Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal International Journal of Social Service and Research Journal of Mathematics Instruction, Social Research and Opinion
Mukidin, Mukidin
Unknown Affiliation
Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
K-Means Algorithm Method for Clustering Best-Selling Product Data at XYZ Grocery Stores Ridzki, Mohamad Maulana; Hadijah, Ijah; Mukidin, Mukidin; Azzahra, Adelia; Nurjanah, Aisyah
International Journal of Social Service and Research Vol. 3 No. 12 (2023): International Journal of Social Service and Research (IJSSR)
Publisher : Ridwan Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/ijssr.v3i12.652

Abstract

This study aims to utilize the K-means clustering algorithm in data mining to categorize sales data at XYZ Grocery store. The research is essential for understanding sales patterns and enhancing inventory management strategies. The research methodology involves implementing the K-means clustering algorithm to generate centroid values for each cluster, thereby creating groups of products based on their sales performance. The findings of this study are expected to provide insights into sales trends at the store. While the abstract provides a general overview, specific results and contributions of this research are not detailed. Further studies could offer a more in-depth understanding of the practical applications of these findings in improving store management and inventory control.
Monte Carlo Method for Predicting Educational Service Revenue at Each Level of Education at PT. Kanaka Belajar Baratasena, Raden Radian; Mukidin, Mukidin; Kosim, Kosim; Ariatin, Adinda Rainah Lova
Journal of Mathematics Instruction, Social Research and Opinion Vol. 4 No. 3 (2025): September
Publisher : MASI Mandiri Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58421/misro.v4i3.497

Abstract

The increasing demand for education services in Indonesia has significantly influenced the growth of private tutoring businesses. PT Kanaka Belajar is a company that provides private tutoring services, yet it continues to face challenges related to revenue uncertainty and fluctuating student enrollment, which can affect financial management and increase the risk of business bankruptcy. Therefore, a reliable and accurate revenue prediction system is necessary at each level of education to estimate income for the coming year. The Monte Carlo method is a computational algorithm that uses repeated random sampling to obtain numerical results. This study applied the Monte Carlo method to forecast revenue based on historical data from 2021 to 2023. This research aims to develop a web-based revenue prediction system for educational services at different levels by implementing the Monte Carlo simulation. The results demonstrated that the model provided high prediction accuracy for private tutoring income at the elementary school level in 2023, with an MAPE value of 1.57%. The system predicted 314 tutoring sessions, while the data showed 319 sessions, resulting in a minimal difference of 5 sessions. These findings suggest that the Monte Carlo method effectively forecasts educational service revenue, where smaller percentage error values indicate higher accuracy, while larger errors suggest lower forecast reliability.
Co-Authors Ariatin, Adinda Rainah Lova Azzahra, Adelia Baratasena, Raden Radian Ijah Hadijah Kosim Kosim Nurjanah, Aisyah Ridzki, Mohamad Maulana