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All Journal Dinamik Techno.Com: Jurnal Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Prosiding SNATIF JAIS (Journal of Applied Intelligent System) Proceeding SENDI_U Jurnal Informatika Upgris Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control CCIT (Creative Communication and Innovative Technology) Journal Jurnal SITECH : Sistem Informasi dan Teknologi Building of Informatics, Technology and Science Jurnal Mantik Jurnal Informatika dan Rekayasa Perangkat Lunak Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Pengabdian, Pendidikan dan Teknologi Jurnal Teknik Informatika (JUTIF) Jurnal Program Kemitraan dan Pengabdian Kepada Masyarakat Jurnal Pendidikan dan Teknologi Indonesia Jurnal Citrakara Prosiding Seminar Nasional Hasil-hasil Penelitian dan Pengabdian Pada Masyarakat Seminar Nasional Teknologi dan Multidisiplin Ilmu Scientific Journal of Informatics INOVTEK Polbeng - Seri Informatika Palawa Jurnal Pengabdian Kepada Masyarakat
Elkaf Rahmawan Pramudya
Universitas Dian Nuswantoro
Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Physics Public Health Social Sciences Other

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Deteksi Malware Android Berbasis Ensemble Soft Voting LightGBM, Logistic Regression dan CatBoost Ardian Danendra; Elkaf Rahmawan Pramudya
Building of Informatics, Technology and Science (BITS) Vol 7 No 4 (2026): March 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i4.8865

Abstract

The Android operating system faces serious challenges with increasingly complex and diverse malware evolution. This research proposes an Android malware detection system based on soft voting ensemble that integrates three algorithms (LightGBM, Logistic Regression, and CatBoost) to improve detection accuracy while maintaining computational efficiency. The dataset used is CCCS-CIC-AndMal-2020, which is highly imbalanced with over 400,000 Android application samples. The proposed model leverages hybrid features that combine static information (permissions, intents, API calls from the AndroidManifest) with dynamic behavior (memory activities, runtime API calls, logcat, and network traffic in an emulated environment), balancing low extraction cost with improved robustness against obfuscation. The methodology includes multi-stage preprocessing (IQR capping 40×, StandardScaler, RFE 150 features, SMOTE 30%) to improve data quality and reduce dimensionality by 56% without losing important information. The ensemble model is trained with F1-Macro-based weights (33.46% LightGBM, 30.99% Logistic Regression, 35.55% CatBoost) approximating 1:1:1 proportion. Evaluation results on the testing set demonstrate very high performance: Accuracy 95.58%, Balanced Accuracy 92.21%, F1-Macro 0.9208, True Positive Rate 100%, and False Alarm Rate 0.00%. The combination of these metrics indicates that the model can detect all malware samples without false positives on benign applications, making it suitable for production deployment. This research contributes by demonstrating the effectiveness of an efficient soft voting ensemble (only 3 models) for Android malware detection with multi-dimensional evaluation metrics representative of imbalanced data.
Implementasi Deep Learning Berbasis MobileNetV2 untuk Deteksi Real-Time Bacterial Spot dengan Pendekatan Arsitektur Lightweight Ahmad Nabilul As'ad; Elkaf Rahmawan Pramudya
Building of Informatics, Technology and Science (BITS) Vol 7 No 4 (2026): March 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i4.9252

Abstract

Bacterial spot caused by Xanthomonas campestris pv. vesicatoria is a critical disease in bell peppers that can reduce productivity by up to 50%. This study implements MobileNetV2 with two-stage transfer learning for real-time bacterial spot detection using lightweight architecture approach, with ResNet50 as baseline comparison. PlantVillage dataset (2,475 images) was used for training and in-domain evaluation, while India dataset (132 images) for domain shift assessment. Results demonstrate MobileNetV2 achieves 98.66% accuracy on PlantVillage test set, outperforming ResNet50 (89.78%) by 8.88 percentage points despite being 9.2× lighter (2.7 MB vs 24.3 MB TFLite) and 2.0× faster (22.4 ms vs 45.8 ms inference time). MobileNetV2 efficiency advantage is also evident in its inference memory footprint of only 107 MB RAM, significantly 2.3x lower than ResNet50(242 MB RAM), making it highly suitable for deployment on mid-range smartphones with limited RAM. External dataset evaluation reveals MobileNetV2 maintains superior robustness with 65.3% retention rate versus ResNet50's 52.3%. Trade-off analysis positions MobileNetV2 on the Pareto frontier, achieving optimal accuracy-efficiency sweet spot for plant disease detection applications. This research contributes empirical evidence for lightweight architecture superiority, comprehensive efficiency-oriented evaluation framework, ULTRA-LIGHT training strategy for addressing inverse overfitting, and realistic generalization assessment using tropical external dataset.
Co-Authors ., Muslih Abdussalam Abdussalam Abdussalam Abdussalam Abdussalam Abdussalam, Abdussalam Abi Senoprabowo Ahmad Nabilul As'ad Ajib Susanto Akhmad Rizaldy Ali Muqoddas ALI MUQODDAS Annahdli, Zacky Fahd Ardian Danendra Ari Yahya A Arief Soeleman Aris Marjuni Arry Maulana Syarif Aufa Fadholi Suharyoto Briliantino Abhista Prabandanu Budi Harjo Cahaya Jatmoko Christy Atika Sari De Rosal Ignatius Moses Setiadi Doheir, Mohamed Dwi Puji Prabowo, Dwi Puji Edi Faisal Edi Sugiarto Eko Hari Rachmawanto Erna Zuni Astuti Erwin Yudi Hidayat Farrel Athaillah Putra Fikri Budiman Folasade Olubusola Isinkaye Gilang Raharjito Guruh Fajar Shidik Henry Bastian Henry Bastian, Henry Ibnu Utomo Wahyu Mulyono Khafiidz Hastuti Khafiizh Hastuti L. Budi Handoko Luqman Abdul Malik Mega Bintang Hatmi Moch Arief Soeleman Moch. Arief Soeleman Muslih - Muslih - Muslih Muslih Muslih Muslih Muslih Muslih Naufal Rizky Ramadhan Noor Hasyim Noor Hasyim Noor Hasyim Novia Wahyu W. Nugraha, Arifinza Eska Nugraini, Siti Hadiati Oki Setiono Pratama, Zudha Pulung Nurtantio Andono Puri Sulistiyawati Ramadhan Rakhmat Sani Rico Rian Alvian S Nurhendratno Sarker, Md. Kamruzzaman Sarwadi Sarwadi Sinaga, Daurat Soeleman, Arief Soeleman, M. Arief Supriyono Asfawi Viky Luffiandi Rismawan Viky Luffiandi Rismawan Widyatmoko Karis Wildanil Ghozi