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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer ELINVO (Electronics, Informatics, and Vocational Education) Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Jurnal Sistem Informasi, Teknologi Informasi, dan Edukasi Sistem Informasi (JUST-SI) J-Intech (Journal of Information and Technology)
Satrio Hadi Wijoyo
Program Studi Teknik Informatika, Fakultas Teknologi Informasi, Institut Teknologi Sepuluh Nopember, Surabaya
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Library & Information Science

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Journal : journal of information technology and computer science

 1 
Development of Interactive Multimedia-Based Learning Media for Basic Graphic Design Subjects with the ADDIE Model Guidelines at SMK Negeri 5 Malang Husen, Dania Lazuardi; Herlambang, Admaja Dwi; Wijoyo, Satrio Hadi
Journal of Information Technology and Computer Science Vol. 9 No. 3: December 2024
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.93349

Abstract

This research aims to explain the results of the needs analysis in developing interactive multimedia-based learning media so that it can improve learning outcomes and support the learning interaction process and can motivate students during learning activities. This learning media was built by adapting the ADDIE model which consists Analysis, Design, Development, Implementation, and Evaluation phase. The results of this research test are the learning outcomes of students increase after using learning media. Hypothesis testing with Paired Sample T-Test technique produces a hypothesis that there are differences in learning outcomes due to the use of learning media. The test results based on the use of learning media by students resulted in an average eligibility of media in support of learning interactions of 85.81% and learning motivation of 87.05%. That is, learning media can be categorized as very feasible to be used to build learning interactions and learners' learning motivation.
Intelligent Computing System to Predict Vocational High School Student Learning Achievement Using Naïve Bayes Algorithm Herlambang, Admaja Dwi; Wijoyo, Satrio Hadi; Rachmadi, Aditya
Journal of Information Technology and Computer Science Vol. 4 No. 1: June 2019
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (5451.972 KB) | DOI: 10.25126/jitecs.20194169

Abstract

Vocational High School with ICT major need an intelligent computing system that could predict the student learning achievement. The system used fifteen achievement indicators and Naïve Bayes algorithm in data processing. Testing on student achievement data produces the conclusion that is the highest intelligent accuracy values in 53% with lowest accuracy value in 48% based on Naïve Bayes algorithm processing. The result of mining process using Naïve Bayes algorithm can be used to classify the 3rd year student achievement to five categories. These categories are Very Good, Good, Fair, Poor, and Failed. The system testing result showed that this intelligent computing system function was fitted with Vocational High School’s system requirement, system design, and system implementation.
Interactive Digital Book Development for Computer and Network Fundamental Teaching Subject based on Four - D Model at Indonesian Computer and Network Engineering Vocational High School Herlambang, Admaja Dwi; Akhmadi, Lutfiani; Wijoyo, Satrio Hadi
Journal of Information Technology and Computer Science Vol. 4 No. 2: September 2019
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2734.954 KB) | DOI: 10.25126/jitecs.201942118

Abstract

Computer and Network Fundamental is one of the teaching subjects atComputer and Network Engineering Vocational High School in Indonesia. Thelearning activities at the research location was less interactive because of thelearning process still uses conventional textbooks or static digital books.Solutions that offered in the research are not only interactive digital book productdevelopment inappropriate way but also product implementation in experimentaldesign. The development used Four-D Model. The experimental design usedMatching-Only Pretest-Posttest Control Group Design. The instrumentation usedobservation, interviews, questionnaires, and tests. Content Validity Content(CVR) value based on Subject Matter Experts (SMEs) evaluation result for goal,learner, learning, context, and technical criteria are above 0.75. Paired T-Test andIndependent T-Test results showed that interactive digital book implementationin the learning process can cause an enhancement in student learning outcomes.
Mastery of Technological Pedagogical And Content Knowledge (TPACK) Prospective Teacher In ICT Expertise Brawijaya University Latifah, Luluk; Herlambang, Admaja Dwi; Wijoyo, Satrio Hadi
Journal of Information Technology and Computer Science Vol. 6 No. 3: December 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1153.904 KB) | DOI: 10.25126/jitecs.202163350

Abstract

The Information Technology Education (ITE) study program, Faculty of Computer Science, Universitas Brawijaya requires its students to take part in Pengenalan Lapangan Persekolahan (PLP) 2 according to Permenristekdikti No. 55 of 2017 in order to be able to produce prospective teachers who have the competence of educators. This study describes the gap in mastery of competencies with the TPACK framework based on the results of PLP 2 activities which are compared with standard values using a discrepancy evaluation model. The results of the gap are mapped using the method Importance Performance Analysis (IPA) to determine the priority scale for improvement of variables according to positions in certain quadrants. Through the IPA method, the variables that are prioritized to improve their mastery are TPK and PCK because they have very small gaps. Recommendations are given for the TPK variable to be given a pretest and posttest on the material for preparing teaching tools and training in the preparation of lesson plans. For the PCK variable, should be given pretest and posttest to the study material for theoretical and practical learning scenarios, the activities are needed lesson study which is carried out at least twice.
Student Stress Level Prediction Based on DASS-42 Questionnaire Using XGBoost Algorithm: A Case Study of Undergraduate Information Technology Education Students Reinanda, Moch Zoel; Wijoyo, Satrio Hadi; Wicaksono, Satrio Agung
Journal of Information Technology and Computer Science Vol. 11 No. 1: April 2026
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.111831

