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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Teknika SITEKIN: Jurnal Sains, Teknologi dan Industri CESS (Journal of Computer Engineering, System and Science) Jurnal CoreIT JURNAL MEDIA INFORMATIKA BUDIDARMA Indonesian Journal of Artificial Intelligence and Data Mining Seminar Nasional Teknologi Informasi Komunikasi dan Industri Jurnal Informatika Universitas Pamulang Malikussaleh Journal of Mathematics Learning (MJML) Jurnal Nasional Komputasi dan Teknologi Informasi JURIKOM (Jurnal Riset Komputer) TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi, Kendali, Komputer, Elektrik, dan Elektronika Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jurnal Tekinkom (Teknik Informasi dan Komputer) Indonesian Journal of Electrical Engineering and Computer Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Computer Science and Information Technology (CoSciTech) Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Bulletin of Information Technology (BIT) Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Sains dan Informatika : Research of Science and Informatic JPLED
Jasril Jasril
Universitas Islam Negeri Sultan Syarif Kasim Riau
Aerospace Engineering Arts 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 Social Sciences Transportation Veterinary Other

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Integrasi Tamadun Melayu dalam Kurikulum Madrasah Ibtidaiyah sebagai Upaya Penguatan Pendidikan Karakter Susiandri; Jasril; Alifiyoni Rahmat Umara; M. Muda
Journal of Practice Learning and Educational Development Vol. 6 No. 2 (2026): Journal of Practice Learning and Educational Development (JPLED) in Press
Publisher : Global Action and Education for Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58737/jpled.v6i2.1059

Abstract

Character education has become a major focus in basic education, including in Madrasah Ibtidaiyah (MI), in line with the increasing moral and social challenges faced by students in the era of globalization. One relevant approach to strengthening character is the integration of local wisdom values, particularly Malay civilization, into the learning curriculum. Malay civilization contains noble values such as religiosity, politeness, mutual cooperation, responsibility, and respect for customs and the social environment. This study aims to describe the integration of Malay civilization into the Madrasah Ibtidaiyah curriculum as an effort to strengthen students' character education. The research used a qualitative approach with a case study design. Data collection techniques included learning observation, interviews with teachers and madrasah principals, and documentation of learning tools and school activities. Data analysis was carried out through data reduction, data presentation, and conclusion drawing. The results show that the integration of Malay civilization values into the MI curriculum can be done through the development of teaching materials, contextual learning strategies, school cultural habits, and teacher role models. This integration has been proven to contribute to strengthening students' religious character, discipline, responsibility, and social awareness. Thus, Malay civilization can be an effective cultural foundation in supporting character education at Madrasah Ibtidaiyah.
Sistem Tanya-Jawab Berbasis Chatbot Telegram Tentang Fiqih Kontemporer Menggunakan Langchain Dan LLM Muhammad Mulky Mar'arif; Nazruddin Safaat Harahap; Jasril Jasril; Muhammad Affandes
TEKNIKA Vol. 19 No. 2 (2025): Teknika Mei 2025
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15437200

Abstract

Informasi mengenai fiqih kontemporer sangat susah didapatkan, terkhusus berasal dari ustadz Syekh Al-Qardhawi. Perlunya sebuah layanan informasi yang bisa memberikan jawaban dari pertanyaan seputar fiqih kontemporer, salah satunya yaitu memanfaatkan teknologi saat ini seperti chatbot yang ada pada telegram. Dengan memanfaatkan chatbot pada telegram dapat menghasilkan sebuah sistem tanya-jawab mengenai fiqih kontemporer. Jadi, penelitian ini bertujuan untuk menerapkan sistem tanya-jawab berbasis chatbot Telegram mengenai fiqih kontemporer. Penelitian ini juga memanfaatkan metode langchain dan large language model (LLM) agar dapat menciptakan sistem tanya-jawab yang optimal. Penelitian ini berhasil menunjukkan keefektifan nya dalam memberikan jawaban mengenai fiqih kontemporer yang mana hasil pengujian User Acceptance Test (UAT) dan Black Box Testing menunjukkan bahwa sistem ini dapat memberikan informasi yang akurat dan juga berfungsi sebagaimana mestinya sebagai sistem tanya-jawab tentang fiqih kontemporer.
Evaluation of Information Gain Feature Selection on Support Vector Machines Performance in Craniometric Sex Classification Sonya Aulia Febriana; Iis Afrianty; Jasril Jasril; Eka Pandu Cynthia
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 10 No. 2 (2026): Sisfo: Jurnal Ilmiah Sistem Informasi, Oktober 2026 (In Press)
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v10i2.28622

