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All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING
Asrianda Asrianda
Program Studi Magister Teknologi Informasi, Universitas Malikussaleh
Computer Science & IT

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Evaluation of Support Vector Machines and Adaptive Boosting in Classifying the Compliance Levels of Property and Building Taxpayers Using Receiver Operating Characteristic (ROC) Saumina Saumina; Munirul Ula; Asrianda Asrianda
Journal of Applied Informatics and Computing Vol. 10 No. 4 (2026): August 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i4.13643

Abstract

Taxpayer compliance is a critical factor in increasing Property Tax (PBB) revenue. A low level of compliance can reduce local government revenue, making accurate classification methods essential for identifying taxpayer compliance. This study aims to compare the performance of Support Vector Machine (SVM) and Adaptive Boosting (AdaBoost) in classifying property taxpayer compliance. The dataset consisted of 58,998 property tax records collected from Lhokseumawe City, covering the districts of Banda Sakti, Blang Mangat, Muara Dua, and Muara Satu. The research stages included data preprocessing, label encoding, Min–Max normalization, data splitting using 80:20 and 70:30 scenarios, model training, and performance evaluation using accuracy, precision, recall, F1-score, and Area Under the Curve (AUC). Under the 80:20 data split, SVM achieved an accuracy of 92.89%, precision of 93.12%, recall of 98.81%, F1-score of 95.87%, and AUC of 80.59%, while AdaBoost achieved an accuracy of 92.86%, precision of 93.11%, recall of 98.78%, F1-score of 95.86%, and AUC of 80.76%. Under the 70:30 data split, SVM achieved an accuracy of 93.02%, precision of 93.18%, recall of 98.90%, F1-score of 95.95%, and AUC of 80.32%, whereas AdaBoost achieved an accuracy of 92.99%, precision of 93.18%, recall of 98.87%, F1-score of 95.93%, and AUC of 80.97%. Overall, both methods demonstrated comparable classification performance, while AdaBoost exhibited slightly better discriminative capability based on the AUC values.
Performance Comparison of Point-to-Point and Point-to-Multipoint Fiber Optic Networks Using QoS Parameters and the Analytical Hierarchy Process (AHP) Husni Husni; Taufiq Taufiq; Defry Hamdhana; Muhammad Daud; Asrianda Asrianda
Journal of Applied Informatics and Computing Vol. 10 No. 4 (2026): August 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i4.13728

Abstract

The rapid growth of internet traffic in Indonesia, including in Aceh Province, requires an optical fiber network infrastructure that is both efficient and reliable. Two fundamental architectures, Point-to-Point (P2P) and Point-to-Multipoint (P2MP), offer different trade-offs between service quality and cost efficiency, yet a quantitative comparison that combines Quality of Service (QoS) measurement with a structured multi-criteria decision-making method remains limited. This study experimentally measures the throughput, delay, jitter, packet loss, and bandwidth of P2P and P2MP networks implemented at Universitas Almuslim, Bireuen, Aceh, using iPerf3 and Wireshark under varying client loads of 1, 2, 4, 8, and 16 users, and applies the Analytical Hierarchy Process (AHP) to weight the QoS criteria and rank the two architectures. The results show that P2P consistently outperforms P2MP on every QoS parameter, maintaining an average throughput of 95 Mbps, a delay of 2.68 ms, a jitter of 0.85 ms, a packet loss of 0.054%, and a fixed bandwidth of 100 Mbps, whereas P2MP degrades progressively as the number of users increases. AHP weighting identified throughput as the most influential criterion (0.50), followed by bandwidth (0.26), delay (0.13), jitter (0.07), and packet loss (0.03), with a Consistency Ratio of 0.054, confirming that the pairwise judgments were consistent. The resulting AHP scores were 9.00 for P2P and 2.66 for P2MP, indicating that P2P is the more optimal architecture for QoS-sensitive deployments, while P2MP remains advantageous where cost efficiency and wide coverage are prioritized.
Co-Authors Defry Hamdhana Husni Husni Muhammad Daud Munirul Ula Saumina Saumina Taufiq Taufiq