Article Per Year (5 Year)
p-Index From 2021 - 2026
4.406
P-Index
This Author published in this journals
All Journal Jurnal Pendidikan Teknologi dan Kejuruan MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Prosiding Seminas Competitive Advantage Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Kursor Register: Jurnal Ilmiah Teknologi Sistem Informasi Journal of Development Research JOIV : International Journal on Informatics Visualization Applied Information System and Management IJISTECH (International Journal Of Information System & Technology) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Systemic: Information System and Informatics Journal ILKOMNIKA: Journal of Computer Science and Applied Informatics Jurnal Mnemonic International Journal of Advances in Data and Information Systems IJISTECH Jurnal Indonesia : Manajemen Informatika dan Komunikasi Jurnal Janitra Informatika dan Sistem Informasi SinarFe7 Bulletin of Social Informatics Theory and Application Jurnal Indonesia : Manajemen Informatika dan Komunikasi al-Balagh : Jurnal Dakwah dan Komunikasi International Journal of Electrical and Intelligent Engineering
Yunifa Miftachul Arif
Department Of Informatics Engineering, Universitas Islam Negeri Maulana Malik Ibrahim Malang
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

Published : 45 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 45 Documents
Search

 1   2   3   4   5 
Sistem Rekomendasi Destinasi Wisata Menggunakan Data Demografis Berbasis Klasifikasi Support Vector Machine A'yun, Aldilla Qurrata; Arif, Yunifa Miftachul; ., Muhammad Imamudin
ILKOMNIKA Vol 7 No 3 (2025): Volume 7, Number 3, December 2025
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/ilkomnika.v7i3.826

Abstract

Penelitian ini bertujuan untuk mengembangkan sistem rekomendasi destinasi wisata berbasis data demografis menggunakan metode klasifikasi Support Vector Machine (SVM). Sistem dirancang untuk memberikan rekomendasi destinasi yang sesuai dengan karakteristik wisatawan, seperti usia, jenis kelamin, dan status sosial. Dataset yang digunakan terdiri dari sepuluh variabel demografis dan empat belas kategori destinasi wisata. Analisis awal menunjukkan bahwa dataset memiliki ketidakseimbangan kelas yang sangat tinggi, dengan kelas Jatim Park 1 mendominasi lebih dari separuh data sementara banyak kelas lain hanya memiliki 1–6 sampel. Untuk mengurangi dampak ketidakseimbangan ini, dilakukan teknik oversampling pada data training. Model SVM kemudian dilatih menggunakan beberapa kombinasi parameter dan kernel, serta diuji menggunakan metrik akurasi, precision, recall, dan F1-score. Hasil eksperimen menunjukkan bahwa pada data training yang sudah diseimbangkan, performa model meningkat signifikan, ditunjukkan oleh nilai F1-macro pada cross-validation sebesar 0.84. Namun, ketika diuji pada data testing yang mencerminkan kondisi distribusi asli, performa model menurun, dengan akurasi sebesar 54% dan nilai F1-macro yang rendah pada sebagian besar kelas minoritas. Temuan ini menunjukkan bahwa meskipun SVM efektif pada data yang seimbang, performanya masih belum optimal pada dataset rekomendasi wisata yang sangat timpang. Penelitian ini merekomendasikan pengayaan data, terutama untuk kelas-kelas minoritas, serta eksplorasi metode penanganan ketidakseimbangan kelas lainnya pada penelitian lanjutan.
DIGITAL DA'WAH AND THE RECONSTRUCTION OF ISLAMIC AUTHORITY A’lan Tabaika, Mokhammad; Barizi, Ahmad; Arif, Yunifa Miftachul
al-Balagh : Jurnal Dakwah dan Komunikasi Vol. 10 No. 2 (2025): December 2025
Publisher : Fakultas Ushuluddin dan Dakwah UIN Raden Mas Said Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22515/albalagh.v10i2.12116

