi dan Komunikasi (JUPTIK) Vol. 4 No. 1 (2026): JURNAL PENGEMBANGAN TEKNOLOGI INFORMASI DAN KOMUNIAKSI (JUPTIK)
Publisher : Universitas Muhammadiyah Muara Bungo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52060/juptik.v4i1.4349

Abstract

Hadits Islam merupakan sumber hukum kedua dalam ajaran Islam, namun penerapan Large Language Model (LLM) pada domain ini menghadapi masalah halusinasi faktual dan kesalahan atribusi sitasi. Penelitian ini mengembangkan sistem tanya jawab hadits berbasis Qwen 2.5 7B Instruct melalui tiga tahap. Pertama, Supervised Fine tuning (SFT) dengan Quantized Low-Rank Adaptation (QLoRA) pada 988 pasangan instruksi-respons yang dipilih dari 1.730 data mentah menggunakan Instruction Following Difficulty (IFD) Scoring berbasis rasio perplexity pada rentang P20–P80. Kedua, Direct Preference Optimization (DPO) Iterasi 1 dengan strategi off-policy menyebabkan regresi perilaku model akibat perbedaan distribusi data. Ketiga, DPO Iterasi 2 dengan strategi on-policy penuh menghasilkan respons chosen (T=0,1) dan rejected (T=0,9) dari model SFT yang sama, menghasilkan 509 pasangan valid. Komponen Hybrid Retrieval-Augmented Generation (RAG) mengindeks 65.811 hadits dari 11 kitab di Qdrant Cloud menggunakan BGE-M3 dan BM25 dengan Reciprocal Rank Fusion. Evaluasi RAGAS v0.2.6 dengan hakim GPT-4o dan BERTScore berbasis xlm-roberta-base menunjukkan DPO Iterasi 2 memperoleh Faithfulness lebih tinggi (0,676 vs 0,633), Context Precision sempurna (1,000) pada kedua model, dan BERTScore F1 yang setara (0,8621 vs 0,8615). Temuan ini mengonfirmasi bahwa strategi on-policy DPO menghasilkan keselarasan perilaku yang lebih stabil untuk model bahasa domain-spesifik.
Analisa Faktor yang Mempengaruhi Kondisi Kesehatan Menggunakan Algoritma Frequent Pattern Growth Sukma Evadini; Alwis Nazir; Yusra Pizaini
Applied Information System and Management (AISM) Vol. 1 No. 1 (2018): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v1i1.8646

Abstract

Health is an important factor in human life that have to be guarded, both physically and mentally. This study aimed to analyze the factors that affect health condition using medical check up data. Factors analyzed were consuming alcohol, smoking, exercise, age and gender. The method was the association rule using FPGrowth. The result of this study was factors that affect the health condition is alcohol, exercise and age. This result evidenced by the rules A3→K3, which means that if a person consumes more alcohol than 4 days/week with the amount of alcohol is less than 180ml/day, then health condition was poor with 11% support and 67% confidence. E1→K3, which means that if one rarely exercise then health condition was poor with 24% support and 99% confidence. G2→K3, which means that if a person in middle age group, then the condition of health was poor with 24% support and 99% confidence.
Text to Speech Bahasa Jawa dialek Solo-Jogja dengan Metode VITS Putri Syakira Wirdiani; Muhammad Fikry; Yusra Yusra; Febi Yanto; Pizaini Pizaini
TEKNIKA Vol. 19 No. 3 (2025): Teknika September 2025
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.16294499

Abstract

Pengembangan TTS di Indonesia masih berfokus pada Bahasa Indonesia dan bahasa asing, sementara bahasa daerah seperti Jawa dialek Solo-Jogja belum banyak tersentuh, padahal memiliki banyak penutur dan nilai budaya tinggi. Penelitian ini mengembangkan model TTS untuk dialek tersebut menggunakan metode Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech (VITS). Metode ini dipilih karena kemampuannya mengintegrasikan inferensi variasional, aliran normalisasi, dan pelatihan adversarial secara end-to-end, sehingga menghasilkan suara sintetis dengan kualitas lebih alami. Dataset berisi 450 pasangan teks dan audio dari penutur asli, dibersihkan manual dan disusun dalam format LJSpeech. Sebanyak 428 data digunakan untuk pelatihan dan 22 untuk evaluasi. Model dilatih menggunakan Coqui TTS di Google Colab dengan fonemizer eSpeak. Setelah pelatihan, model terbaik digunakan untuk menyintesis 50 kalimat uji yang dinilai oleh lima penutur asli menggunakan metode MOS. Rata-rata skor yang diperoleh adalah 4,088, melampaui standar minimum 4,0. Meski begitu, masih ada kekurangan dalam kejelasan fonem dan kealamian jeda. Hasil ini menunjukkan potensi besar TTS untuk pelestarian bahasa daerah dan pengembangan teknologi serupa untuk bahasa lokal lainnya.
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 Arif Marsal 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 Fitra Kurnia Fitri Insani Fitri Insani Fitri Insani Fitri, Dina Deswara Gusti, Siska Kurnia Haikal Zikri Heru Sukoco Husnan Husnan Ibrahim Armadian Pujakesuma Ilham Habibi Hasibuan Iwan Iskandar Iwan Iskandar Iwan Iskandar Iwan Iskandar Iwan Jasril Jasril Jesi Alexander Alim Kana Saputra S Khonofi, Khoidir Lestari Handayani Lola Oktavia m azwan M Wandi Dwi Wirawan M. Saski Mandiro, Mulia Anton Mery Berlian Muhammad Affandes Muhammad Affandes Muhammad Affandes Muhammad Azmi Muhammad Fauzan Muhammad Fikry Muhammad Irsyad Muhammad Irsyad Muhammad Ridha 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 Syakira Wirdiani Putri, Adilah Atikah Rahmad Abdillah Rahmad Kurniawan Reski Mai Candra Reski Mai Chandra Rometdo Muzawi Roziana Roziana, Roziana Saktioto Saktioto Suci Rahayu Sugi Guritman Sukma Evadini Surya Agustian Suwanto Sanjaya Syarifuddin Syarifuddin Tahir, Musa Tarmizi, Veci Cahyono Teddie Darmizal Thahir, Musa Umar Syarif Vebrianto, Rian Wenny Tarisa Oktaviany Yelfi Vitriani Yovita Yovita Yusra Yusra, Yusra Zuriati Ardila Safitri