Article Per Year (5 Year)
p-Index From 2020 - 2025
5.689
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering Tekno : Jurnal Teknologi Elektro dan Kejuruan Teknologi dan Kejuruan: Jurnal teknologi, Kejuruan dan Pengajarannya Jurnal Inovasi Teknologi Pendidikan International Journal of Advances in Intelligent Informatics Proceeding of the Electrical Engineering Computer Science and Informatics JOIN (Jurnal Online Informatika) Briliant: Jurnal Riset dan Konseptual JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information Technology and Computer Science INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Knowledge Engineering and Data Science Pendas : Jurnah Ilmiah Pendidikan Dasar Cetta: Jurnal Ilmu Pendidikan ILKOM Jurnal Ilmiah at-tamkin: Jurnal Pengabdian kepada Masyarakat SENTIA 2016 SENTIA 2015 MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Karinov TRIDARMA: Pengabdian Kepada Masyarakat (PkM) Edunesia : jurnal Ilmiah Pendidikan Letters in Information Technology Education (LITE) Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) DECODE: Jurnal Pendidikan Teknologi Informasi Bulletin of Community Engagement Journal of Education Research Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Ekonomi, Bisnis dan Pendidikan (JEBP)
Didik Dwi Prasetya
Universitas Negeri Malang
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

Published : 56 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 56 Documents
Search

 2   3   4   5   6 
Multilingual Parallel Corpus for Indonesian Low-Resource Languages Sulistyo, Danang Arbian; Wibawa, Aji Prasetya; Prasetya, Didik Dwi; Ahda, Fadhli Almu’iini; Arya Astawa, I Nyoman Gede; Andika Dwiyanto, Felix
JOIV : International Journal on Informatics Visualization Vol 9, No 5 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.5.3412

Abstract

Indonesia has an extraordinary number of languages, with more than 700 regional languages such as Javanese, Madurese, Balinese, Sundanese, and Bugis. Despite the wealth of languages, digital resources for these languages remain scarce, making the preservation and accessibility of digital languages a significant challenge. Research was conducted to address this gap by building a multilingual parallel corpus consisting of more than 150,000 phrase pairs extracted from Bible translations in five regional languages in Indonesia. Rigorous preprocessing, normalization, and Unicode tokenization were performed to improve data quality and consistency. The encoder-decoder architecture was a key focus in the development of the NMT model. Evaluation focused on forward and backward translation directions, which were measured using BLEU scores. The results show that forward translation consistently outperforms backward translation. The Indonesian Javanese model produced a score of 0.9939 for BLEU-1 and 0.9844 for BLEU-4, indicating a high level of translation quality. In contrast, reverse translation tasks, such as translating from Sundanese to Indonesian, presented significant challenges, with BLEU-4 scores as low as 0.3173. This illustrates the complexity of the translation system from Indonesian to local languages. If future research focuses on transformer-based models and incorporates additional linguistic parameters to enhance the accuracy of natural language processing (NLP) models for Indonesia's underrepresented regional languages, this work provides a dataset that can be utilized for that purpose.
The Power of Play! A Review of Gamification Design Trends and Their Impact on Learning Outcomes Haq, Salsabila Thifal Nabil; Prasetya, Didik Dwi; Ichwanto, Muhammad Aris; Samodra, Joko; Prasetya, Luhur Adi
Edunesia : Jurnal Ilmiah Pendidikan Vol. 6 No. 3 (2025)
Publisher : research, training and philanthropy institution Natural Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51276/edu.v6i3.1340

Abstract

Digital transformation in education has accelerated the integration of gamification as an interactive and motivational learning strategy. This study presents a systematic literature review following the SPAR 4 SLR protocol, based on the analysis of 25 empirical research articles published between 2020 and 2025. The objective is to explore the distribution and impact of various gamification elements on cognitive, affective, and psychomotor learning domains. Elements that provide rewards, such as points (88%), badges (80%), and leaderboards (72%), were the most commonly applied in learning environments. In contrast, reflective features such as storytelling (20%), learner autonomy (24%), and role-playing activities (16%) were especially effective in increasing emotional involvement, self-directed learning, and practical abilities. Through thematic analysis using NVivo 12, the study found that external rewards often encourage only temporary motivation, whereas reflective components support more lasting and meaningful learning processes. The study concludes by recommending a balanced and goal-oriented approach to gamification design, which can strengthen its role as a transformative educational strategy in the digital learning era.
Educational Data Mining: Multiple Choice Question Classification in Vocational School Sucipto, Sucipto; Dwi Prasetya, Didik; Widiyaningtyas, Triyanna
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 2 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i2.3499

