APPLICATION OF DBSCAN FOR CLUSTERING SOCIETY BASED ON WASTE MANAGEMENT BEHAVIOR
This research aims to answer the challenge of identifying the characteristics of the Batu City community in waste management, where traditional clustering techniques are often suboptimal due to the presence of noise or objects that do not fit the general pattern. As a solution, the Density-Based Spa...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Universitas Pattimura
2025-04-01
|
| Series: | Barekeng |
| Subjects: | |
| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/14990 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849402290215059456 |
|---|---|
| author | Hafizh Syihabuddin Al Jauhar Solimun Solimun Rahma Fitriani |
| author_facet | Hafizh Syihabuddin Al Jauhar Solimun Solimun Rahma Fitriani |
| author_sort | Hafizh Syihabuddin Al Jauhar |
| collection | DOAJ |
| description | This research aims to answer the challenge of identifying the characteristics of the Batu City community in waste management, where traditional clustering techniques are often suboptimal due to the presence of noise or objects that do not fit the general pattern. As a solution, the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is applied, which allows the clustering of objects based on local density and detects the presence of noise or outliers in the data. DBSCAN is considered more flexible than other clustering methods, especially in clustering data that is not linear or has a non-uniform distribution. This study successfully identified three clusters of waste management behavior with a silhouette index of 0.875, indicating good cluster quality. The first cluster consists of communities with good environmental quality, active participation in the use of waste banks, and a deep understanding of 3R-based waste management. The second cluster has adequate infrastructure quality and high awareness of the potential economic benefits of waste, while the third cluster displays a pretty good level of understanding of the 3Rs and relatively good environmental quality. The results of this study provide important insights into the differences in waste management characteristics between clusters, with environmental quality proving to be a significant factor in cluster formation. |
| format | Article |
| id | doaj-art-89c8db3ea9544b2ea9d96df0df9463ca |
| institution | Kabale University |
| issn | 1978-7227 2615-3017 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Universitas Pattimura |
| record_format | Article |
| series | Barekeng |
| spelling | doaj-art-89c8db3ea9544b2ea9d96df0df9463ca2025-08-20T03:37:34ZengUniversitas PattimuraBarekeng1978-72272615-30172025-04-0119296197210.30598/barekengvol19iss2pp961-97214990APPLICATION OF DBSCAN FOR CLUSTERING SOCIETY BASED ON WASTE MANAGEMENT BEHAVIORHafizh Syihabuddin Al Jauhar0Solimun Solimun1Rahma Fitriani2Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Brawijaya, IndonesiaDepartment of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Brawijaya, IndonesiaDepartment of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Brawijaya, IndonesiaThis research aims to answer the challenge of identifying the characteristics of the Batu City community in waste management, where traditional clustering techniques are often suboptimal due to the presence of noise or objects that do not fit the general pattern. As a solution, the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is applied, which allows the clustering of objects based on local density and detects the presence of noise or outliers in the data. DBSCAN is considered more flexible than other clustering methods, especially in clustering data that is not linear or has a non-uniform distribution. This study successfully identified three clusters of waste management behavior with a silhouette index of 0.875, indicating good cluster quality. The first cluster consists of communities with good environmental quality, active participation in the use of waste banks, and a deep understanding of 3R-based waste management. The second cluster has adequate infrastructure quality and high awareness of the potential economic benefits of waste, while the third cluster displays a pretty good level of understanding of the 3Rs and relatively good environmental quality. The results of this study provide important insights into the differences in waste management characteristics between clusters, with environmental quality proving to be a significant factor in cluster formation.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/14990dbscan clusteringenvironmental qualitynoise detectionwaste management behavior3r-based waste management |
| spellingShingle | Hafizh Syihabuddin Al Jauhar Solimun Solimun Rahma Fitriani APPLICATION OF DBSCAN FOR CLUSTERING SOCIETY BASED ON WASTE MANAGEMENT BEHAVIOR Barekeng dbscan clustering environmental quality noise detection waste management behavior 3r-based waste management |
| title | APPLICATION OF DBSCAN FOR CLUSTERING SOCIETY BASED ON WASTE MANAGEMENT BEHAVIOR |
| title_full | APPLICATION OF DBSCAN FOR CLUSTERING SOCIETY BASED ON WASTE MANAGEMENT BEHAVIOR |
| title_fullStr | APPLICATION OF DBSCAN FOR CLUSTERING SOCIETY BASED ON WASTE MANAGEMENT BEHAVIOR |
| title_full_unstemmed | APPLICATION OF DBSCAN FOR CLUSTERING SOCIETY BASED ON WASTE MANAGEMENT BEHAVIOR |
| title_short | APPLICATION OF DBSCAN FOR CLUSTERING SOCIETY BASED ON WASTE MANAGEMENT BEHAVIOR |
| title_sort | application of dbscan for clustering society based on waste management behavior |
| topic | dbscan clustering environmental quality noise detection waste management behavior 3r-based waste management |
| url | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/14990 |
| work_keys_str_mv | AT hafizhsyihabuddinaljauhar applicationofdbscanforclusteringsocietybasedonwastemanagementbehavior AT solimunsolimun applicationofdbscanforclusteringsocietybasedonwastemanagementbehavior AT rahmafitriani applicationofdbscanforclusteringsocietybasedonwastemanagementbehavior |