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All Journal Jurnal Buana Informatika Jurnal Sarjana Teknik Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Formil (Forum Ilmiah) Kesmas Respati Building of Informatics, Technology and Science Buletin Ilmiah Sarjana Teknik Elektro Mobile and Forensics JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Shihatuna : Jurnal Pengabdian Kesehatan Masyarakat ADINDAMAS: Jurnal Pengabdian Kepada Masyarakat Jurnal AGRISEP: Kajian Masalah Sosial Ekonomi Pertanian dan Agribisnis
Nuril Anwar, Nuril
Program Studi Teknik Informatika Universitas Ahmad Dahlan Prof. Dr. Soepomo, S.H., Janturan, Umbulharjo, Yogyakarta 55164
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Electrical & Electronics Engineering Environmental Science Health Professions Library & Information Science Medicine & Pharmacology Neuroscience Nursing Public Health Social Sciences

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Geographic-Origin Music Classification from Numerical Audio Features: Integrating Unsupervised Clustering with Supervised Models Pranolo, Andri; Sularso, Sularso; Anwar, Nuril; Putra, Agung Bella Utama; Wibawa, Aji Prasetya; Saifullah, Shoffan; Dreżewski, Rafał; Nuryana, Zalik; Andi, Tri
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 4 (2025): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i4.13400

Abstract

Classifying the geographic origin of music is a relevant task in music information retrieval, yet most studies have focused on genre or style recognition rather than regional origin. This study evaluates Support Vector Machine (SVM) and Convolutional Neural Network (CNN) models on the UCI Geographical Origin of Music dataset (1,059 tracks from 33 non-Western regions) using numerical audio features. To incorporate latent structure, we first applied K-means clustering with the optimal number of clusters (k=2) determined by the Elbow and Silhouette methods. The cluster assignments were used as auxiliary signals for training, while evaluation relied on the true region labels. Classification performance was assessed with Accuracy, Precision, Recall, and F1-score. Results show that SVM achieved 99.53% accuracy (95% CI: 97.38–99.92%), while CNN reached 98.58% accuracy (95% CI: 95.92–99.52%); Precision, Recall, and F1 mirrored these values. The differences confirm SVM’s superior performance on this dataset, though the near-perfect scores also suggest strong separability in the feature space and potential risks of overfitting. Learning-curve analysis indicated stable training, and cluster supervision provided small but consistent benefits. Overall, SVM remains a reliable baseline for tabular music features, while CNNs may require spectro-temporal representations to leverage their full potential. Future work should validate these findings across multiple datasets, apply cross-validation with statistical significance testing, and explore hybrid deep models for broader generalization.
Design and Implementation of a Captive Portal Login System for Improved Network Security and User Access Management Kesumahadi, Lisdianto Dwi; Anwar, Nuril; Charlos, Feby; Setya, Bagus
Journal of Information System Research (JOSH) Vol 7 No 2 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i2.9082

Abstract

This study addresses network security issues and the suboptimal access time recording mechanism at the Informatics S1 Research Laboratory of Universitas Ahmad Dahlan. The research aims to design a hotspot system based on a Captive Portal, integrated with the existing MikroTik infrastructure, to enhance both security and efficiency. The study follows the Software Development Life Cycle (SDLC) methodology, encompassing the stages of requirements analysis, system design, implementation, testing, as well as operation and maintenance. Additionally, a Vulnerability Assessment is conducted to identify and address potential security weaknesses. The main objectives of this research include improving network security by preventing unauthorized access and data interception, as well as automating and accurately recording network usage duration for each user. The expected contribution of this work is the creation of a centralized authentication system that will optimize laboratory management and improve user experience. Preliminary results indicate a significant increase in network security and an efficient time-tracking mechanism, contributing to a 30% improvement in the lab's operational efficiency.
Co-Authors Abd. Rasyid Syamsuri Ahmad Azhari Ahmad Luthfi Aji Prasetya Wibawa Andri Pranolo Apik Rusdiarna Indra Praja Aretama, Lucky Barga Azmi, Muhammad Ilham Charlos, Feby Drezewski, Rafał Fauzi, Rachmad Nur Hafizh, Muhammad Naufal Imam Riadi Jalaludin Jalaludin Kesumahadi, Lisdianto Dwi Khoiriyah Isni Lazuardi, Risandio Ilham Lovandri Dwanda Putra, Lovandri Dwanda Murein Miksa Mardhia Murti, Raden Hario Wahyu Nur Rochmah Dyah Pujiastuti Nuraisyah, Fatma Nuryana, Zalik Prasetyo, Hamas Pratama, Krisna Dewa Putra, Agung Bella Utama Reswita Reswita, Reswita Rostika, Reni Ryanto, Luthfi Saifullah, Shoffan Sakirno, Muhammad Bayu Aji Satria Putra Utama Setya, Bagus Son Ali Akbar Sudianto, Iis Sularso Sularso, Sularso Suryanto, Imam Taufiq Ismail Tri Andi, Tri Yudistiawan, Ari Dimas Zain, Luthfi Amalia