Abstract

Sex classification is a fundamental stage in forensic anthropology because it provides the basis for constructing an individual's biological profile during the identification process. Although Support Vector Machine (SVM) has demonstrated high performance for craniometric sex classification, previous studies have primarily focused on classification performance using the complete feature set, with limited evaluation of the trade-off between feature reduction and predictive performance. Therefore, this study aims to evaluate the influence of Information Gain feature selection on SVM performance, identify the optimal combination of Information Gain threshold and SVM kernel configuration, and analyse the trade-off between feature reduction and classification performance. The proposed approach was evaluated using the William W. Howells Craniometric Dataset consisting of 2,524 skull samples. After removing identification attributes, 82 predictor features were used for classification. The research process included data preprocessing, label transformation, Z-score normalization, Information Gain feature selection using threshold values of 0.01, 0.05, and 0.1, followed by classification using SVM with Linear, Radial Basis Function (RBF), Polynomial, and Sigmoid kernels. Model performance was evaluated using 10-fold cross-validation based on Accuracy, Precision, Recall, and F1-score. The baseline SVM model without feature selection achieved an accuracy of 89.59% using 82 features. Experimental results show that Information Gain effectively reduced feature dimensionality while maintaining competitive classification performance. The best feature-selection result was obtained using an Information Gain threshold of 0.01, which retained 68 features. The optimal configuration used the RBF kernel with C = 1 and gamma='auto', achieving an Accuracy of 89.42%, Precision of 90.73%, Recall of 89.69%, and F1-score of 90.17%. Compared with the baseline model, the Information Gain-based model reduced the number of features by 17.07% while producing an accuracy difference of only 0.17 percentage points. These findings indicate that Information Gain primarily contributes to feature reduction and model simplification rather than improving classification accuracy. The results demonstrate that a moderate reduction in craniometric features can maintain classification performance close to the baseline model and highlight the trade-off between feature reduction and predictive performance in computer-assisted forensic sex classification.
Co-Authors Afiana Nabilla Zulfa Ahmad Paisal Ahyani Junia Karlina Alifiyoni Rahmat Umara Alwis Nazir Amalia Hanifah Artya Dardiri Dardiri Deny Ardianto Dodi Efendi Eka Pandu Cynthia Eka Pandu Cynthia Elin Haerani Elin Haerani Elin Haerani Elin Haerani Elin Hearani Elvia Budianita Fadhilah Syafria Febi Yanto Fikri Kurnia Rahman Fikri Utri Amri Firman Zahri Fitri Insani Fitri Insani Fitri Insani Gusrifaris Yuda Alhafis Gusti, Siska Kurnia Hafez Almirza Iis Afrianty Ikhwan Habibi Ikhwanul Akhmad DLY Imam Hanafi Ismu Kusumanto Isnan Mellian Ramadhan Iwan Iskandar Lestari Handayani Lestari Handayani Lola Oktavia M Alfandri Aqilah M Ridho Saputra M Wandi Dwi Wirawan M. Fadil Martias M. Muda MAS`UD ZEIN Maulana Junihardi Meiky Surya Cahyana Mori Hovipah Mori Hovipah Muhammad Affandes Muhammad Affandes Muhammad Fauzan Muhammad Hasbi Assidiqqi Muhammad Irsyad Muhammad Mulky Mar'arif Muhammad Vio Hardiansyah Musa Thahir Mustakim Mustakim Mustakim Mustakim Nadila Handayani Putri Nazruddin Safaat H Novia Kumala Sari Novriyanto Novriyanto Nurul Gayatri Indah Reza Pizaini Pizaini Rahayu Anggraini Rahma Shinta Reski Mai Candra Rizuan Rizuan Said Nanda Saputra Saputra, Elvino Dwi Sarah Lasniari Sarah Lasniari Siti Ramadhani Sola Huddin Sonya Aulia Febriana Sonya Meitarice Surya Agustian Susiandri Suwanto Sanjaya Suwanto Suwanto Tiara Ramayanti Yoga Nur Pradana Yusra, Yusra Zulkifli M. Nuh