Abstract

Data mining on student learning outcomes in the education sector can overcome this problem. This research aimed to provide a solution for selecting quality multiple choice questions (MCQ) using the results of students’ mid-semester exams in vocational high schools using a Data Mining approach. The research method used was the Cross-Industry Standard Process for Machine Learning (CRISP-ML) model. Steps to assess the accuracy of analyzing the difficulty level of questions based on student profile data and midterm test results. The data used in this research were the findings of basic computer tests on mid-term exams in mathematics disciplines at vocational high schools. This research used several classification algorithms, including SVM, Naive Bayes, Random Forest, Decision Three, Linear Regression, and KNN. The results of evaluating the classification
Comparison of Text Representation for Clustering Student Concept Maps Fatrisna Salsabila, Reni; Dwi Prasetya, Didik; Widyaningtyas, Triyanna; Hirashima, Tsukasa
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 24 No. 2 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i2.4598

Abstract

This research aims to address the critical challenge of selecting a text representation method that effectively captures students’ conceptual understanding for clustering purposes. Traditional methods, such as Term Frequency-Inverse Document Frequency (TF-IDF), often fail to capture semantic relationships, limiting their effectiveness in clustering complex datasets. This study compares TF-IDF with the advanced Bidirectional Encoder Representations from Transformers (BERT) to determine their suitability in clustering student concept maps for two learning topics: Databases and Cyber Security. The method used applies two clustering algorithms: K-Means and its improved variant, K-Means++, which enhances centroid initialization for better stability and clustering quality. The datasets consist of concept maps from 27 students for each topic, including 1,206 concepts and 616 propositions for Databases, as well as 2,564 concepts and 1,282 propositions for Cyber Security. Evaluation is conducted using two metrics Davies-Bouldin Index (DBI) and Silhouette Score, to assess the compactness and separability of the clusters. The result of this study is that BERT consistently outperforms TF-IDF, producing lower DBI values and higher Silhouette Scores across all clusters (k= 2 - k=10). Combining BERT with K-Means++ yields the most compact and well-separated clusters, while TF-IDF results in overlapping and less-defined clusters. The research concludes that BERT is a superior text representation method for clustering, offering significant advantages in capturing semantic context and enabling educators to identify student misconceptions and improve learning strategies.
Revealing Interaction Patterns in Concept Map Construction Using Deep Learning and Machine Learning Models Laily, F.ti Ayyu Sayyidul; Prasetya, Didik Dwi; Handayani, Anik Nur; Hirashima, Tsukasa
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 24 No. 2 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i2.4641

Abstract

Concept maps are educational tools for organizing and representing knowledge, enhancing comprehension, and memory retention. In concept map construction, much knowledge can be utilized. Still, concept map construction is complex, involving actions that reflect a user’s thinking and problemsolving strategies. Traditional methods struggle to analyze large datasets and capture temporal dependencies in these actions. To address this, the study applies deep learning and machine learning techniques. This research aims to evaluate and compare the performance of Long Short-Term Memory (LSTM), K-Nearest Neighbors (K-NN), and Random Forest algorithms in predicting user actions and uncovering user interaction patterns in concept map construction. This research method collects and analyzes interaction logs data from concept map activities, using these three models for evaluation and comparison. The results of this research are that LSTM achieved the highest accuracy (83.91%) due to its capacity to model temporal dependencies. Random Forest accuracy (80.53%), excelling in structured data scenarios. K-NN offered the fastest performance due to its simplicity, though its reliance on distance-based metrics limited accuracy (70.53%). In conclusion, these findings underscore the practical considerations in selecting models for concept map applications; LSTM demonstrates effectiveness in predicting user actions and excels for temporal tasks, while Random Forest and K-NN offer more efficient alternatives in computational.
AI UNTUK GENERASI CERDAS: BELAJAR TEKNOLOGI BERSAMA PENDIDIKAN PROFESI GURU Abdul Wafi; Adi Wahyu Wardani; Ainun Nur Baiti; Dwi Widiyasari; Ella Amelia Widodo; Moh. Nur Zamzami; M. Ajie Kalifatullah; Khoirul Anwar; Sigit Perdana; Azhar Ahmad Smaragdina; Didik Dwi Prasetya
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 10 No. 03 (2025): Volume 10 No. 03 September 2025
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v10i03.30839

