Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
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All Journal Informatics Management, Engineering and Information System Journal
Adi Raharjo
STMIK Mardira Indonesia, Bandung
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Library & Information Science Other

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Application of Value Added Tax Calculation on Sales: Case Study of PT. Tiga Nova Sentosa Dian Savitri; Roni Ilham Subagja; Dadi Rosadi; Adi Raharjo; Adjat Sudrajat
Informatics Management, Engineering and Information System Journal Vol. 1 No. 1 (2023): Infotmatics Management, Engineering, and Information System Journal
Publisher : LPPM STMIK Mardira Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56447/imeisj.v1i1.225

Abstract

This research is entitled an application that can calculate input VAT and output VAT on sales in a company. The lack of utilization of current technology or the system in calculating VAT sometimes results in errors in the difference in payments for the VAT. Therefore, it is necessary to have a system that functions as a VAT calculation tool. So that when the SPT period is reported there are no errors. This application aims to improve accuracy, speed and accuracy so as to reduce errors in management and report generation. The method of data collection uses interviews, observations and literature studies, while the research method used is descriptive method and for its development is Laravel which is an open source PHP-based web application, using the Model-View-Controller concept. This web- based information system was developed using the PHP and MySQL programming languages. The new system can maximize the work of the finance department in tax calculations in a way to be more effective and efficient.
Application Of The K-Means Clustering Algorithm For Data Collection And Grouping Of Reading Monitoring In The Literacy Program In One Of The Public Elementary Schools In Bandung Chicha Wiarsa; Lilis Emalia; Egi Badar Sambani; Adi Raharjo
Informatics Management, Engineering and Information System Journal Vol. 4 No. 1 (2026): Informatics Management, Engineering and Information System Journal
Publisher : LPPM STMIK Mardira Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study employs the K-Means Clustering algorithm within a data-gathering and monitoring framework for student literacy initiatives at a public primary school in Bandung. The research used a descriptive quantitative methodology, employing data from student reading activities, including the quantity of books read and reading comprehension scores. The K-Means algorithm analyzes this data to categorize children into three reading levels: high (Grade A), moderate (Grade B), and low (Grade C). The computation technique employs two variables ($x$ and $y$) denoting the number of books read and the corresponding comprehension scores. The study determined the final centroids for each cluster as follows: C1 (12.5, 88.75) for high ability, C2 (7.33, 75.0) for moderate ability, and C3 (3.0, 55.0) for poor ability. After two cycles, the clustering outcomes stabilized, indicating no further member reassignments among groups. Of the 10 students assessed, the algorithm categorized four into the high cluster, three into the intermediate cluster, and three into the low cluster. The findings indicate that the K-Means algorithm effectively classifies student literacy data in an objective, quantifiable manner. The execution of this algorithm helps educators track literacy progress, categorize abilities, and develop more targeted instructional strategies.
Co-Authors Adjat Sudrajat Chicha Wiarsa Dadi Rosadi Dian Savitri Egi Badar Sambani, Egi Badar Emalia, Lilis Roni Ilham Subagja