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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic E-Dimas: Jurnal Pengabdian kepada Masyarakat JURNAL MEDIA INFORMATIKA BUDIDARMA JTERA (Jurnal Teknologi Rekayasa) INTECOMS: Journal of Information Technology and Computer Science JURIKOM (Jurnal Riset Komputer) Jurnal Riset Informatika Building of Informatics, Technology and Science Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Abdimas Galuh : Jurnal Pengabdian Kepada Masyarakat JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Madaniya Community Empowerment Jurnal ABDIMAS (Pengabdian kepada Masyarakat) UBJ Journal of Applied Computer Science and Technology (JACOST) Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Prosiding University Research Colloquium Borobudur Informatics Review Prosiding Seminar Nasional Hasil-hasil Penelitian dan Pengabdian Pada Masyarakat Jurnal Informatika Polinema (JIP) Journal Of Computer Science Contributions (JUCOSCO)
Maimunah
Universitas Muhammadiyah Magelang, Magelang, Indonesia
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Journal : Jurnal Riset Informatika

 1 
K-Means Clustering Method for Determining Waste Transportation Routes to Landfill Almas Nurfarid Budi Prasetyo; Maimunah Maimunah; Pristi Sukmasetya
Jurnal Riset Informatika Vol 5 No 3 (2023): Priode of June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i3.540

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.
K-Means Clustering Method for Determining Waste Transportation Routes to Landfill Almas Nurfarid Budi Prasetyo; Maimunah Maimunah; Pristi Sukmasetya
Jurnal Riset Informatika Vol. 5 No. 3 (2023): June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i3.219

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.
Co-Authors Achmat Mujafar Afif Prasetyo Afrilia Putri Permata Sari Ajeng Tri Rahayu Aldi Muhammad Nur Fadli Alfira Nisa Fadhilah Almas Nurfarid Budi Prasetyo Anita Setyowati Srie Gunarti Annisa Hakim Purwantini Arazka Firdaus Anavyanto Ardhin Primadewi Arya Prayoga Daffa Syahnakri Mikola Rusadi Danang Setya Nugraha Devara Avila Sebastian Devi Oktaviani Dimas Sandya Nugraha Dwihantoro, Prihatin Emilya Ully Artha Endah Ratna Arumi Fachri Ilman Fauzandi Fitria Suryatini Hanaki Restu Putri Helmi Naufal Muzakki Henni Lestari Herlawati Herlawati Heru Yusmanto Hery Setiawan Ika Arthalia Imam Saputra Ira Nuryani Irfan Rasyid Irfan Reza Pratama Malikus Sumadyo Maulina Rizky Anggraeni Mayu Shofwan Khamid Muhamad Nurrohman Muhammad Aulia Tegar Pratama Muhammad Devananda Andika Putra Muhammad Resa Arif Yudianto Mukhtar Hanafi Nadila Dwi Saputri Oqi Dyah Larasakti Prima Dina Atika Purwono Hendradi Raden Kartika Satya Suryanegara Rahendra Firman Sunartama Rahmadya Trias Handayanto Resa Arif Yudianto Resa Arif Yudianto Resa Arif Yudiyanto Rindiyani Rindiyani Rofi Abul Hasani Safira Ayu Muthi'ah Salsabila Putri Abhiseka Satrio Seta Samsiana Sukmasetya, Pristi Teddy Rahardian Uky Yudatama Venia Almira Wahyu Santoso Yantria Gusta Nugraha Yusril Febriyanto