Geographic Information System for Mapping Drug Abuse Areas in Lhokseumawe City Using the Average Linkage Method

Icut Syintia; Wahyu Fuadi; Zara Yunizar

doi:10.29103/jacka.v2i1.17804

Geographic Information System for Mapping Drug Abuse Areas in Lhokseumawe City Using the Average Linkage Method

Icut Syintia, Wahyu Fuadi, Zara Yunizar

Abstract

Aceh is one of the provinces in Indonesia where the development of drug abuse has increased. The system that runs at BNN Lhokseumawe City in recording data and information about drug abuse cases has not been integrated with the mapping of drug abuse areas. Therefore, BNN and Lhokseumawe City Police need a drug abuse area mapping system in the Lhokseumawe City area. This research aims to build a webgis-based geographic information system using the Google Maps API for map visualization. The data mining method used is Average Linkage, clustering is done based on the number of cases, number of suspects and population in each sub-district in Lhokseumawe City. Cluster 1 consists of 1 sub-district, namely Banda Sakti, which in cluster 1 has a relatively high average value compared to clusters 2 and 3 so that it is included in a very vulnerable level. In cluster 2 consists of 2 sub-districts, namely Muara Satu and Muara Dua, because this cluster has a medium average value compared to clusters 1 and 3 so that it is included in the vulnerable level. Whereas the cluster in cluster 3 consists of 1 sub-district, namely Blang Mangat, which in cluster 3 has a relatively lower average value than clusters 1 and 2 so that it is included in the moderately vulnerable level.

Keywords

Drug Abuse; WebGis; Google Maps API; Average Linkage

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References

Sahputra, I., Mauliza, M., & Zohra, S. F. A. (2023). The Implementasi Algoritma C5.0 Pada Klasifikasi Status Gizi Ibu Hamil di Kota Lhokseumawe. Metik Jurnal, 7(1), 42–46. https://doi.org/10.47002/metik.v7i1.562

Sari, Y., & Riyansah, H. (2021). Aplikasi Tracking Pedagang Keliling Dengan GPS Google Maps API Berbasis Android. Jurnal Komputer Dan Informatika, 5(3), 178–191.

Kadarsih, K., & Andrianto, S. (2022). Membangun Website SMA Gunung Raya Ranau Menggunakan PHP dan MYSQL. JTIM: Jurnal Teknik Informatika Mahakarya, 03(2), 37–44.

Adek, R. T., Yunizar, Z., & Febriliansyah, M. (2023). Sistem Informasi Geografis Pemetaan Dan Penentuan Lokasi Wisata Alam Strategis Dengan Metode Simple Additive Weighting (Saw). POSITIF : Jurnal Sistem Dan Teknologi Informasi, 9(1), 49–56. https://doi.org/10.31961/positif.v9i1.1711.

Rahardja, U., Aini, Q., & Iqbal, M. (2020). InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan. InfoTekJar : Jurnal Nasional Informatika Dan Teknologi Jaringan, 5(1), 40–43. https://doi.org/10.30743/infotekjar.v5i1.2464%0Ahttps://doi.org/10.30743/infotekjar.v5i1.1997

Novia, E., & Hendikawati, P. (2024). Average Linkage Hierarchical Cluster untuk Pengelompokan Kabupaten / Kota di Provinsi Jawa Tengah Berdasarkan Variabel Pencegahan Terjadinya Stunting. 7, 702–711.

Novitasari, P., & Arofah, I. (2023). Penerapan Metode Clustering Average Linkage Untuk Mengelompokkan Kabupaten/Kota Di Provinsi Sumatera Utara Berdasarkan Indikator Kemiskinan. MathVision : Jurnal Matematika, 5(1), 22–27. https://doi.org/10.55719/mv.v5i1.604

Paramadina, M., Sudarmin, S., & Aidid, M. K. (2019). Perbandingan Analisis Cluster Metode Average Linkage dan Metode Ward (Kasus: IPM Provinsi Sulawesi Selatan). VARIANSI: Journal of Statistics and Its Application on Teaching and Research, 1(2), 22. https://doi.org/10.35580/variansiunm9357

Putri, S. H., Anisa, M. N., Nur, I. M., & Haris, M. Al. (2021). Perbandingan Metode Single Linkage dan Average Linkage Pada Pengelompokan Wilayah Kecamatan di Kabupaten Kendal Berdasarkan Potensi Sektor Pertanian. Seminar Nasional UNIMUS, 4, 44–51.

Reinaldi, Y., Ulinnuha, N., & Hafiyusholeh, M. (2021). Comparison of Single Linkage, Complete Linkage, and Average Linkage Methods on Community Welfare Analysis in Cities and Regencies in East Java. Jurnal Matematika, Statistika Dan Komputasi, 18(1), 130–140. https://doi.org/10.20956/j.v18i1.14228

Septianingsih, A. (2022). Pemetaan Kabupaten Kota Di Provinsi Jawa Timur Berdasarkan Tingkat Kasus Penyakit Menggunakan Pendekatan Agglomeratif Hierarchical Clustering. Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika Dan Statistika, 3(2), 367–386. https://doi.org/10.46306/lb.v3i2.139

Simamora, H., & Bagus Sumargo. (2019). Pengklasifikasian Pengguna Internet Lingkungan Pedesaan Menurut Jenjang Pendidikan di Indonesia menggunakan Metode Cluster Average Linkage. Jurnal Statistika Dan Aplikasinya, 3(1), 22–29. https://doi.org/10.21009/jsa.03103

Wayan, N., Damayanthi, R., Luh, N., Suciptawati, P., Jayanegara, K., & Kencana, E. N. (2023). Pengelompokan Provinsi di Indonesia Menurut Indikator Indeks Kebahagiaan Menggunakan Metode Average Linkage. INNOVATIVE: Journal Of Social Science Research, 3, 8859–8872

Yanti, R., Retno, S., & Yafis, B. (2024). Implementation of K-NN Algorithm to classify the Scholarship Recipients of Aceh Carong at Universitas Malikussaleh. Journal of Advanced Computer Knowledge and Algorithms, 1(1), 5-9.

Widodo, E., Mashita, S. N., & Prasetyowati, Y. G. (2020). Perbandingan Metode Average Linkage, Complete Linkage, dan Ward’S pada Pengelompokan Kabupaten/Kota di Provinsi Jawa Tengah Berdasarkan Indikator Indeks Pembangunan Manusia. Faktor Exacta, 13(2), 81. https://doi.org/10.30998/faktorexacta.v13i2.6581

Arief Rahman, Renny Puspita Sari, & ]Dian Prawira. (2023). Sistem Informasi Geografis Pemetaan Lahan Pertanian Dan Komoditi Hasil Panen Berbasis Website. Jurnal Komputer Dan Aplikasi, 11(Volume 11, No. 01 (2023), hal 83–91), 83–91

Fauziah, S., & Wachidah, L. (2021). Pengelompokan kota/kabupaten di Provinsi Jawa Barat berdasarkan indikator keluarga sehat tahun 2019 menggunakan metode average linkage. Prosiding Statistika, 324–331

Permatasari, A., & Suhendi, S. (2020). Rancang Bangun Sistem Informasi Pengelolaan Film berbasis Aplikasi Web. Jurnal Informatika Terpadu, 6(1), 29–37. https://doi.org/10.54914/jit.v6i1.255

DOI: https://doi.org/10.29103/jacka.v2i1.17804