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All Journal Telematika : Jurnal Informatika dan Teknologi Informasi Pendas : Jurnah Ilmiah Pendidikan Dasar Jurnal Inotera JSiI (Jurnal Sistem Informasi) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal ICT : Information Communication & Technology Generation Journal JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) G-Tech : Jurnal Teknologi Terapan Jurnal Teknologi Informatika dan Komputer Reputasi: Jurnal Rekayasa Perangkat Lunak JUSTER: Jurnal Sains dan Terapan Jurnal Pengabdian Masyarakat - Teknologi Digital Indonesia Jurnal Pengabdian Masyarakat Bhinneka International Journal of Science and Environment Jurnal Masyarakat Madani Indonesia Jurnal Pengabdian Masyarakat Bangsa Amal Ilmiah: Jurnal Pengabdian Kepada Masyarakat Pandawa : Pusat Publikasi Hasil Pengabdian Masyarakat Horizon: Indonesian Journal of Multidisciplinary E-Amal: Jurnal Pengabdian Kepada Masyarakat Journal of Information Technology Smatika Jurnal : STIKI Informatika Jurnal Journal of Education and ICT
Sari, Yayak Kartika
Universitas Bhinneka PGRI
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management 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 Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Pengembangan Sistem Kursus Online Smart Study Club (SSC) Berbasis Adaptif Learning Path Menggunakan Kerangka Kerja Scrum Mumtaza, Ilyas Abdullah; Sari, Yayak Kartika; Iskandar, Joko
HORIZON: Indonesian Journal of Multidisciplinary Vol. 4 No. 3 (2026): HORIZON: Indonesian Journal of Multidisciplinary
Publisher : Lembaga Intelektual Muda (LIM) Maluku

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54373/v9vgnh98

Abstract

Online course-based learning generally still applies uniform materials and assessments to all students without considering differences in individual abilities. This condition results in a less personalized learning process and has the potential to reduce learning effectiveness. This study aims to develop a web-based online course system that implements an Adaptive Learning Path (ALP) to adjust the material and the difficulty level of questions based on student abilities. The study used a Research and Development (R&D) method with software development based on the Scrum framework, which includes the product backlog, sprint planning, sprint execution, and sprint review stages. The system implements the Item Response Theory (IRT) Rasch Model algorithm with the Maximum Likelihood Estimation (MLE) method to estimate student abilities and determine questions adaptively. The results of the study produced an online course platform equipped with adaptive learning path features, IRT-based automatic quizzes, a leaderboard, and a material management administration panel. Black box testing results showed that all system functions ran well and were valid, while beta testing on 26 users obtained a feasibility level of 86.8%, which is categorized as very feasible. These findings indicate that the developed system is able to support more personalized, adaptive, and effective learning according to the abilities of each student.
Pengembangan Sistem Service Elektronik dengan Fitur Chatbot dan Integrasi Whatsapp pada Rama Jaya Service Electronic Menggunakan Framework Laravel Arianto, Rifky Dio; Sari, Yayak Kartika; Cahyono, Taufiq Agung
HORIZON: Indonesian Journal of Multidisciplinary Vol. 4 No. 3 (2026): HORIZON: Indonesian Journal of Multidisciplinary
Publisher : Lembaga Intelektual Muda (LIM) Maluku

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54373/x8c8yz96

Abstract

This study aims to develop a web-based electronic service system at Rama Jaya Service Electronic to improve the effectiveness of repair service management and customer communication. The study uses the Agile Kanban software development method, which allows the development process to be carried out in stages and adaptively according to user needs. Research data was obtained through observation, interviews, and literature studies. The system was developed using the Laravel framework with a MySQL database and is equipped with service management, transaction, chatbot, WhatsApp integration, and user dashboard features. The system quality was evaluated through Black Box Testing, System Usability Scale (SUS), and GTmetrix to assess aspects of system functionality, usability, and performance. The results of the study indicate that the developed system is able to support the management of electronic services more effectively and structured, accelerate the delivery of information to customers, and improve service quality. Thus, the developed web-based electronic service system can be a solution to support the digitalization of business processes at Rama Jaya Service Electronic.
Identification of Quantity Relationships in Math Story Problems Using Bidirectional Long Short-Term Memory (Bi-LSTM) Puspita, Diana Ayu; Prasetya, Agung; Sari, Yayak Kartika
HORIZON: Indonesian Journal of Multidisciplinary Vol. 4 No. 3 (2026): HORIZON: Indonesian Journal of Multidisciplinary
Publisher : Lembaga Intelektual Muda (LIM) Maluku

