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All Journal INFORMAL: Informatics Journal SMATIKA PINTER : Jurnal Pendidikan Teknik Informatika dan Komputer Jurnal Manajemen Informatika dan Sistem Informasi Jurnal Informatika dan Rekayasa Elektronik REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Brilliance: Research of Artificial Intelligence Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Pengabdian Masyarakat Bidang Sosial dan Humaniora Jurnal Pengabdian Masyarakat Sains dan Teknologi Jurnal ELTEK Recent in Engineering Science and Technology PANDALUNGAN : Jurnal Pengabdian kepada Masyarakat
Dwi Wijonarko
Universitas Jember
Religion Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Other

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Harmoni Multikultural: Membangun Kebersamaan di Tengah Perbedaan untuk Kaum Milenial Katarina Leba; Balthasar Watunglawar; Muhammad ‘Ariful Furqon; Dwi Wijonarko
ABDISOSHUM: Jurnal Pengabdian Masyarakat Bidang Sosial dan Humaniora Vol. 3 No. 4 (2024): Desember 2024
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/abdisoshum.v3i4.4217

Abstract

This community service activity is conducted through a religious seminar to strengthen the understanding and implementation of diversity values among young generations. The seminar is designed to respond to the increasing challenges of societal polarisation and intolerance, especially among millennials. Through a series of interactive sessions, participants are invited to explore the concept of multicultural harmony from a religious perspective, emphasizing universal values such as compassion, empathy, and mutual respect. The seminar material covers discussions on the role of religion in promoting peace, strategies to overcome inter-group prejudices and stereotypes, and best practices in building interfaith dialogue. The seminar also addresses the role of technology and social media in facilitating positive interactions between cultures and religions. It is hoped that through this activity, millennials can become active agents of change in building a harmonious and inclusive society while respecting the uniqueness of each cultural identity. Post-seminar evaluations show increased participants' understanding of the importance of togetherness in diversity and a commitment to apply the values of multicultural harmony in daily life.
Deteksi Berita Hoaks Berbahasa Indonesia Menggunakan One-Dimensional Convolutional Neural Network Muhammad Zuama Al Amin; Muhammad Ariful Furqon; Dwi Wijonarko
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 14 No 2: Mei 2025
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v14i2.19050

Abstract

The rapid advancement of information technology has enabled global information dissemination and led to a surge in hoax news, particularly in Indonesia. Hoax news poses a significant risk of spreading disinformation, potentially influencing public opinion, social stability, and security. Therefore, an effective technology-based solution is required to detect and identify hoaxes. This study aims to develop and optimize a one-dimensional convolutional neural network (1D-CNN) model to detect hoax news with high accuracy. The dataset comprised 12,151 articles, including 5,276 valid news items and 6,875 hoax news items, collected from reliable sources and anti-hoax platforms. The text preprocessing stages included data cleaning, case folding, punctuation removal, number removal, and stopword removal. The textual data were processed through tokenization and padding stages for model training preparation. The proposed 1D-CNN architecture integrated embedding, Conv1D, batch normalization, globalmaxpooling1d, dense, and dropout layers to enhance generalization capabilities and reduce the risk of overfitting. The model was trained using the Adam optimizer and its performance was evaluated using 10-fold cross-validation. Experimental results showed that the model achieved an average accuracy, precision, recall, and F1 score of 97.74%, 97.75%, 97.74%, and 97.73%, respectively. The developed model outperformed previous methods, namely the convolutional neural network–bidirectional long short-term memory (CNN-BiLSTM), gated recurrent unit (GRU), and conventional methods such as naïve Bayes or support vector machine (SVM), in terms of accuracy and training efficiency. This study demonstrates that the model has a reliable capability in identifying hoax news, both in terms of detection accuracy and performance consistency.
Implementation of YOLO in Cabbage Plant Disease Detection for Smart and Sustainable Agriculture Saputra, Muhammad Andryan Wahyu; Novtahaning, Damar; Narandha Arya Ranggianto; Dwi Wijonarko
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.5054

