Article Per Year (5 Year)
p-Index From 2019 - 2024
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This Author published in this journals
All Journal Jurnal Software Engineering and Computational Intelligence Media Journal of General Computer Science (MJGCS)
Muhammad Sulkhan Nurfatih
Universitas Serelo Lahat
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Analysis of Accreditation's Impact on Student Numbers in South Sumatra Private Universities Using K-Means Clustering Muhammad Sulkhan Nurfatih; Yusi Nurmalasari; Agustian Prakarsyah
Media Journal of General Computer Science Vol. 1 No. 2 (2024): MJGCS
Publisher : MASE - Media Applied and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62205/mjgcs.v1i2.23

Abstract

Private universities in Indonesia are essential in meeting the educational needs of the country's increasing number of students. Among the key determinants of student enrollment is the accreditation status of these institutions. This study investigates how accreditation status influences student numbers at private universities in South Sumatra, employing the K-Means clustering method for analysis. Data from various institutions across South Sumatra were collected and analyzed, revealing distinct patterns in how universities are grouped based on their accreditation and enrollment figures. The findings shed light on the significant relationship between accreditation status and student enrollment, offering valuable insights for policymakers and university administrators. These insights can inform the development of effective student admission strategies, ultimately contributing to the growth and success of private universities in the region. This research not only highlights the importance of accreditation but also provides a comprehensive understanding of the factors driving student growth at private universities in South Sumatra.
Build Up Aplikasi Verifikasi Kemurnian Balok Karet dengan Whale Optimization Algorithm Firza Septian; Muhammad Sulkhan Nurfatih
Jurnal Software Engineering and Computational Intelligence Vol 2 No 01 (2024)
Publisher : Informatics Engineering, Faculty of Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jseci.v2i01.4146

Abstract

The rubber industry requires precise quality control of rubber blocks to maintain product consistency and customer satisfaction. This study develops an application to verify the purity of rubber blocks using the Whale Optimization Algorithm (WOA). The application aims to provide an accurate, efficient, and automated solution for detecting impurities. Inspired by the bubble-net hunting strategy of humpback whales, WOA is effective in solving complex optimization problems. In this research, WOA optimizes parameters for impurity detection, enhancing verification accuracy. The application integrates image processing techniques and machine learning algorithms. Images of rubber blocks are captured and processed to extract relevant features, which are then analyzed using WOA to identify impurities. Extensive testing demonstrated that the application achieves high accuracy in impurity detection, outperforming traditional methods. The use of WOA significantly reduces processing time, making the application suitable for real-time industrial verification. This study highlights the potential of the Whale Optimization Algorithm to improve quality control processes in the rubber industry. The developed application offers a reliable and efficient tool for ensuring rubber block purity, thereby enhancing product quality and operational efficiency.
Co-Authors Agustian Prakarsyah Firza Septian Yusi Nurmalasari