Abstract

Stress among university students negatively impacts their academic progress and mental health. Early detection is crucial for targeted intervention. This research designs and evaluates a machine learning model using the XGBoost algorithm to predict stress among undergraduate students of Information Technology Education at Universitas Brawijaya. Utilizing the CRISP-DM methodology, the study processes data from the DASS-42 questionnaire and academic records. The workflow included data pre-processing to handle missing values and class imbalance, followed by model training and evaluation. Six scenarios tested prediction targets (five-level multi-class and binary ‘Normal’ or ‘Stress’), data handling, and hyperparameter tuning. Results indicate that the binary classification model was significantly superior. The best model, utilizing original data and default parameters, achieved an accuracy of 97.87%. Evaluation proved its reliability, achieving 100% recall for the ‘Stress’ class, ensuring no at-risk cases were missed (0 False Negatives). Feature importance analysis identified Mother’s Education as the dominant predictor. The research output includes a functional dashboard prototype equipped with LIME interpretation for individual case analysis.
Naive Bayes with SMOTE for Predicting the Competitiveness of Vocational School Graduates on Imbalanced Data (Case Study: SMK Negeri 3 Malang) Arsy Kurnia Fitri; Wijoyo, Satrio Hadi; Hariyanti, Uun
Journal of Information Technology and Computer Science Vol. 11 No. 1: April 2026
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.111870

Abstract

Vocational high schools (SMK) aim to produce work-ready graduates. However, the open unemployment rate (TPT) for SMK graduates remains high at 9.01%, indicating a significant competency gap. This study designs a model to predict graduates workforce competitiveness using the Naive Bayes algorithm combined with the Synthetic Minority Over-sampling Technique (SMOTE). SMOTE is employed to address the class imbalance between capable and incapable graduates. The study follows the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology, utilizing academic scores and tracer study datasets. Evaluation results demonstrate that applying SMOTE with a 70:30 train-test split successfully increased model accuracy to 97%. Notably, the model effectively detects the minority class with a Recall of 90%. Furthermore, cross-validation yielded an average accuracy of 97.66%, demonstrating stable performance. Finally, the model was implemented as a web-based dashboard to serve as an early warning system for schools.
Predicting On-Time Graduation Using the C 4.5 Algorithm with Forward Selection Optimization (Case Study: Computer Engineering Study Program, Faculty of Computer Science, Brawijaya University) Bangse, Ni Nyoman Dinda Permata Putri; Wijoyo, Satrio Hadi; Bachtiar, Fitra Abdurrachman
Journal of Information Technology and Computer Science Vol. 11 No. 2: August 2026
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.2026112871

