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All Journal JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi
IRWAN IRWAN
[SINTA ID: 6652752] Department of Mathematics, Universitas Negeri Makassar
Computer Science & IT Decision Sciences, Operations Research & Management Environmental Science Mathematics Social Sciences

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PENGGUNAAN SELF ORGANIZING MAP DALAM PENGELOMPOKAN TINGKAT KESEJAHTERAAN MASYARAKAT IRWAN IRWAN; ASTRI YUNI HASHARI; HISYAM IHSAN; AHMAD ZAKI
Jambura Journal of Probability and Statistics Vol 1, No 2 (2020): Jambura Journal of Probability and Statictics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjps.v1i2.7266

Abstract

Self Organizing Map (SOM) is one of the topology forms of Unsupervised Neural Network where in the learning process does not require output target. Clusters in this research consist of one or more regency/city areas that have certain characteristics based on the variables. Each cluster had to be validated by using the Davies Bouldin Index value to get the best cluster formation from the SOM algorithm learning process. The best cluster model is the cluster model that has the smallest Davies Bouldin Index value. This research used 30 variables that refer to the key statistics of South Sulawesi Province People's Prosperity in 2018 by BPS of South Sulawesi Province. In this research, four cluster formation models were formed which began by forming 2 cluster model to form 5 cluster. Based on the Davies Bouldin Index value, it was found that the  5 cluster model have minimum value of 0.17.
Pengelompokan Jenis Penerimaan Pajak di Kota Makassar Menggunakan Fuzzy Clustering Irwan Irwan; Sahlan Sidjara; Asmelia Putri Aryati
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi EULER: Volume 10 Issue 1 June 2022
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/euler.v10i1.14225

Abstract

This research discusses grouping types of tax receipts in the City of Makassar with the method of Fuzzy C-Means (FCM). The data used are secondary data from the tax office in the form of the amount of the receipts of income tax, value-added tax, and land tax building each district in the year 2018. The discussion starts from the theory of fuzzy clustering, simulation, and the characteristics of the simulation results. In this study, the obtained number of clusters the optimum, namely the 7 clusters that have the potential for tax revenue is relatively high, namely at cluster seven consists only of the District Tamalanrea, and the lowest in the cluster a sixth consisting of the Kecamatan Tallo, Ujung Tanah, and Sangkarrang. After hashing on a cluster that is formed can be used to see the level of the welfare of the community in each district.
Co-Authors AHMAD ZAKI Asmelia Putri Aryati ASTRI YUNI HASHARI Hisyam Ihsan Sahlan Sidjara