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All Journal International Journal of Informatics and Computation Jurnal Sistem Informasi Akuntansi
Ulumuddin Ulumuddin
Universitas Bina Sarana Informatika
Computer Science & IT Economics, Econometrics & Finance

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Sistem Informasi Tabungan Siswa (Sitasi) Berbasis Website Dengan Model PIECES Azzah Rifqi Hakim; Abimanyu Surya Putra; Nikmatul Maula; Cindy Ayu Santika; Dea T rinanda Prameswari; Rousyati Rousyati; Fandhillah Fandhillah; Husni Mubarok; Dzulchan Abror; Warjiyono Warjiyono; Ulumuddin Ulumuddin
Jurnal Sistem Informasi Akuntansi (JASIKA) Vol. 3 No. 1 (2023): Mei 2023
Publisher : LPPM UBSI Kampus Kota Tegal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jasika.v3i01.2188

Abstract

Student savings is a form of activity that aims to educate students about the importance of saving and good financial management. Student savings also help students prepare for the future, develop savings habits, and understand the importance of discipline in managing finances. This study discusses the development of a website-based Student Savings Information System (Citation) as a solution to replace the manual student savings system at Nurul Iman Islamic Vocational School. Stasi uses information technology and the internet to facilitate the management of student savings. This system provides advantages and convenience for educational institutions, teachers, students, and parents. The research method used includes data collection through direct observation and the application of the PIECES Analysis method (Performance, Information, Economy, Control/Security, Efficiency, Service). This method is used to process data relevant to research. With the existence of a website-based Student Savings Information System (SITAS), it is hoped that the management of student savings can become more efficient, transparent, and provide greater benefits for students, teachers, and educational institutions as a whole. Through Citation, students can learn about the importance of saving and managing finances responsibly from an early age.
Enhancing Crime Prediction Using K-Means with PSO Ulumuddin
International Journal of Informatics and Computation Vol. 7 No. 1 (2025): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v7i1.68

Abstract

The effects of social media and modern approaches help offenders to achieve their crimes. This paper explores machine learning architecture to predict criminal crime cases by classifying each type of crime using K-Means which is optimized with PSO from the data the researcher got in the past mas. The clustering parameters use medium, light, and severe crime categories, each of them gets medium = 74, light = 46, and weight = 30. According to the experimental result, K-Means optimization with PSO can produce 0,12287 which uses SSE parameters while k-means performance gets results 0.885.
Co-Authors Abimanyu Surya Putra Azzah Rifqi Hakim Cindy Ayu Santika Dea T rinanda Prameswari Dzulchan Abror Fandhillah Fandhillah Husni Mubarok Nikmatul Maula Rousyati Rousyati Warjiyono Warjiyono