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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI PYTHAGORAS: Jurnal Program Studi Pendidikan Matematika Limits: Journal of Mathematics and Its Applications Jambura Journal of Mathematics Jurnal Matematika UNAND Contemporary Mathematics and Applications (ConMathA) Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Jambura Journal of Biomathematics (JJBM) Jurnal Diferensial Pattimura International Journal of Mathematics (PIJMath) Limits: Journal of Mathematics and Its Applications
Rahmi, Emli
Universitas Negeri Gorontalo
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Materials Science & Nanotechnology Mathematics Public Health

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Journal : PYTHAGORAS: Jurnal Program Studi Pendidikan Matematika

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Density based spatial clustering of application with noise using flower pollination algorithm for leptospirosis clustering Karim, Finansiya S. Abd.; Rahmi, Emli; Abdussamad, Siti Nurmardia; Hasan, Isran K.; Yahya, Nisky Imansyah
PYTHAGORAS : Jurnal Program Studi Pendidikan Matematika Vol 14, No 1 (2025): PYTHAGORAS: Jurnal Program Studi Pendidikan Matematika
Publisher : UNIVERSITAS RIAU KEPULAUAN, BATAM, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33373/pyth.v14i1.7505

Abstract

Leptospirosis is an important health problem in Indonesia, with most cases found in East Java and Central Java provinces. This study aims to identify the distribution pattern of leptospirosis in the two provinces using a clustering approach. The Density-Based Spatial Clustering of Applications with Noise (DBSCAN) method is used to cluster areas based on leptospirosis spread factors, but DBSCAN requires optimal parameter determination for accurate results. Therefore, this research implements Flower Pollination Algorithm (FPA) to optimize the epsilon (ϵ) and minimum points (MinPts) parameters in DBSCAN. This research uses secondary data obtained from data on the Number of Natural Disaster Events by Regency / City in East Java and Central Java Provinces in 2023 and data on Population Density by Regency / City in East Java and Central Java Provinces in 2023. The population in this study uses all observations, namely all people in the districts and cities in East Java and Central Java. The sampling technique is saturated sampling, that is, the entire population in the study is sampled. The clustering results using FPA-DBSCAN resulted in two main clusters, with 30 districts/municipalities detected as noise, 23 districts/municipalities belonging to cluster 0, and 20 districts/municipalities in cluster 1. The validation test using Silhouette Coefficient showed a value of 0.1892, indicating that the clustering is quite valid. The results of this clustering can serve as a strategic reference for local governments in optimizing disease surveillance and targeted health interventions.
Co-Authors Abdussamad, Trizaning Nursahbani Agusyarif Rezka Nuha Aliwu, Randa Resvitasari Amelia Tri Rahma Sidik Ana Nadiyyah Armayani Arsal Beay, Lazarus Kalvein DIAN SAVITRI Djihad Wungguli Friansyah Gani Hasan S. Panigoro Isran K Hasan Karim, Finansiya S. Abd. La Ode Nashar Lailany Yahya Mahmud, Sri Lestari NISKY IMANSYAH YAHYA Nisky Imansyah Yahya Novianita Achmad Nurhalis Hasan Nurwan Nurwan Nurwan Resmawan Resmawan Reza Mokodompit Reza Mokodompit Rusdianto Ibrahim Salmun K. Nasib Salmun K. Nasib Siti Maisaroh Siti Nurmardia Abdussamad Sitty Oriza Sativa Putri Ahaya Sri Lestari Mahmud