K-Means Clustering Method for Determining Waste Transportation Routes to Landfill
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 o...
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| Format: | Article |
| Language: | English |
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Kresnamedia Publisher
2023-06-01
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| Series: | Jurnal Riset Informatika |
| Subjects: | |
| Online Access: | https://ejournal.kresnamediapublisher.com/index.php/jri/article/view/540 |
| _version_ | 1797688881632509952 |
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| author | Almas Nurfarid Budi Prasetyo Maimunah Maimunah Pristi Sukmasetya |
| author_facet | Almas Nurfarid Budi Prasetyo Maimunah Maimunah Pristi Sukmasetya |
| author_sort | Almas Nurfarid Budi Prasetyo |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-12T01:38:00Z |
| format | Article |
| id | doaj.art-3b19987f951140cca150d28f1c8dc492 |
| institution | Directory Open Access Journal |
| issn | 2656-1743 2656-1735 |
| language | English |
| last_indexed | 2024-03-12T01:38:00Z |
| publishDate | 2023-06-01 |
| publisher | Kresnamedia Publisher |
| record_format | Article |
| series | Jurnal Riset Informatika |
| spelling | doaj.art-3b19987f951140cca150d28f1c8dc4922023-09-11T04:17:56ZengKresnamedia PublisherJurnal Riset Informatika2656-17432656-17352023-06-015327728410.34288/jri.v5i3.540540K-Means Clustering Method for Determining Waste Transportation Routes to LandfillAlmas Nurfarid Budi Prasetyo0Maimunah Maimunah1Pristi Sukmasetya2Universitas Muhammadiyah MagelangUniversitas Muhammadiyah MagelangUniversitas Muhammadiyah MagelangWaste 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.https://ejournal.kresnamediapublisher.com/index.php/jri/article/view/540wastetransportation routek-means clusteringhaversine formula |
| spellingShingle | Almas Nurfarid Budi Prasetyo Maimunah Maimunah Pristi Sukmasetya K-Means Clustering Method for Determining Waste Transportation Routes to Landfill Jurnal Riset Informatika waste transportation route k-means clustering haversine formula |
| title | K-Means Clustering Method for Determining Waste Transportation Routes to Landfill |
| title_full | K-Means Clustering Method for Determining Waste Transportation Routes to Landfill |
| title_fullStr | K-Means Clustering Method for Determining Waste Transportation Routes to Landfill |
| title_full_unstemmed | K-Means Clustering Method for Determining Waste Transportation Routes to Landfill |
| title_short | K-Means Clustering Method for Determining Waste Transportation Routes to Landfill |
| title_sort | k means clustering method for determining waste transportation routes to landfill |
| topic | waste transportation route k-means clustering haversine formula |
| url | https://ejournal.kresnamediapublisher.com/index.php/jri/article/view/540 |
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