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All Journal International Journal of Artificial Intelligence Research Djtechno: Jurnal Teknologi Informasi Jurnal Atma Inovasia Jurnal Pengabdian Masyarakat - Teknologi Digital Indonesia UPGRADE: Jurnal Pendidikan Teknologi Informasi
Dzul Fadli Rahman
Universitas Negeri Yogyakarta
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Environmental Science Social Sciences Other

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Machine Learning-Based Network Traffic Anomaly Detection Using the CIC-IDS2017 Dataset Nadhir Fachrul Rozam; Tika Novita Sari; Muhammad Resa Arif Yudianto; Dzul Fadli Rahman
Upgrade : Jurnal Pendidikan Teknologi Informasi Vol 3 No 2 (2026): Februari
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/upgrade.v3i2.6174

Abstract

The increasing volume and diversity of traffic in modern networks demand more adaptive intrusion detection approaches than traditional signature-based methods. This study aims to evaluate and compare the performance of several machine learning algorithms in detecting multi-class network traffic anomalies using the  CIC-IDS2017 dataset. The research process includes data cleaning and transformation,  class imbalance handling through random undersampling, and the implementation of five classification models: Logistic Regression, Gaussian NaïveBayes, Random Forest, K-Nearest Neighbors, and Support Vector Machine. Model performance is assessed using accuracy, precision, recall, and F1-score, supported by confusion matrix analysis and feature contribution evaluation. The results indicate that Random Forest achieves the best performance with an accuracy of 99.44% and consistently high evaluation metrics, while Gaussian Naïve Bayes shows the lowest performance. Furthermore, flow-based features are found to play a dominant role in improving classification accuracy, while misclassifications mainly occur among classes with similar traffic patterns. The findings highlight that selecting appropriate algorithms and applying effective preprocessing strategies are critical for developing more accurate and adaptive intrusion detection systems capable of addressing evolving cyber threats.
Prototype of IoT-Enabled RFID Door Lock System Using n8n Workflow Integration Ilmawan Mustaqim; Dzul Fadli Rahman; Heri Nurdiyanto; Abdul Khaliq Pangestu; Fauzi Wijaya
International Journal of Artificial Intelligence Research Vol 10, No 1 (2026): June
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v10i1.1733

Abstract

This study aims to develop a Radio Frequency Identification (RFID)-based door lock system integrated with the n8n automation platform as an innovative solution to enhance access security within an academic envi-ronment. The research employs a Research and Development (R&D) method with a Waterfall Model approach, consisting of requirement analysis, system design, hardware and software implementation, and prototype test-ing stages. The system utilizes an RFID RC522 module, an ESP8266 microcontroller, an I2C LCD, and a 12V Li-Ion battery, integrated through an n8n workflow to automatically record access data into an Excel data-base. The test results show that the system can perform user authentication and real-time access logging with 100% accuracy and an average response time of five seconds. The casing, printed using a 3D printer with PLA filament, provides a lightweight, durable, and easily assembled design. Overall, the developed system functions effectively as both a control and monitoring tool, demonstrating potential as a model for smart security system development in higher education institutions
Peningkatan Kompetensi Guru SMP Negeri 12 Yogyakarta dalam Membuat Bahan Ajar Digital dengan Canva Satriyo Agung Dewanto; Bekti Wulandari; Bonita Destiana; Agus Qomaruddin Munir; Muhammad Resa Arif Yudianto; Dzul Fadli Rahman; Ramadhana Setiyawan
Jurnal Atma Inovasia Vol. 6 No. 1 (2026)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jai.v6i1.12704

Abstract

Digital transformation requires teachers to be able to develop innovative and interactive teaching materials. However, limited competence in utilizing modern design platforms remains an obstacle at SMP Negeri 12 Yogyakarta. This community service program aims to improve teachers' skills in creating interactive digital teaching materials using the Canva platform. The method utilized was a hands-on workshop with a mixed-methods evaluation approach, including pre-tests, post-tests, product assessments, and feedback questionnaires. The evaluation results showed a significant increase in competence among all participants, as evidenced by a surge in post-test scores, the quality of teaching materials that were functional and visually appealing, and a very positive perception of the benefits and implementation of the training. It was concluded that this training was effective in equipping teachers with practical skills to transform themselves into producers of digital content relevant to 21st-century learning needs.
SEMANTIC WEB IMPLEMENTATION FOR ENHANCING BUDGET TRANSPARENCY IN YOGYAKARTA CITY GOVERNMENT: AN ONTOLOGY AND RDF-BASED FRAMEWORK Dzul Fadli Rahman; Ramadhana Setiyawan; Herjuna Artanto
Djtechno: Jurnal Teknologi Informasi Vol 6, No 3 (2025): Desember
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v6i3.7448

