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Mugiarso, Mugiarso
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Algoritma K-Means Clustering Untuk Rekomendasi Pemberian Beasiswa Bagi Siswa Berprestasi Sagala, Febry Sandrian; Mugiarso, Mugiarso; Priatna, Wowon
Journal of Students‘ Research in Computer Science Vol. 2 No. 2 (2021): November 2021
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/jdy9g441

Abstract

Scholarships are given to underprivileged students or outstanding students through a selection involving certain criteria. The criteria include the average value of report cards, parents' income, distance from home to school, number of dependents of parents, condition of the house, and status of the house. This study aims to assist the selection team in determining the award of scholarships so that they can provide appropriate and inappropriate recommendations, taking into account 6 criteria. The problem is that the existing scholarships are only given to students who do not have a father. The K-Means Clustering Algorithm can help Cluster students who are not eligible and eligible to get scholarship recommendations. The dataset used was 145 instances from the MAS scholarship selection committee. Attaqwa 02 Babylon. The data is calculated and tested using the K-Means Clustering algorithm. The results of the test were 32 people were recommended as eligible and 113 people were not eligible. The K-Means Clustering Algorithm can help the selection team to determine the scholarship award.
Sistem Pengendalian Persediaan Stok Barang Pada Toko Hafiz Menggunakan Metode EOQ (Economic Order Quantity) Makhfiroh, Tyka; Mugiarso, Mugiarso; Pamungkas, R. Wisnu Prio
Journal of Students‘ Research in Computer Science Vol. 3 No. 1 (2022): Mei 2022
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/6t111a14

Abstract

Inventory control needs to be considered by retail and manufacturing companies because it greatly determines the smooth running of business activities in achieving maximum profits with minimal costs. Inventory management of the Hafiz Store is still done manually. This can be overcome by having a prediction of the inventory that must be done to meet the number of customer requests. Prediction is expected to determine the optimal inventory. So the use of the Economic Order Quantity method in predicting demand for the next period is the right choice. The results of the analysis of yarn inventory control at the Hafiz Store concluded that the average demand for raw materials was 100 with an order cost of 1000, and a storage cost of 1000, with a period of 5 days, and the reorder point was 2550, the EOQ results obtained were 55. The prediction results are obtained then the process the calculation of the Economy Order Quantity (EOQ) method which is used to determine the number of items that must be ordered for each order, the amount of safety stock, and the minimum amount of stock for reordering through the built inventory application.
Co-Authors Makhfiroh, Tyka Pamungkas, R. Wisnu Prio Priatna , Wowon Sagala, Febry Sandrian