Abstract

The advancement of artificial intelligence (AI) technology presents both challenges and opportunities in the field of education. This report presents the outcomes of a community service activity conducted by lecturers and student-teachers from the Teacher Professional Education (PPG) Program at Universitas Negeri Malang through an educational talk show at SMA Negeri 8 Malang. The initiative aimed to improve digital literacy among students and teachers regarding the ethical and responsible use of AI. The talk show involved students, teachers, and student council members (OSIS), and featured expert speakers who discussed the fundamentals of AI, its applications, and associated risks such as technological dependency and academic plagiarism. The activity led to increased awareness of the benefits and challenges of AI, as well as the importance of academic integrity and character in its use. The school responded positively by establishing an AI Literacy Team, organizing teacher workshops, and launching the campaign “Smart AI, Not Instant AI.” This program serves as a model for promoting an adaptive and ethical digital culture within secondary education.
Co-Authors Abdul Wafi Adi Wahyu Wardani Ahmad Fajruddin Syauqi Ainun Nur Baiti Aji P Wibawa Aji Prasetya Wibawa Akbar, Asna Isyarotul Andika Dwiyanto, Felix Andrew Nafalski Anik Nur Handayani Anjar Dwi Rahmawati Arifiati Fitri Anggraini Aryo Pinandito Ashar, Muhammad Azhar Ahmad Smaragdina Bagaskoro Biantoro, Yudhi Bintang Romadhon Cakir, Gulsun Kurubacak Denis Eka Cahyani Dwi Widiyasari Dyah Ayu Langening Tyas Ella Amelia Widodo Erlik Prasetyo Wahyudi F.ti Ayyu Sayyidul Laily Fadhli Almu’iini Ahda Fadli Hidayat, M. Noer Fatrisna Salsabila, Reni Firdaus, Nabilah Zakiyah Salmaa Gigih Perkasa Gradiyanto Radityo Kusumo Hafid, Ahmad Hakkun Elmunsyah Hanifah Muslimah Az-Zahra, Hanifah Muslimah Haq, Salsabila Thifal Nabil Hariyanto Hariyanto Hayashi, Yusuke Hirashima, Tsukasa I Nyoman Gede Arya Astawa Ida Agus Setyani Intan Sulistyaningrum Sakkinah Iskandar Syah, Abdullah KHOIRUL ANWAR Kusumo, Gradiyanto Radityo Laily, F.ti Ayyu Sayyidul Lalu Ganda Rady Putra Langlang Gumilar Lismi Animatul Chisbiyah Lutfi Budi Ilmawan, Lutfi Budi M. Ajie Kalifatullah Marsono Marsono Maulana Nur Antoro Putro Mayadi, Mayadi Mega Oktaviana Moh. Nur Zamzami Moh. Zainul Falah Mokhamad Nuryakin Muhammad Arief Nugroho Muhammad Aris Ichwanto muhammad hafiizh, muhammad Muhammad Jauharul Fuady Muhammad Mushawwir Mukhamad Angga Gumilang Muladi Nafalski, Andrew Nanscy Evi Wardani Natalina Wahyu Siswijayanti Nena Erviana Nunung Nurjanah Nur Hidayat, Wahyu Prasetya, Luhur Adi Prasetyo, Muchamad Wahyu Pratama, Wahyu Styo Prihandicha, Adiftya Bayu Ratnaduhita, Nadiah Alma Reni Fatrisna Salsabila Ridlo, Muhammad Zidni Rofiudin, Amir Ryan Kurniawan Samodra, Joko Setiadi Cahyono Putro Setiawan, Ahmad Yusuf Sigit Perdana Siti Sendari Sofiya Anggraini Sucipto Sucipto Sucipto Sucipto Sulistyo, Danang Arbian Syaad Patmanthara Syaichul Fitrian Akbar Syamsul Arifin Triyanna Widiyaningtyas Triyanna Widyaningtyas Triyanna Widyaningtyas, Triyanna Tsukasa Hirashima Tsukasa Hirashima Tsukasa Hirashima Tuwoso Utomo Pujianto Wahyu Sakti Gunawan Irianto Wahyu Tri Handoko Wardani, Adi Wahyu Wibawa, Aji P Wibisono Sukmo Wardhono, Wibisono Sukmo Widiyanti Widiyanti, Widiyanti Wiryawan, Muhammad Zaki Yana Andayani Yusril Imamuddin Zainul Falah, Moh.