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p-Index From 2021 - 2026
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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

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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.
Grouping Students Based On Academic Values Using The K-Means Method At A Vocational High School In Bandung Robi Firmansyah; Rini Risanti; Oktavia Oktavia; Miftah Fahmi; Adi Raharjo
Informatics Management, Engineering and Information System Journal Vol. 3 No. 2 (2025): Informatics Management, Engineering and Information System Journal
Publisher : LPPM STMIK Mardira Indonesia

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Abstract

A vocational high school in Bandung is dedicated to cultivating competitive and employable graduates.  Nonetheless, the institution faces challenges in conducting comprehensive assessments of pupils' academic data to identify their strengths and weaknesses.  Currently, data analysis relies on basic descriptive methodologies, which often fail to yield adequate insights for informed strategic decision-making.  Furthermore, there is a lack of interactive visualization tools to enhance the presentation of student grouping data. This study aims to address these concerns by utilizing the K-Means algorithm to categorize pupils based on their academic performance.  This classification yields three clusters that delineate students' attributes in high, medium, and low score categories.  The evaluation results indicate that the model comprising three clusters has the highest Silhouette Score of 0.3364.  This research generates an interactive website as a visualisation tool to display the outcomes of student grouping correctly. The implementation of this method is anticipated to enhance the school's management of academic data and deliver tailored learning recommendations that more effectively address the needs of students within each cluster.  Therefore, the educational quality of this vocational high school in Bandung can be markedly enhanced.
Co-Authors Adjat Sudrajat Chicha Wiarsa Dadi Rosadi Dian Savitri Egi Badar Sambani, Egi Badar Emalia, Lilis Miftah Fahmi Oktavia Oktavia Rini Risanti Robi Firmansyah Roni Ilham Subagja