IMPLEMENTASI DATA MINING DENGAN METODE CLUSTERING ALGORITMA K-MEANS UNTUK PENGELOMPOKAN DATA TILANG DI POLDA KEPRI
Abstrak
Every community relies on transportation, but drivers must follow the rules to be safe. There are several variables that lead many individuals to get ticketed, including the public's lack of knowledge and awareness of excellent, accurate, and safe driving standards, and the community's failure to check vehicle conditions and paperwork before traveling to avoid tickets during special operations (raids). This research examined two-wheeled drivers' traffic offenses in Batam City, an issue investigated by the author due to the numerous traffic offences that have disrupted the regulatory system thus far. The K-Means method clusters. Implementing the K-Means Algorithm to group traffic violation data helps the Riau Regional Police discover the most traffic infractions and the ticketing service department locate Batam traffic violation data groupings. The author will utilize a K-Means algorithm data mining approach to segment infractions thus far. Data analysis from the cluster, segregated by mopabudget type, degree of violation, and fine amount, yielded the findings of Cluster 0: 11 items 13. Cluster 2: 11 items from 35 data treated as sample data with performance vector; best clustering is 0.499.
Keywords : Transport, Traffic Violation, Data Mining, K-Means Algorithm, cluster, RapidMiner
Referensi
Aditya, A., Jovian, I., & Sari, B. N. (2020). Implementasi K-Means Clustering Ujian Nasional Sekolah Menengah Pertama di Indonesia Tahun 2018/2019. JURNAL MEDIA INFORMATIKA BUDIDARMA, 4(1), 51–58. https://doi.org/10.30865/mib.v4i1.1784
Annisa Ekasetya, V., & Jananto, A. (2020). KLUSTERISASI OPTIMAL DENGAN ELBOW METHOD UNTUK PENGELOMPOKAN DATA KECELAKAAN LALU LINTAS DI KOTA SEMARANG. Dinamika Informatika, 12(1), 20–28.
Daeli, F. F. W., Nofriansyah, D., & Yakub, S. (2022). Implementasi Data Mining Untuk Mengelompokkan Lokasi Berdasarkan Tingkat Kejahatan Pada Kabupaten Nias Barat Menggunakan Metode K-Means Clustering. Jurnal Cyber Tech, 1(4).
Dewi, E., Mulyani, S., Yusup, A. M., Tisna, A. K., Fauzi, F. A., Seta, I. B., Khairunas, R., & Ardiansyah, W. (2019). Clustering Wilayah Dan Pelanggaran Berkendaraan Menggunakan Algoritma K-Means Pada Data Satlantas Polres Tasikmalaya Kota (Vol. 8, Issue 1).
Indraputra, R. A., Fitriana, R., & others. (2020). K-Means Clustering Data COVID-19. Jurnal Teknik Industri, 10(3), 275–282.
