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All Journal Building of Informatics, Technology and Science Journal Of World Science
Christina Juliane
Sekolah Tinggi Manajemen Informatika dan Komputer LIKMI, Bandung
Computer Science & IT Economics, Econometrics & Finance Engineering Health Professions Law, Crime, Criminology & Criminal Justice Social Sciences

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User Satisfaction Analysis of Paylater Services Using K-Means Algorithm in Campus Syahrul Anwar; Nina Kurnia Hikmawati; Christina Juliane
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): Desember 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2533

Abstract

In the 4.0-based digital era, the use of e-commerce is increasing. The convenience provided to e-commerce users is increasingly being considered by companies engaged in e-commerce. Paylater is a fairly new payment method among Indonesian e-commerce, so research is needed to improve the service and satisfaction of e-commerce users, especially those using the paylater payment method. The purpose of this study is to analyze user satisfaction with paylater services using the k-means algorithm on campuses in region 3 Cirebon. This research is also to find out the benefits of paylater used by students. This research is a type of quantitative research using the k-means algorithm to determine the classification of paylater user satisfaction in several e-commerce applications at several universities in region 3 Cirebon which is then clustered. The results of the study show that Cirebon students in the Campus 3 area are satisfied with services from companies or online shops that have paylater payment facilities
Analysis and Design of Student Point Systems to Improve Student Achievement using The Clustering Method Ade Bani Riyan; Mochamad Fikri Rifai; Christina Juliane
Journal of World Science Vol. 2 No. 3 (2023): Journal of World Science
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jws.v2i3.155

Abstract

The student points system is an application for recording students' achievement and offense points. The lack of recording and dissemination of information on achievement results makes students less motivated to improve achievement, and the distribution of scholarships for outstanding students is inappropriate. To improve student achievement, an application program is needed that can record and disseminate student achievement data in real-time, accurate, and effective. So, the purpose in this study is to know and analyze the design of the student point system to improve student achievement using the clustering method. Researchers use the Clustering Method in calculating data to determine the accuracy of scholarship distribution for outstanding students. Clustering with the most achievement points is clustering 2 with 25,254 Achievement Points. The total number in the level 2 cluster is 1,797 which indicates the number is close to 2,000 or 2 which is the result of data transformation from the junior high level. The implication of clustering research on student point data is to provide useful information for the Foundation as an institution that houses schools in allocating scholarships for outstanding students. In this case, clustering 2 with the highest number of Achievement Points indicates that there is a group of students with high achievement points. By using the clustering results, the Foundation can allocate scholarships more effectively and efficiently, because it can identify outstanding students from various school levels more easily.
Co-Authors Ade Bani Riyan Mochamad Fikri Rifai Nina Kurnia Hikmawati Syahrul Anwar