Abstract

On-time student graduation is a key indicator of academic effectiveness and higher education quality. Timely graduation reflects efficient academic management, while delays may negatively impact institutional performance and accreditation. Graduation delays are influenced by various academic and non-academic factors, making early prediction essential. This study aims to develop an on-time graduation prediction model using the C4.5 algorithm optimized with the forward selection method. The research was conducted in the Computer Engineering Study Program, Faculty of Computer Science, Universitas Brawijaya, using student data from the 2018–2021 cohorts. The dataset includes both academic and nonacademic attributes. The modeling process followed the CRISP-DM framework, and model performance was evaluated using a confusion matrix. The results show that the C4.5 model without feature selection achieved an accuracy of 63%, while the application of forward selection significantly improved accuracy to 83%. These findings indicate that feature selection plays a crucial role in enhancing prediction performance. The proposed model can support academic stakeholders in data driven decision making and in designing strategies to improve on-time graduation rates.  
Co-Authors 'Aisy, Rihadatul Abdurrahman, Ikzaaz Bakhtar Abhirama, Fauzan Akbar Abiyyu, Muhammad Alifandi Addieni, Jihan Syahda Aditya Rachmadi, Aditya Admaja Dwi Herlambang, Admaja Dwi Adristi, Tikta Ahmad Afif Supianto Ahnaf, Muhammad Farrel Reginaldo Aji, Yanuar Bimantoro Akbar, Muhammad Aminul Akhmadi, Lutfiani Alfian Hakim Alifian, Faris Ihsan Alimah, Cindy Felita Nur Almas, Muhammad Fikri Almira Syawli Ananda, Reza Berlian Anandhika, I Made Bagus Ananta, Aprilia Andi Reza Perdanakusuma, Andi Reza Aprilianto, Pratama Ardelia, Ayunizar Fata Ardiansyah, M. Iqbal Aritonang, Elsa Arsy Kurnia Fitri Aryani, Lisa Aryati, Meilita Dwi Aryo Pinandito Astriya Nugraha, Dwi Cahya Aswin Suharsono, Aswin Atmaja, Alvino Dwiky Aurellia, Salsabila Rachma Ayuningdias, Risky Azizi Fahreza, Muhammad Alfian Kurnia Azkiyah, Azka Bangse, Ni Nyoman Dinda Permata Putri Bayu Rahayudi Bayu Satriawan, Eka Bihantoro, Riyan Budi Bilqis, Ariqa Budiyanti, Alifia Putri Cahyani, Ernita Dwi Dewa Yani, Kartika Putri DEWI RAHMAWATI Dian Eka Ratnawati Diana Purwitasari dicky setiawan, chandra Djoko Pramono Dwinanda, Ashila Gisara Edmund Pierre Purba, Geoffrey Eris Maghfiroh, Intan Sartika Fadhilah, Irsya Salim Fadhlika, Nidi Amalia Faizatul Amalia, Faizatul Farrel, Zhafa Anbiya Ananta Fatmawati, Fatmawati Faturani, Bunga Sauma FEBIANA, DHEA RACHMA Firdaus, Raihan Zahran Fitra Abdurrachman Bachtiar Fitri, Arsy Kurnia Ghani Wijaya, Alfiyanto hafilah, salma Hanggara, Buce Trias Hanif, Muhammad Fauzan Hanifah Muslimah Az-Zahra, Hanifah Muslimah Hanun, Putri Nabilah Hariz Farisi Herawati, Serra Nadya Indi Herlambang, Adwaja Dwi Herlando, Muhammad Raafi Heryana, Ana Hikmah Amalia, Dwi Himawat Aryadita, Himawat Husen, Dania Lazuardi Ibrohim, Muhammad Idota, Patrick Jore Ikhsawiyanthi, Anisah Irmawan, Rozy Setia Iskandar, Fahru Setiawan Issa Arwani Jahiro, Almaas Janara Khansa, Elyzia Jannah, Ghina Shofa Raudhatul Jatmiko, Alvindo Tri Juan, Helga Julen, Eiko Farah Diva Khalid Rahman, Khalid Kirana, Urdha Egha Krisnandi, Didik Kurniasari, Salvia Dyah Laksmana, Adysha Jauseva Lubis, Ade Fatmasari Macira Balqis Abdul Gopur, Maersyifaa Maulana, Alif Rizal Mochamad Chandra Saputra, Mochamad Chandra Mubarok, Muhammad Rosyid Mulyadi, Alfansya Achmad Muslichah, Nur Wachidatul Nabawiyyatin, Ala Millatin Nanang Yudi Setiawan Nugraha, Dwi Cahya Astriya Nurul Hidayat Octavia, Sarah Uli Perdanalusuma, Andi Reza Perwira, Muhammad Phadung, Muneeroh Pinem, Gilbert Pinem, Gilbert Aryaduta Prabandari, Putu Ayu Purnama Dyah Prakoso, Bondan Sapta Prakoso, Erick Pranaliwa, I Putu Ardhika Pryono, Muhammad Adam Purnama, Putu Tya Virnayanti Purnawirawan, Okta Purnomo, Welly Puspita, Amelia Dhea PUSPITA, ARBALIYAH Putra, Kristantheo Nathaniel Damara Putri, Hana Rizkia Iswana Putri, Rizka Saudah Yunida Putri, Salsabila Tjahya Kusuma Rahmandita, Prasetya Naufal Ramadana, Muhammad Rifqy Ramadhan Al Fauzi, Rafly Ramadhan, Rakhmad Fajar Ramadhani, Aditya Wahyu Reinanda, Moch Zoel Retno Indah Rokhmawati, Retno Indah Riswan Septriayadi Sianturi Ro'if, M. Rosady, Annisa Rosanti, Mitha Diah Rosida, Khanif Rozi, Fahrur Salim, Pratama Maulidi Ega Salsabila, Syahda Rani Salshabila, Alyssa Salshabila, Alyssa Melani Salwa, Shafa Nathaniela Satriawan, Eka Bayu Satrio Agung Wicaksono Sebayang, Gading Sembiring, Rinawati Septiyan Andika Isanta Setyawan, Romi Fajar Sholihah, Tuffahati Sibuea, Sandro Christopher Siregar, Rafi Arya Sitepu, Mikha Aziel Christian Sugiharto, Pradiptya Kahvi Suhartanto, Nathalia Clarissa Anggraini SUPRAPTO Suprihono, M. Rezky Revansyah Suryananda, Dananjaya Cikal Danis Suryanugraha, Mohamad Ariq Susanto, Ananta Risky Tambing, Nathania Maerella Arungla'bi' Tarihoran, Aditya Nugraha Tri Afirianto, Tri Uun Hariyanti Uun Hariyanti, Uun Waworuntu, Kenneth Clinton Welly Purnomo Wibisono Sukmo Wardhono, Wibisono Sukmo Wibisono, Jonathan Wicaksono, Abdul Harris Widhiprasetyo, Fadhil Widhy Hayuhardhika Nugraha Putra wijaya, khonsa Yanuar, Athallarifky Yanuardhana, Anugrah Daffa Yufis Azhar Yusi Tyroni Mursityo Zaein, Nabila