K-Means Clustering Method for Determining Waste Transportation Routes to Landfill
Abstract
Waste is worsening in Magelang City, especially in urban areas. As a result of poorly managed waste disposal, a landfill is needed. Magelang City has a landfill called TPA Banyuurip, located in Plumbon Hamlet, Banyuurip Village, Tegalrejo Subdistrict, Magelang City. From this case, the application of the kmeans clustering method to determine the efficiency of the waste transportation route to the landfill is needed. The research began by conducting direct observations at the Banyuurip landfill by interviewing the drivers of waste vehicles to find out information such as waste sources, transportation schedules, etc. In this study, the data used are the name and address of the supplier, sub-district, coordinate point, and distance from the supplier's place to the landfill. After data collection, data preprocessing is done by dividing and selecting data based on sub-districts. Then the data is processed using the kmeans clustering algorithm to divide the route efficiency and the haversine formula algorithm to determine the closest distance between clusters. After the data has been successfully processed, the number of clusters is 4 for north Magelang, where each cluster will become a corridor with four routes. For central Magelang, 2 clusters with two routes, while for south Magelang, the results are 4 clusters with four routes. From these results, the evaluation results using silhouette score for data clustering of 3 sub-districts are 0.632560 for North Magelang, 0.640667 for Central Magelang, and 0.630186 for South Magelang. This method is expected to help in grouping routes and mapping supplier areas effectively and efficiently in the waste transportation process in Magelang City.
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References
Adiya, M. H., & Desnelita, Y. (2019). Penerapan Algoritma K-Means Untuk Clustering data Obat-Obatan pada RSUD Pekanbaru. 05(01).
Ahmad, H., & Sigarete, B. G. (2020). Pengaruh Pemasangan Media Interpretatif Terhadap Perubahan Perilaku Wisatawan dalam Membuang Sampah di Tebing Breksi. Pringgitan, 1(02), 58–67. https://doi.org/10.47256/pringgitan.v1i02.37
Annugerah, A., Astuti, I. F., & Kridalaksana, A. H. (2018). Sistem Informasi Geografis Berbasis Web Pemetaan Lokasi Toko Oleh-oleh Khas Samarinda.
Apriyanti, D., Kresnawati, D. K., & Diniyah, W. F. (2019). Pemanfaatan Sistem Informasi Geografis untuk Analisis Rute Truk Pengangkutan Sampah di Kota Bogor. Seminar Nasional Geomatika, 3, 357. https://doi.org/10.24895/SNG.2018.3-0.975
Ardiansyah, R. (2021). ScientiCO : Computer Science and Informatics Journal Vol. 4, No. 1, (2021) E-ISSN: 2620-4118. 4(1).
Arifin, M. (2022). Sistem Informasi Geografis (SIG) Penentuan Tempat Pembuangan Akhir Sampah (TPA) Kabupaten Pamekasan Menggunakan Metode Composite Performance Index (CPI).
Drl, I. R., Chrisnanto, Y. H., & Umbara, F. R. (2022). Analisis Cluster pada Kelompok Masyarakat yang Rentan Terhadap Paparan Covid-19 Menggunakan Metode K-Means Clustering dan Visualisasi dengan SIG.
Hanafi, M., Warsito, B., & Gernowo, R. (2022). Sistem Informasi Manajemen Pengumpulan dan Pengangkutan Sampah Padat dengan Efisiensi Rute Menggunakan K-Means Clustering dan Travelling Salesman Problem. JURNAL SISTEM INFORMASI BISNIS, 12(2), 106–115. https://doi.org/10.21456/vol12iss2pp106-115
Hermanto, T. I., & Muhyidin, Y. (2021). Analisis Sebaran Titik Rawan Bencana dengan K-Means Clustering dalam Penanganan Bencana. 5.
Hutabalian, M., Sunanto, S., & Januar Al Amien. (2022). Sistem Informasi Geografis Pemetaan Tempat Pembungan Sampah Sementara di Kota Pekanbaru dengan Mencari Rute Terdekat Menggunakan Algoritma A Star (A*). Jurnal CoSciTech (Computer Science and Information Technology), 2(2), 33–42. https://doi.org/10.37859/coscitech.v2i2.2936
Irawan, A., Hermawan, E., & Riana, F. (2021). Pemetaan Zonasi Tingkat Resiko Covid-19 Menggunakan Metode K-Means Cluster Berbasis Webgis di Kota Bogor.
Isman, I., Khairat, U., & Kahpi, A. (2021). Sistem Informasi Pelayanan Pengangkutan Sampah Menggunakan GIS. Journal Peqguruang: Conference Series, 3(1), 154. https://doi.org/10.35329/jp.v3i1.2178
Paembonan, S., & Abduh, H. (2021). Penerapan Metode Silhouette Coeficient untuk Evaluasi Clutering Obat. 6(2).
Riza, M., Seminar, K. B., & Maulana, A. (2018). Pembentukan Target Pasar Berdasarkan Data Stream Transaksi Kartu Kredit (Clustering dan Association Rule) pada PT Bank Bukopin. Jurnal Aplikasi Bisnis dan Manajemen, 86–95. https://doi.org/10.17358/jabm.4.1.86
Rohmatulloh, Y. M., Herlambang, B. A., & Wibowo, S. (2022). Implementasi Algoritma Haversine Formula pada Aplikasi Sadewa (Sistem Informasi Destinasi Wisata) Kota Salatiga Berbasis Android. Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN), 10(1). https://doi.org/10.30646/tikomsin.v10i1.598
Sakti, B. R., Witanti, W., & Hadiana, A. I. (2021). Blood Bank Information System with Location-Based Service to Improve Blood Type Search Efficiency (Case Study: UTD PMI Cimahi).
Santoso, W., & Sukmasetya, P. (2023). Prediksi Volume Sampah di TPSA Banyuurip Menggunakan Metode Backpropagation Neural Network. 7.
Sentosa, R. B. (2018). Membangun Web Konten Manajemen Sistem Secara Dinamis dengan Bahasa Pemograman PHP Framework Codeigniter dengan Database MariaDB. INTECOMS: Journal of Information Technology and Computer Science, 1(2), 212–223. https://doi.org/10.31539/intecoms.v1i2.295
Sugianto, C. A., Rahayu, A. H., & Gusman, A. (2020). Algoritma K-Means untuk Pengelompokkan Penyakit Pasien pada Puskesmas Cigugur Tengah. Journal of Information Technology, 2(2), 39–44. https://doi.org/10.47292/joint.v2i2.30
Triyansyah, D., & Fitrianah, D. (2018). Analisis Data Mining Menggunakan Algoritma K-Means Clustering untuk Menentukan Strategi Marketing. Jurnal Telekomunikasi dan Komputer, 8(3), 163. https://doi.org/10.22441/incomtech.v8i3.4174
Wijayanti, D. E., Thobirin, A., & Prasetyo, P. W. (2020). Menentukan Rute Kendaran Pengangkut Sampah Kota Yogyakarta dengan Algoritma Cheapest Insertion Heuristic Modifikasi Route Construction. JURNAL FOURIER.
Wulakada, H. H., & Si, M. (2021). Sistem Informasi Geografis Pemetaan Lokasi Tempat Pembuangan Sampah Sementara (TPSS) Menggunakan Metode Promethe di Kota Kupang. 17.
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