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All Journal Jurnal Accounting Information System (AIMS) Jurnal Accounting Information System (AIMS)
Nana Mulyanasari
STMIK IKMI Cirebon
Computer Science & IT Economics, Econometrics & Finance Education Other

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Sistem Informasi Pengelompokan Pembayaran Denda Tilang Menggunakan Algoritma K-Means Clustering Nana Suarna; Nining Rahaningsih; Nana Mulyanasari; Usup Supendi
Jurnal Accounting Information System (AIMS) Vol. 4 No. 1 (2021)
Publisher : Universitas Ma'soem

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32627/aims.v4i1.128

Abstract

This study Violation can be defined as a situation where there is a mismatch between the rules and implementation. The regulation is contained in Law Number 22 Year 2009, concerning "Road Traffic and Transportation" which has been stipulated by the state and is valid legally. The current problem shows, there is no information service system for ticket data management, unable to manage the process of grouping the results of the payment of fines properly, because the process is still manual by checking the data of offenders who have made payments, so it takes longer to process the grouping and data management payment results. The objectives of this study are: Knowing the success of the k-means clustering algorithm in the process of grouping the ticket data to the process of grouping the results of the payment of fines. This research uses the clustering method with the k-means algorithm which is one of the algorithms for the formation of data clusters. This algorithm works by dividing the data into k-clusters by grouping data based on certain classes which are then formulated the results by analyzing the articles that are violated and average. the total amount of the penalty payment. Research shows that information services for ticket data management using the k means clustering algorithm can simplify the process of grouping the payment of fines by more than 70%. This can be proven through the results of the hypothesis test which states that t count is smaller than t table with a value of -2.430 <2.178 so that Ha can be accepted and H0 is rejected.
Sistem Informasi Pengelompokan Pembayaran Denda Tilang Menggunakan Algoritma K-Means Clustering Nana Suarna; Nining Rahaningsih; Nana Mulyanasari; Usup Supendi
Jurnal Accounting Information System (AIMS) Vol. 4 No. 1 (2021)
Publisher : Ma'soem University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32627/aims.v4i1.268

Abstract

This study Violation can be defined as a situation where there is a mismatch between the rules and implementation. The regulation is contained in Law Number 22 Year 2009, concerning "Road Traffic and Transportation" which has been stipulated by the state and is valid legally. The current problem shows, there is no information service system for ticket data management, unable to manage the process of grouping the results of the payment of fines properly, because the process is still manual by checking the data of offenders who have made payments, so it takes longer to process the grouping and data management payment results. The objectives of this study are: Knowing the success of the k-means clustering algorithm in the process of grouping the ticket data to the process of grouping the results of the payment of fines. This research uses the clustering method with the k-means algorithm which is one of the algorithms for the formation of data clusters. This algorithm works by dividing the data into k-clusters by grouping data based on certain classes which are then formulated the results by analyzing the articles that are violated and average. the total amount of the penalty payment. Research shows that information services for ticket data management using the k means clustering algorithm can simplify the process of grouping the payment of fines by more than 70%. This can be proven through the results of the hypothesis test which states that t count is smaller than t table with a value of -2.430 <2.178 so that Ha can be accepted and H0 is rejected.
Co-Authors Nana Suarna Nining Rahaningsih Usup Supendi