Abstract

This study addresses the research gap regarding how Islamic authority is contested and reconstructed in the era of digital media, where social media dynamics disrupt traditional hierarchies. It aims to analyze how online Islamic preaching is transformed by social media logics, aesthetic strategies, and audience engagement, emphasizing the participatory and dialogical nature of comment sections. This research adopts a qualitative design using a netnographic approach, observing and analyzing social media content produced by prominent Indonesian Islamic figures, including Hanan Attaki, Abdul Somad, and Habib Husein Ja’far. The dataset comprises YouTube sermons, Instagram posts, TikTok videos, and user interactions, including comments and shares. Findings reveal the emergence of "religious influencers" who blend piety with branding, the commodification of Islamic preaching, and the evolution of comment sections into semi-public arenas of theological debate and negotiation. These interactions show how authority is no longer solely institutional but co-produced with audiences in real time. This study demonstrates that digital da’wah democratizes access to religious discourse while raising concerns about theological integrity, commercialization, and regulation challenges. It argues that understanding these dynamics is essential for developing critical digital religious literacy and fostering more inclusive, reflective, and ethically grounded online Islamic communication.
Deepfake Image Detection Using Transfer Learning Method Tsalatsatun Nur Rohmah; Dewi Purnamasari; Kurniawati Kurniawati; Didin Herlinudinkhaji; Yunifa Miftachul Arif; Santiago Criollo-C
International Journal of Electrical and Intelligent Engineering Vol 1, No 2 (2025)
Publisher : Department of Electrical Engineering Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ijeie.v1i2.40796

Abstract

The development of Artificial Intelligence (AI) technologies, particularly deep learning has led to the emergence of innovative applications such as deepfake technology, which enables the realistic manipulation of digital images and videos. While this technology offers positive applications in fields such as entertainment and education, it also poses significant risks of misuse, particularly in the dissemination of false information and violations of privacy. Therefore, deepfake detection has become a crucial aspect in preserving the authenticity of digital content. This study aims to analyze the effectiveness of transfer learning methods in detecting deepfake images using VGG16, VGG19, and ResNet50 architectures. The research employs a dataset of deepfake and real images sourced from Kaggle, comprising 10,826 facial images with a resolution of 256 × 256 pixels, evenly balanced between authentic and manipulated content. The data are split in an 80:20 ratio for training and testing purposes. Each model is trained using identical parameter configurations. The performance evaluation of the models was conducted using confusion matrix metrics, including accuracy, precision, recall, and F1-score. The results indicate that the VGG16 model achieved the best performance, with an accuracy of 76%, followed by VGG19 at 72%, and ResNet50 at 58%. VGG16 also outperformed the other models in terms of precision, recall, and F1-score, demonstrating more effective performance in identifying visual manipulation patterns. In contrast, ResNet50 exhibited the lowest performance, which may be attributed to its architectural complexity not being optimally aligned with the characteristics of the dataset. It can be concluded that the transfer learning approach using the VGG16 model is more effective in detecting deepfake images on this dataset. This study also highlights the importance of selecting appropriate architectures and fine-tuning models to the characteristics of the data.
Ball Detection in Wheeled Soccer Robot Using the YOLOv8 Model Aqza Tri Ananda HAT; Shoffin Nahwa Utama; M. Imamudin; Yunifa Miftachul Arif; Ajib Hanani
International Journal of Electrical and Intelligent Engineering Vol 1, No 2 (2025)
Publisher : Department of Electrical Engineering Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ijeie.v1i2.39317

Abstract

This research designs and builds a wheeled soccer robot using YOLOv8 for real-time ball detection and distance estimation, aiming to improve efficiency in technology competitions. The system includes Arduino Uno R3, Raspberry Pi 3 model b, detection system, and navigation design. 691 ball image use as dataset that consist of 552 image as training dataset and 249 image as valid dataset. YOLOv8 demonstrated exceptional reliability in ball detection during testing, achieving an average accuracy of 100%, 100% precision, and 94% recall. Navigation testing toward the ball had an acceptable average error of 8.0466%. The results confirm that YOLOv8 is excellent for simplifying high-accuracy ball detection and distance estimation in wheeled soccer robots. Future work should consider a higher-spec Raspberry Pi, a high-resolution camera, additional sensors, and advanced systems to improve detection and obstacle avoidance (opponent robots, goal).
Career Path Mapping Using the Random Forest Method for Vocational High School Graduates Imami, Nia Kurniawati; Hariyadi, Mokhamad Amin; Arif, Yunifa Miftachul
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 4 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i4.9297

