Open access Jurnal SINTA 3
IMPLEMENTATION OF THE DBSCAN ALGORITHM FOR CLUSTERING STUNTING PREVALENCE TYPOLOGY IN WEST JAVA, CENTRAL JAVA, AND EAST JAVA REGIONS
BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 19 No. 3 (2025) · pp. 1779–1790
- ISSN
- 2615-3017, 1978-7227
- Published
- 2025-07-01
- Publisher
- PATTIMURA UNIVERSITY
- Language
- eng
Abstract
Stunting, a condition where children are malnourished for a long period, causes growth failure in children. West Java, Central Java, and East Java are the 3 provinces with the highest prevalence of stunting in 2021. This study aims to group districts/cities in these provinces based on factors that influence stunting using the DBSCAN method (there has been no previous research using this method for this case), so the typology of stunting prevalence is implied. The group results can be valuable input for policy priorities in overcoming stunting. The study used the DBSCAN (Density-Based Spatial Clustering of Application with Noise) method, which can also detect noises (outliers). The determination of eps and MinPts is based on the average value of the distance from each data to its closest neighbor. The distance obtained then was used in the KNN algorithm to determine eps and MinPts parameters. Clustering is done using standardized data and DBSCAN parameters obtained from the k-dist plot, eps is 1.92, and MinPts is 2. The validation test used is the silhouette coefficient to determine the goodness of the cluster results. The clustering results show that there are 2 clusters and 1 noise that have special characteristics related to factors that influence the prevalence of stunting. Cluster 1 consisted of 97 districts/cities and was characterized by a high percentage of infants under 6 months receiving exclusive breastfeeding and the lowest average per capita household expenditure. Cluster 2 (Bekasi City and Depok City) was characterized by the lowest percentage of households with proper health facilities and infants aged 0-59 months receiving complete immunization. The noise (high stunting prevalence) in Bandung City is characterized by the lowest percentage of households having proper sanitation.
Collaboration network of the authors
40 authors · 185 co-authorship links · 2 across different organisations · showing the 40 most connected
Hover or tap a name to highlight its co-authors. Double-click to open the author's page.
- Universitas Halu Oleo
- Jenderal Soedirman University
- Universitas Syiah Kuala
- Affiliation unknown
- Different organisations
- Same organisation
- Affiliation unknown
- Thicker line = more joint articles · bigger circle = more articles
Show as table
| Co-author | Organisation | Joint articles |
|---|---|---|
| Abd Kadir | Universitas Halu Oleo | 9 |
| Muhammad Sudia | Affiliation unknown | 6 |
| Salim Salim | Universitas Halu Oleo | 6 |
| Ridway Balaka | Affiliation unknown | 6 |
| Samhuddin Samhuddin | Affiliation unknown | 6 |
| La Masi | Affiliation unknown | 5 |
| Mustamin Anggo | Universitas Halu Oleo | 5 |
| Aminur Aminur | Universitas Halu Oleo | 5 |
| Al Ichlas Imran | Affiliation unknown | 5 |
| Salimin Salimin | Affiliation unknown | 5 |
| Fahinu Fahinu | Affiliation unknown | 4 |
| Yuspian Gunawan | Affiliation unknown | 4 |
| Agustinus Lolok | Affiliation unknown | 4 |
| La Hasanudin | Universitas Halu Oleo | 4 |
| La Arapu | Affiliation unknown | 3 |
| Rahmad Prajono | Affiliation unknown | 3 |
| Edi Cahyono | Universitas Halu Oleo | 3 |
| La Hasanuddin | Affiliation unknown | 3 |
| Muhammad Hasbi | Universitas Syiah Kuala | 3 |
| Anwar Bey | Affiliation unknown | 3 |
| Suhar Suhar | Affiliation unknown | 2 |
| Jafar Jafar | Affiliation unknown | 2 |
| Kodirun Kodirun | Universitas Halu Oleo | 2 |
| La Ode Ahmad Jazuli | Affiliation unknown | 2 |
| Mohamad Salam | Affiliation unknown | 2 |
| Ruslan Ruslan | Affiliation unknown | 2 |
| Lukas Kano Mangalla | Universitas Halu Oleo | 2 |
| Budiman Sudia | Affiliation unknown | 2 |
| La Ndia | Universitas Halu Oleo | 2 |
| Saleh Saleh | Affiliation unknown | 2 |
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.