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54373/hijm.v4i3.6049

Abstract

Penelitian ini bertujuan untuk mengidentifikasi hubungan kuantitas dalam soal cerita matematika menggunakan metode Bidirectional Long Short-Term Memory (BiLSTM). Permasalahan dalam penelitian ini adalah kesulitan dalam memahami dan mengklasifikasikan hubungan kuantitas secara otomatis akibat variasi struktur kalimat dan konteks bahasa. Metode yang digunakan adalah pendekatan deep learning dengan tahapan pengumpulan data, preprocessing, pembentukan vocabulary, pelatihan model, dan evaluasi model. Hasil penelitian menunjukkan bahwa model BiLSTM mampu mengklasifikasikan hubungan kuantitas dengan baik dengan memperoleh nilai accuracy sebesar 0.9224 serta nilai precision, recall, dan F1-score yang relatif tinggi pada setiap kelas. Hal ini menunjukkan bahwa model memiliki performa yang baik dalam memahami pola hubungan kuantitas dalam teks soal cerita matematika, sehingga dapat digunakan sebagai pendekatan yang efektif untuk identifikasi hubungan kuantitas secara otomatis.
Design of an IOT-Based Digital Rice Weighing System (Smart Rice-Ws) to Improve Efficiency and Accuracy in Supporting Smart Village Economic Development Yayak Kartika Sari; Joko Iskandar; Nailariza Umami
G-Tech: Jurnal Teknologi Terapan Vol 10 No 4 (2026): G-Tech, Vol. 10 No. 4 October 2026
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/gtech.v10i4.11291

Abstract

Rice weighing in village-scale rice industries is generally still performed manually, resulting in dependence on operators, potential recording errors, and limited access to real-time weighing information. This study aims to formulate and develop the initial concept of SMART RICE-WS (Smart Rice Weighing System), an Internet of Things (IoT)-based digital rice weighing system designed to improve the efficiency, accuracy, and traceability of the weighing process. The research employs a Design-Based Research Methodology (DBR) through iterative stages of analysis, design, development, implementation, and evaluation. The research activities include existing process analysis, literature review and state-of-the-art analysis, user requirement identification, system architecture design, algorithm development, simulation module implementation, and initial testing. The proposed system integrates a Load Cell, HX711, ESP32, actuator, LCD, IoT communication, database/cloud storage, and monitoring dashboard. Initial testing was conducted through ten measurements using reference loads of 1 kg and 2 kg. The results showed that the system was able to measure both loads, with an average absolute error of 1.55%. These initial findings indicate that the Load Cell–HX711–ESP32 module can serve as a foundation for further system development. Subsequent development will focus on calibration, repeated testing, actuator integration, and IoT-based monitoring.
Sentiment Analysis of the Free Nutritious Meal (MBG) Program on TikTok Using Naïve Bayes Classifier Sukma Ajeng Griyandari; Fahrur Rozi; Yayak Kartika Sari
J-INTECH ( Journal of Information and Technology) Vol 14 No 03 (2026): Journal of Information and Technology
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v14i03.2458

Abstract

The Free Nutritious Meal (MBG) Program is an Indonesian government initiative to improve nutritional quality and support human resource development. As a public policy, it has generated diverse public responses on social media, particularly TikTok. The novelty of this study lies in utilizing TikTok comments, which remain underexplored in previous MBG sentiment studies, and employing expert-validated manual sentiment labeling to improve annotation reliability. This study applies the Naïve Bayes Classifier to analyze public sentiment toward the MBG Program using 3,190 TikTok comments, of which 1,294 were retained after relevance filtering, data cleaning, and manual labeling validated by two Indonesian language experts. Text preprocessing included cleaning, case folding, tokenization, normalization, stopword removal, and stemming, followed by TF–IDF feature weighting. The model was evaluated using stratified 10-fold cross-validation. It achieved 72.80% accuracy, 69.90% weighted precision, 73.20% weighted recall, and 71.40% F1-score. Negative sentiment dominated public discussion of the MBG Program. These findings demonstrate that combining expert-validated manual labeling, TF–IDF, and the Naïve Bayes Classifier provides a reliable approach for sentiment analysis of Indonesian social media text and offers useful insights for evaluating the implementation of the MBG Program
Co-Authors Agung Cahyono, Taufiq Agung Prasetya Agung Prasetya Agung Prasetya Ahmad Fathurrohim Ahmad Rofi Rizaqi Amartya Bambang Kusuma Amartya Bambang Kusuma Ananda Dicky Adinata Anwar, Ndaru Syaiful Arianto, Rifky Dio Dani Irwansyah Darel Trescanaya Diyah Anggraini Edy Susanto Fahrur Rozi Fahrur Rozi Farid Sukmana, Farid Ferry Wahyu Wibowo firlana, firlana eza putra Hilmy Mufadhdhol Putra Imam Sukwatus Suja'i Iskandar, Joko Kifatul Hasna Tria Widyarsi Kusrini Kusuma, Amartya Bambang Lailatul Musyarofa Latifatus Sariroh Luthfiana, Tias Hafidzotul Meyliana Wafaul Ummah Mochammad Ilham Aldi Wahyudi Mohamad Khoirul Ansor Muhyiddin, Sulthon Mumtaza, Ilyas Abdullah Nawang Rimarsha Alifdyani Nur Akhsin Alifian Hadi Nurwiyati Prihandari Okta Mayasari, Anisa Oktaviana Dyah Palupi Puspita, Diana Ayu Raharjo, Artha Khemal Febrianto Renzy Praha Nandiva Renzy Rozi, Fahrur Sari, Norma Novita Sukma Ajeng Griyandari Taufiq Agung Cahyono Titik Lina Widyaningsih Umami, Nailariza Veny Dwi Wahyuningsih Widiyanto, Wahyu Wijaya Yuliyanti, Nurul Eka