Using k-Means and Self Organizing Maps in Clustering Air Pollution Distribution in Makassar City, Indonesia

Annas, Suwardi and Uca, Uca and Irwan, Irwan and Safei, Rahma Hesha and Rais, Zulkifli (2022) Using k-Means and Self Organizing Maps in Clustering Air Pollution Distribution in Makassar City, Indonesia. Jambura Journal of Mathematics, 4 (1). pp. 167-176. ISSN 2654-5616

	Text 5. Jurnal Sinta 3 Jambura_Penulis1_Koresponden_fix.pdf - Published Version Download (167kB)
	Text 5. Hasil Turnitin Jurnal Sinta 3 Jambura_Penulis1_Koresponden_fix.pdf - Additional Metadata Download (2MB)
	Text 5. Hasil Review Jurnal Sinta 3 Jambura_Penulis1_Koresponden_fix.pdf - Additional Metadata Download (1MB)
	Text 5. Jejak Korespondensi Jurnal Sinta 3 Jambura_Penulis1_Koresponden_fix.pdf - Additional Metadata Download (236kB)

Abstract

Air pollution is an important environmental problem for specific areas, including Makassar City, Indonesia. The increase should be monitored and evaluated, especially in urban areas that are dense with vehicles and factories. This is a challenge for local governments in urban planning and policy-making to fulfill the information about the impact of air pollution. The clustering of starting points for the distribution areas can ease the government to determine policies and prevent the impact. The k-Means initial clustering method was used while the Self-Organizing Maps (SOM) visualized the clustering results. Furthermore, the Geographic Information System (GIS) visualized the results of regional clustering on a map of Makassar City. The air quality parameters used are Suspended Particles (TSP), Sulfur Dioxide (SO2), Nitrogen Dioxide (NO2), Carbon Monoxide (CO), Surface Ozone (O3), and Lead (Pb) which are measured during the day and at night. The results showed that the air contains more CO, and at night, the levels are reduced in some areas. Therefore, the density of traffic, industry and construction work contributes significantly to the spread of CO. Air conditions vary, such as high CO levels during the day and TSP at night. Also, there is a phenomenon at night that a group does not have SO2 and O3 simultaneously. The results also show that the integration of k-Means and SOM for regional clustering can be appropriately mapped through GIS visualization.

Item Type:	Article
Subjects:	FMIPA > STATISTIKA - (S1) FMIPA > Geografi PASCASARJANA > Geografi PASCASARJANA > Geografi FMIPA > Matematika
Divisions:	FAKULTAS MIPA
Depositing User:	FMIPA UNM
Date Deposited:	24 Aug 2022 09:23
Last Modified:	24 Aug 2022 09:23
URI:	http://eprints.unm.ac.id/id/eprint/24412

Actions (login required)

View Item