Abstract

Cabbage plants are a commodity needed by the community and an export commodity that must have good quality and be worth selling. There are approaches to create detection systems, namely rule-based and image-based. The use of images allows the system to be reorganized by training data, resulting in a flexible system. The image will be detected by the model and then predict the cabbage plant disease. The data used is image data, namely Alternaria Spots, Healthy, Black Root, and White Rust. Implementation This research tests the YOLO model in making a detection system with the highest precision-confidence result for all labels is 78,5%. While in confusion-matrix testing, the highest result is 0.67 in White Rust disease. This indicates that the YOLO model can identify diseases in cabbage plants based on data that has been trained with great results.
Procedural Content Generation pada Level Gim Sokoban Menggunakan Model Hybrid GPT2 dan Algoritma Genetika Narandha Arya Ranggianto; Akbar Pandu Segara; Dwi Wijonarko; Anang Andrianto; M. Habibullah Arief
REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer Vol. 9 No. 3 (2025): Volume 9 Nomor 3 Agustus 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/remik.v9i3.15188

Abstract

Procedural Content Generation (PCG) yang berfokus pada level menjadi poin penting dalam mempengaruhi pengalaman pengguna dalam bermain gim. Salah satu gim puzzle khususnya Sokoban dapat diterapkan untuk pembangunan level secara otomatis karena dapat direpresentasikan secara sederhana. Dataset Sokoban biasanya direpresentasikan ke dalam string ASCII yang terdiri dari pemain (@), dinding (#), kotak ($), dan tujuan (.). Hal ini menjadikan level Sokoban dapat dikembangkan menggunakan dua pendekatan yaitu berbasis pencarian dan machine learning. Metode pencarian memiliki kelebihan dalam mengeksplorasi sebuah level yang playable namun menghasilkan level yang sama. Sedangkan pada pendekatan machine learning data digunakan untuk melakukan training dengan pola-pola tertentu sehingga memberikan kemampuan membangun level yang bervariatif. Kekurangan data dalam level gim menjadikan pendekatan fine-tuning GPT2 lebih unggul untuk digunakan dalam pembangunan level. Namun, karakteristik data yang tidak memiliki koherensi yang baik pada level Sokoban menjadikan GPT2 tidak dapat membangun level yang playable. Model Hybrid GPT2 dan Algoritma Genetika (GPT2-GA) dimana nilai penggabungan ini akan memberikan hasil yang optimal. Evaluasi untuk mengukur accuracy, playability, dan diversity yang menunjukkan performa lebih unggul dibandingkan GPT2. Model GPT2-GA menunjukkan hasil peningkatan accuracy dari 81,9% menjadi 90,1%, playability dari 41,3% menjadi 62,8%, dan diversity dari 88,2% menjadi 97,5%. Pendekatan model ini berhasil mengatasi kelemahan model generatif GPT2 dalam menghasilkan level yang fungsional dengan mempertahankan level yang unik yang dapat diselesaikan.
Mobile Ad-Hoc Network (MANET) Method: Some Trends and Open Issues Dwi Wijonarko; Samsul Arifin; Muhammad Faisal; Muhammad Nabil Pratama; Okta Nindita Priambodo; Edwin Setiawan Nugraha
Recent in Engineering Science and Technology Vol. 3 No. 2 (2025): RiESTech Vol. 3 No. 2 Years 2025
Publisher : MBI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59511/riestech.v3i2.108

