Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS
Yunarso Anang
Politeknik Statistika STIS
Computer Science & IT

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

Found 2 Documents
Search

 1 
Development of Student's Dropout Early Warning System Using Analytical Hierarchy Process Naflah Ariqah; Yunarso Anang
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2021 No. 1 (2021): Proceedings of 2021 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2021i1.201

Abstract

As a higher education institution, Politeknik Statistika STIS also faces the same problems as universities in general, those are student failing to compare that year courses thus have to repeat those courses or student dropping out. To overcome this problem, this research proposes a Dropout Early Warning System (DEWS) that can provide early warnings for dropouts and repeat a class. With this system, it is hoped that it can help institutions to identify students who have the potential to drop out or repeat a class. The purpose of making this system is to help academic supervisors and decision makers from Polstat STIS in knowing the potential for student. The potential for students to drop out and repeat a class is measured by a potential score obtained from the results of an assessment of 5 criteria consisting of GPA scores, gender, economic factors, violation points, and record of repeating class. Prediction results are presented in three categories consisting of low potential, medium potential, and high potential which are calculated from the results of weighting calculations using the Analytical Hierarchy Process (AHP). The system is tested and verified using Black Box test and the evaluation of the calculation method using confusion matrix. Based on the test results, the functions that exist in the system can function properly and can supply the needs.
Development of Student’s Uniform Compliance Detection System Using Real Time Image Recognition at Politeknik Statistika STIS Ardian Fajri Saputra; Yunarso Anang
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2023 No. 1 (2023): Proceedings of 2023 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2023i1.298

Abstract

Regulations in the Politeknik Statistika STIS (hereinafter called Polstat STIS) aims to produce graduates who are qualified, with integrity and trusted. In enforcing regulations in Polstat STIS, there are a student squad of regulations enforcement, which is called Satuan Penegak Disiplin or SPD in Indonesian, which aims to maintain the order, discipline and student ethics during their activities on and off campus. In upholding the regulations, SPD carries out surprise inspection and during the weekly morning assembly to check completeness and tidiness of student’s uniform as well as his/her look. However, previous research related to the student’s commitment to the campus regulations shows that half of the students have low commitment. This is partly due to the lack of supervision of students. Therefore, it is necessary to monitor the discipline and neatness of students on an ongoing basis. In order to conduct the monitoring and inspection on a more regular basis, the method of image recognition can be used to assist in overseeing student discipline and neatness. In this study, we developed a system which can detect in a real-time manner the completeness of attributes the student wears. The system we developed uses object detection to detect the completeness of student attributes. The system shows and records student(s) whose attributes are incomplete. The system expected to improve the discipline and neatness of the students.
Co-Authors Ardian Fajri Saputra Naflah Ariqah