Abstract

Vocational high school students are prepared to enter the labor market. However, field facts show that many graduates work outside their field of expertise. To address this, the special job placement bureau (Bursa Kerja Khusus/BKK) plays an important role as it connects graduates with industry. In addition, BKK provides pre-employment training such as interview preparation and soft-skill development. This study aims to develop a classification-based career-path mapping system integrated with BKK functions. The data used are scores of eight competency dimensions for vocational students obtained from BKK. The method employed is the Random Forest algorithm. We conduct hyperparameter tuning with cross-validation. Results show Random Forest achieves accuracy of 0.895 and an F1 score of 0.905. These results indicate that optimizing for F1 yields the best balance between precision and recall while maintaining high overall accuracy. Overall, this study confirms a trade-off between overall accuracy and inter-class balance (F1): constrained tree depth tends to maximize accuracy, whereas unconstrained depth benefits F1. Random Forest proves reliable and stable for the classification task in this career-path mapping
Co-Authors ., Muhammad Imamudin A'yun, Aldilla Qurrata AA Sudharmawan, AA Achmad Sabar, Achmad Ady Wicaksono Agariadne Dwinggo Samala Ahmad Barizi Ahmad Fahmi Karami Ajib Hanani Alfachruddin, M. Nabil Fahd Alfia, Lia Alfia Aqza Tri Ananda HAT Aristantia, Yuliana Aziza, Miladina Rizka A’lan Tabaika, Mokhammad Bojic, Ljubisa Cahyo Crysdian Coelho, Diogo Pereira Dedy Kurnia Setiawan Dewi Purnamasari Diah, Norizan Mat Didin Herlinudinkhaji, Didin Duvan Deswantara Putra Dyah Wardani Fachrul Kurniawan Fathir Fathir Fathir Fathurrahman Firmansyah, Rezky Fresy Nugroho Hamid, Abdulhalim Hamid Salih Hani Nurhayati Howard, Natalie-Jane Ihsan, Afif Nuril Ikhlayel, Mohammed Imami, Nia Kurniawati Imamudin, M. Janitra, Geovanni Azam Juniardi Nur Fadila Junikhah, Allin Khadijah Fahmi Hayati Holle Khan, Nauman Kurniawati Kurniawati Linda Salma Angreani M. Imamudin Mauludiah, Siska Farizah Mauridhi H Purnomo Mochamad Hariadi Mochammad Wahyu Firmansyah Mokhamad Amin Hariyadi Muhammad Faisal Muhammad Faisal Muhammad Sahi Mustofa, Ahmad Habibil Nadhifah, Rizqi Aulia Nauman Khan Norizan Mat Diah Novrindah Alvi Hasanah Putra, Dony Darmawan Putra, Duvan Deswantara Rawas, Soha Ririen Kusumawati Rizqi Aulia Nadhifah Rohma, Salma Ainur Rony, Zahara Tussoleha Roro Inda Melani Safitri A Basid, Puspa Miladin Nuraida Sahi, Muhammad Santiago Criollo-C Setiyawan, Niko Heri Shoffin Nahwa Utama Sulika Sulika Supeno Mardi S. N, Supeno Mardi Supeno Mardi Susiki Nugroho, Supeno Mardi Supriyono Tarranita Kusumadewi Tsalatsatun Nur Rohmah Tsoy, Dana Wahyuliningtyas, Lia Wardani, Dyah Wibowo, Muhammad Ismail Arjun Zainal Abidin Zulfiandri Zulfiandri