Abstract

This study analyzes the latest developments and trends in the field of Mobile Ad-Hoc Networks (MANET) through a bibliometric approach using a metadata dataset from publications taken from Scopus between 2021 and 2024. By utilizing VOSviewer to visualize the data, the study identified key keywords that dominated the MANET literature, such as "security", "routing protocols", "mobility", and "5G". The visualization results show several important clusters, including topics related to network security, vehicle networks (VANET), and the application of advanced technologies such as machine learning in network management. Despite the decline in the number of publications in 2023 and 2024, collaboration between authors continues to show a strong trend. The research also highlights various challenges that are still open problems, such as the development of efficient routing protocols, improving network security, and managing resources in a dynamic MANET environment. In addition to the VOSviewer analysis, further exploration was carried out using the built-in visualization tools from the Scopus web platform to enrich the interpretation of emerging topics and research connections. This was followed by a deeper conceptual mapping using Scopus AI, which provided a visual breakdown of interconnected themes such as security issues, routing protocols, and different network types like VANET and FANET. To complement and validate the findings, the study also incorporated evidence based summaries retrieved from Consensus.app, offering additional insights from AI-driven scientific consensus. This multi-platform approach enhances the reliability of the analysis and provides a more comprehensive view of current and future research directions in the MANET domain.
PENGEMBANGAN APLIKASI MOBILE MANAJEMEN SERVIS KENDARAAN OFFLINE MENGGUNAKAN METODE WATERFALL DI BENGKEL ADIT GARAGE Mohammad Zarkasi; Gama Wisnu Fajarianto; Yudha Alif Auliya; Dwi Wijonarko Wijonarko; Priza Pandunata
PINTER : Jurnal Pendidikan Teknik Informatika dan Komputer Vol. 10 No. 1 (2026): Jurnal PINTER
Publisher : PTIK Fakultas Teknik UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/pinter.10.1.4

Abstract

The management of motor vehicle data, such as service history, fuel consumption, and tax administration, is still done manually in many workshops, which risks causing data loss, recording errors, and irregularities in vehicle maintenance monitoring. This condition indicates the need for a digital system that can help customers and workshop staff manage vehicle information in a more structured and easily accessible manner. This research aims to develop an Offline Vehicle Service Management Mobile Application as a digital solution to support vehicle data management at Adit Garage Workshop. The application development uses the Waterfall method within the Software Development Life Cycle (SDLC) framework, which includes the stages of requirements analysis, system design, implementation, and testing. The application is developed using the Flutter framework and designed to operate fully offline without relying on an API or backend server, so vehicle data can still be managed when an internet connection is not available. The main features developed include recording vehicle identities, digitizing service histories, recording fuel consumption, and reminders for vehicle tax and Vehicle Registration Certificate (STNK) expiration. The development results show that the application is capable of integrating various vehicle maintenance information into a simple and user-friendly mobile platform. Testing using the Black Box Testing method shows that all tested features can operate according to their designed functions without any functional errors found. The implementation of the application also provides ease in recording, searching, and monitoring vehicle information for both customers and workshop personnel. Thus, the developed application can serve as an efficient digital solution to support the management and monitoring of vehicle maintenance, especially in workshop environments that require a system capable of operating without an internet connection.
Co-Authors Afif, Hasnan Akbar Pandu Segara Anang Andrianto Anang Andrianto Balthasar Watunglawar Betta Wahyu Retna Mulya Betta Wahyu Retna Mulya Betta Wahyu RM Damar Novtahaning Edwin Setiawan Nugraha Fajar Wahyu Setyo Budi Firdaus, Ananda Dwi Furqon, Muhammad Ariful Gama Wisnu Fajarianto Ginting, Sonia Br Harry Soepandi Katarina Leba Linda, Kumala M. Habibullah Arief Mohammad Zarkasi Muhammad Andryan Wahyu Saputra Muhammad Faisal Muhammad Nabil Pratama Muhammad Zuama Al Amin Mutasyakir, Cahya Rahmadhan Narandha Arya Ranggianto Priambodo, Oktanindita Priza Pandunata Rizal Fathoni Aji RM, Betta Wahyu Samsul Arifin Talitha, Azzura Yudha Alif Auliya