Implementation of Decision Support System for Illegal Cosmetic Detection in Papua Based Machine Learning
Keywords:
Decision Support System, Predicitive Analytics, Regulatory Enforcement, Illegal Cosmetics, Papua Special Autonomy
Abstract
Regulatory enforcement against illicit cosmetics in the Papua Special Autonomy regions remains constrained by profound geographical complexity and systemic data fragmentation. This study develops a robust Decision Support System (DSS) that bridges the gap between digital surveillance and legal accountability at BBPOM in Jayapura. By integrating the Simple Multi-Attribute Rating Technique (SMART) with a hybrid machine learning framework, the system operationalizes parameters derived from the Indonesian Health Law (No. 17 of 2023) and the Papua Special Autonomy Law (No. 2 of 2021). A high-fidelity dataset of 1,324 multi-source inspection records was utilized to train a hybrid ensemble architecture. Empirical results demonstrate that the Artificial Neural Network (ANN) achieves near-optimal performance, yielding a 99.62% accuracy and 99.90% F1-score, with a marginal error rate of 0.38%. The inclusion of PostGIS-driven spatial intelligence further enables real-time vulnerability mapping within a scalable Service-Oriented Architecture (SOA). Beyond its technical efficacy, this research contributes a novel paradigm for localized law enforcement, successfully unifying regional regulatory mandates with advanced predictive analytics to safeguard public health in marginalized frontiers.
References
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Bousmaha, R., Hamou, R. M., & Amine, A. (2022). Optimizing Connection Weights in Neural Networks Using Hybrid Metaheuristics Algorithms. International Journal of Information Retrieval Research, 12(1), 1–21. https://doi.org/10.4018/ijirr.289569
Buloto, A. V., Puluhulawa, F. U., Rahmah, A., Mantali, Y., & Artikel, I. (2025). PENGUATAN REGULASI DAN PENEGAKAN HUKUM TERHADAP PEREDARAN KOSMETIK ILEGAL DI INDONESIA DAN SINGAPURA. SINERGI : Jurnal Riset Ilmiah, 2(2), 691–703. https://doi.org/10.62335/sinergi.v2i2.889
Effendy, R. G. (2023). Analisis Otonomi Khusus Papua Dalam Perspektif Orang Asli Papua. Binamulia Hukum, 12(2), 309–322. https://doi.org/10.37893/jbh.v12i2.436
Mankotia, S., Leon, D. C. De, & Jamil, H. M. (2026). ReactSmart: ML-Driven Adaptation for Scalable React-Based Web Application Performance. IEEE Access. https://doi.org/10.1109/ACCESS.2026.3650873
Meiana, E. P., Vernanda, A. L., Kartika, I. M., & Kuncoro, D. K. (2026). ASPEK HUKUM BISNIS DALAM PENJUALAN PRODUK SKINCARE ILEGAL DI INDONESIA. Prosiding Seminar Nasional Hukum, Bisnis, Sains Dan Teknologi, 6(1), 201–209. https://www.ojs.udb.ac.id/HUBISINTEK/article/view/5863
Oktaviani, F., Elmi, I., Pelu, A. S., Baihaki, B., Amin, M., & Dewi, W. P. (2025). Pengawasan Peredaran Kosmetik Tanpa Izin Di Media Digital Melalui Platform Elamahamen. JURNAL USM LAW REVIEW, 8(3), 1930–1948. https://doi.org/10.26623/julr.v8i3.12305
Putra, P., Earlyanti, N. I., Mayastinasari, V., & Sinaga, S. P. (2025). Prediction of Kamtibmas Trends in the Jurisdiction of Bireuen Police Resort Using Naïve Bayes and Random Forest. 5(5), 3342–3365.
Salsabila, S., Rokhmah, S., & Pakarti, M. B. (2024). APLIKASI SISTEM PENDUKUNG KEPUTUSAN UNTUK MENENTUKAN PRODUK KOSMETIK TERLARIS PADA TOKO DAUN INDAH MENGGUNAKAN METODE APRIORI. JATI (Jurnal Mahasiswa Teknik Informatika), 8(4), 4499–4505. https://doi.org/10.36040/jati.v8i4.9975
Simanungkalit, A. N. D., Khairani, N., Indra, Z., & Idus, S. I. Al. (2024). Penerapan Metode SMART Pada Sistem Pendukung Keputusan Penentuan Penerima Bantuan Sosial Bagi Keluarga Miskin. Bit-Tech, 7(2), 339–347. https://doi.org/10.32877/bt.v7i2.1814
Sumarni, S., & Patappari, A. (2025). Sistem Pendukung Keputusan Pemberian Bantuan Hukum Secara Gratis Menggunakan Metode Saw Pada LBH Cita Keadilan Watansoppeng. Jurnal RISTER : Riset Sistem Cerdas, 2(1), 18–23. https://doi.org/10.25126/Rister
Suryadi, A., Muiz, A. A., & Hidayat, A. A. (2025). Implementation of a Decision Support System for Selecting the Best Supplier Using the SAW Method. Bit-Tech, 7(3), 928–935. https://doi.org/10.32877/bt.v7i3.2255
Taherdoost, H., & Mohebi, A. (2024). Using SMART Method for Multi-criteria Decision Making: Applications, Advantages, and Limitations. Archives of Advanced Engineering Science, 2(4), 190–197. https://doi.org/10.47852/bonviewaaes42022765
Wahyuningsih, S. E., Setiyowati, S., Mahmuhtarom, H. R., & Iksan, M. (2023). Implementation of Restorative Justice on Elderly Actors in Criminal Law Enforcement Based on Justice Value in Indonesia. International Journal of Social Science and Human Research, 06(02). https://doi.org/10.47191/ijsshr/v6-i2-41
Xin, H., Virk, A. S., Virk, S. S., Akin-Ige, F., & Amin, S. (2024). Applications of artificial intelligence and machine learning on critical materials used in cosmetics and personal care formulation design. Current Opinion in Colloid \& Interface Science, 73, 101847. https://doi.org/10.1016/j.cocis.2024.101847
Yuliani, T., Ariani, M., Hadiyatno, D., Saraswati, W., Susilowati, D., Cahyaning, R., Cipto, P., Sari, K., & Tamara, D. (2025). Pendampingan Izin Edar BPOM Produk Kopi Bubuk Pada UMKM Lamale Kelurahan Mentawir Kabupaten Penajam Paser Utara. Kontribusi: Jurnal Penelitian Dan Pengabdian Kepada Masyarakat, 6(1), 310–321. https://doi.org/10.53624/kontribusi.v6i1.811
Yürüm, O. R. (2025). Technology-Enhanced Multimodal Learning Analytics in Higher Education: A Systematic Literature Review. IEEE Access, 13, 92057–92073. https://doi.org/10.1109/ACCESS.2025.3572467
