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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Mantik Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Teknologi Informatika dan Komputer
Gatot Soepriyono
Universitas Nasional
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media

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Journal : Journal of Computer System and Informatics (JoSYC)

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Penerapan Data Mining Untuk Mengukur Kepuasan Mahasiswa Terhadap Pembelajaran dengan Menggunakan Algoritma Naïve Bayes Agung Triayudi; Gatot Soepriyono
Journal of Computer System and Informatics (JoSYC) Vol 4 No 1 (2022): November 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i1.2524

Abstract

Education is very important for life, with education can help in improving Human Resources (HR). Human Resources (HR) in universities are students. Increased competence in students carried out in higher education is carried out by learning. The process carried out in learning is very influential on the results obtained from learning both competencies and abilities possessed by students. Based on this, it is necessary to improve learning in higher education in order to support good results. Measuring the level of student satisfaction with learning can measure the extent to which the learning process has been carried out. The process of measuring the level of student satisfaction with learning is done first by collecting data. After collecting data, the data processing process is carried out to get the expected results. Errors in the data processing process, the results obtained are also not in accordance with the objectives carried out. Therefore, to solve the problem it is necessary to do it with the right process by using a separate method or technique where the method is data mining. Data mining is a method or technique used for data processing. The data processing process carried out in data mining is carried out on large data. The Naïve Bayes algorithm is an algorithm that is included in the classification of data mining techniques. Where the process in the nave Bayes algorithm is very dependent on the grouping process carried out on each attribute and also the target class of each object. The results of the study show that the probability value of PUAS is 0.034108116 and the probability value of NOT SATISFIED is 0. This indicates that the result of decision making is SATISFIED.
Komparasi Metode Weighted Product (WP) Dan Simple Additive Weighting (SAW) Pada Sistem Pendukung Keputusan Dalam Menentukan Pembangunan Infrastruktur Kelurahan Flipo Hariski; Agung Triayudi; Gatot Soepriyono
Journal of Computer System and Informatics (JoSYC) Vol 4 No 3 (2023): May 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i3.3520

Abstract

The goverment gives urban villages more power includes urban village development. In accordance with local village goverment policies, there are specific criteria for allocating funds for village infrastructure development. The aim is to make the development of urban village infrastructure more equitable and targeted. Priorities for urban village infrastructure development must be decided. Decisions on urban infrastructure development are still made by voting and voting and often more significant developments have to be postponed due to losing votes. To prioritizes urban infrastructure development, urban village officials can use decision support system. Prioritization of urban village infrastructure development is determined using Simple Additive Weight (SAW) and Product weightn(WP) methodologies. Each proposal will be assessed according to the criteria chosen by the Kelurahan to determine development priorities. It is expected that the decision support system will be easier, more accurate, and faster in determining development priorities in Rangkapan jaya urban village. Comparison of SAW and WP methods using 10 alternative data, shows that both methods get accurate data and are suitable when applied as ranking of infrastructure development.
Co-Authors Agung Triayudi Andrianingsih Danis Setiawan Flipo Hariski Irfansyah Ismia Iwandini Muhammad Hafizh Lazuardi Novi Dian Nathasia Nur Hayati