Abstract

Penerapan teknologi Semantic Web dalam pengelolaan data pemerintah menjadi strategi penting untuk meningkatkan transparansi dan keterbacaan mesin terhadap data terbuka. Penelitian ini bertujuan untuk mentransformasikan data Anggaran Murni Kota Yogyakarta tahun 2022 dari format tabular ke dalam representasi semantik menggunakan Resource Description Framework (RDF) dan Web Ontology Language (OWL). Ontologi dikembangkan dengan mendefinisikan lima kelas utama, yaitu Anggaran, Daerah, KategoriAnggaran, KelompokAnggaran, dan JenisAnggaran, serta dilengkapi dengan object property dan data property yang menggambarkan relasi dan atribut antarentitas. Representasi RDF kemudian diuji menggunakan beberapa query SPARQL untuk mengekstraksi informasi, seperti total anggaran, surplus atau defisit, dan identifikasi entitas tanpa alokasi. Visualisasi struktur ontologi dilakukan menggunakan plugin OWLViz untuk memastikan konsistensi logis antar kelas dan properti. Hasil penelitian menunjukkan bahwa model ontologi yang dikembangkan mampu merepresentasikan struktur anggaran secara terstruktur, konsisten, dan mendukung kueri semantik. Penelitian ini memberikan kontribusi terhadap upaya keterbukaan data pemerintah daerah dan dapat dikembangkan lebih lanjut untuk integrasi lintas wilayah serta visualisasi interaktif berbasis Web Semantik.
Pelatihan Literasi Digital untuk Meningkatkan Keterampilan Generative Artificial Intelligence Pekerja Migran Indonesia di Taiwan Ibnu Siswanto; Nur Hidayat; Pramudi Utomo; Fadhil Muhammad; Dzul Fadli Rahman; Akhmad Mujiburrokhman
Jurnal Pengabdian Masyarakat - Teknologi Digital Indonesia. Vol 5, No 1 (2026): Maret 2026
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jpm.v5i1.2164

Abstract

Pekerja Migran Indonesia (PMI) di Taiwan memiliki peran penting dalam ekonomi Indonesia. Akan tetapi PMI seringkali menghadapi tantangan maupun kendala yang salah satunya adalah kurangnya literasi tentang perkembangan teknologi digital. Hal tersebut dapat menjadi hambatan dalam mengakses peluang kerja maupun kewirausahaan. Kurangnya keterampilan dalam pemanfaatan kecerdasan buatan atau Artificial Intelligence (AI) semakin memperparah kesenjangan ini. Dengan demikian, upaya meningkatkan literasi digital menjadi langkah strategis untuk memberdayakan PMI, terutama dalam memahami regulasi dan membuka peluang usaha. Tim PkM Fakultas Teknik UNY berinisiatif mengadakan pelatihan literasi digital bagi PMI di Taiwan dengan tujuan untuk meningkatkan kemampuan generative artificial intelligence. Secara umum, PkM dilaksanakan melalui tahap: (1) perencanaan, (2) pelaksanaan, dan (3) evaluasi. Hasil pelatihan secara umum, peserta telah mengetahui keberadaan AI, hanya saja belum mampu untuk memaksimalkan kontribusinya. Salah satu hal yang disampaikan perwakilan peserta adalah adanya tindak lanjut dari pelatihan. Secara umum peserta merasa puas dengan pelatihan yang dilakukan. Peserta menyadari perlunya kemampuan untuk menguasai media sosial maupun generative AI. Selain itu, peserta berharap setelah adanya pelatihan ini, tim PkM masih mendampingi apabila terdapat pertanyaan maupun komunikasi terutama terkait dengan materi pelatihan.
Co-Authors Abdul Khaliq Pangestu Agus Qomaruddin Munir Akhmad Mujiburrokhman Bekti Wulandari Bonita Destiana Fadhil Muhammad Fauzi Wijaya Heri Nurdiyanto Herjuna Artanto Ibnu Siswanto Muhammad Resa Arif Yudianto Mustaqim, Ilmawan Nadhir Fachrul Rozam Nur Hidayat Pramudi Utomo Ramadhana Setiyawan Satriyo Agung Dewanto Tika Novita Sari