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Fadhil M. Basysyar
STMIK IKMI Cirebon
Computer Science & IT Economics, Econometrics & Finance Education Other

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Penerapan Data Mining Menggunakan Metode Clustering Untuk Mengetahui Kelompok Kepatuhan Wajib Pajak Bumi dan Bangunan Medina Aprilia Putri; Nining Rahaningsih; Fadhil M. Basysyar; Odi Nurdiawan
Jurnal Accounting Information System (AIMS) Vol. 5 No. 2 (2022)
Publisher : Ma'soem University

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Local taxes are taxes set by local governments whose collection authority and tax proceeds are used to fund regional expenditures. One of the taxes included in the authority of local governments is the Land and Building Tax (PBB). Land and Building Tax is one of the taxes that can be paid through the village government. With the increasing number of taxpayers in the village, the data on payment of tax contributions that go directly to the state treasury causes the Kendal Village government, Astanajapura District, Cirebon Regency not to know how many taxpayers are obedient and disobedient. This study uses data mining techniques namely the Clustering Method using the K-Means method. This study uses the Knowledge Discovery in Database (KDD) stage with the amount of data used as much as 1,159 in the form of taxpayer data for the Kendal Village community in 2021. The results of the RapidMiner test using the Davies Bouldin Index calculation obtained a cluster determination value with a value of 4 (0.862). Cluster 0 contains members who have a low level of compliance in paying PBB, Cluster 1 contains members of taxpayers with a moderate level of compliance in paying PBB, Cluster 2 has a high level of taxpayer compliance and Cluster 3 is a cluster with a very high level of taxpayer compliance. By having the most dominant average price determined by PBB in each cluster is Rp. 18.000,-.
Penerapan Data Mining pada Penjualan Produk MS Glow Menggunakan Metode Naive Bayes untuk Strategi Pemasaran Norma Ayuningtyas; Nining R; Fadhil M. Basysyar
Jurnal Accounting Information System (AIMS) Vol. 5 No. 2 (2022)
Publisher : Ma'soem University

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MS Glow Cirebon Store is a store that sells beauty products with sales orders every month in 2021 uncertain. Probably due to competition factors from several oyher stores that sell MS Glow products as well. Responding to this it takes innovation steps by analyzing product sales to generate new knowledge that will the be used for marketing strategy.so that the target market is in accordance with the expected. The method used in this study is the Naïve Bayes method the calculates the probability value of each attribute studied. The purpose og this study can provide a useful information such as the results of the prediction of marketing strategy that efektiv and efficiency of marketing and increase sales. With the 2021 sales data colletion, there are 240 data the based on Book Code attributes, Book Date, Month, Product Name, Price Sold, Initial Stock, Incoming Stock, Final Stock, and Restock. The results of prediction calculation using Naïve Bayes algorithms produce a prediction accuray rate of 92.50%, with precission clas that is “YA” 95.71%, “TIDAK” 88.00% and for class recall that is “YA” 91.78% and “TIDAK” 93.62%
Klasifikasi Data Bantuan Sosial pada Desa Sindangpano dengan Menggunakan Algoritma K-Nearest Neighbor Wulan Suci; Nining R; Fadhil M. Basysyar
Jurnal Accounting Information System (AIMS) Vol. 5 No. 2 (2022)
Publisher : Ma'soem University

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Since the emergence of the Covid-19 Pandemic, many people have joined affacted, one of which is people who have lost their livelihoods. In this study the data used is data on social assistance in the village of Sindangpano in 2021. The data will be processed using the data mining method the k-Nearest Neighbor (KNN) algorithm. One of the them is the emergence ofsocial jealousy between communities. In this study using data mining methods that are assisted by using the K-Nearest Neighbor (KNN) Algorithm and sopported by existing data using Knowlage Discovery Data (KDD) data mining techniques with data selection, transformation, data mining and evaluation in the distribution of social assistance in Sindangpano Village, there are often many problems because people think that the social assistance is distributed is not righ on target so that many people feel that they are not being noticed by the government. Problems that are often found are social jealousy. Among the people this is caused by a lack of information, communication and education by the government to the comunity. This teseach was made with the hope of producing a solution to a problem, so that it can solve many problems that occur in the distribution of Social Assistance in Sindangpano of Village. The results obtained from this classification trial an accuracy rate of 99.57% with a Village Fund precision of 99.50%, BPNT is 99.62%. and the recal result from the Village Fund are 99.50%, BPNT 99.62%. The result of this classification can also be seen what percentage of the community received the assistance, so that the level of balance in the number of recipients can be seen
Co-Authors Medina Aprilia Putri Nining R Nining Rahaningsih Norma Ayuningtyas Odi Nurdiawan Wulan Suci