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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Sebatik IJISTECH (International Journal Of Information System & Technology) Building of Informatics, Technology and Science TEPIAN IJISTECH ProBisnis : Jurnal Manajemen Informatika Wicida Journal of Artificial Intelligence and Digital Business Journal of Humanities and Social Studies Cognitionis Civitatis et Politicae Variable Research Journal
Pahrudin, Pajar
Sistem Informasi, STMIK Widya Cipta Dharma
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Journal : Building of Informatics, Technology and Science

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Penerapan Algoritma K-Nearest Neighbor Untuk Klasifikasi Warga Penerima Bantuan Sosial Pahrudin, Pajar; Harianto, Kusno
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2276

Abstract

Social Assistance (BanSos) is a government program intended for lower-middle families. Social assistance is assistance given to the community, especially the lower middle class, which is not continuous and selective. Many types of social assistance are provided by the government with the aim of prospering and helping the community's economy. However, the problem that occurs is that there are still many people who receive social assistance that are not people who deserve to receive social assistance, while the lower middle class who should receive social assistance are neglected and do not receive the social assistance. It should be for the distributor or the kelurahan to form groups for residents who are entitled to receive social assistance. The process of grouping the recipients of social assistance can be done by processing the data of residents who have the right to receive the social assistance. The data processing can be done by using data mining. One of the algorithms that can be used to solve problems in data mining is the K-Nearest Neighbor algorithm. After carrying out the overall process with a value of K = 5, it was found that the new data from residents was declared eligible to receive social assistance
Penerapan Metode Topsis Pada Sistem Pendukung Keputusan Kelayakan Penerima Dana Bantuan Operasional Sekolah Azahari, Azahari; Pahrudin, Pajar; Yunita, Yunita
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2290

Abstract

One of the ways used to fulfill education. The Indonesian government implements a 12-year compulsory education program. Although there is a 12-year compulsory education program by the government, there are still some students who cannot continue their education due to factors from the family economy who are unable to meet the needs or costs of the education they take. The School Operational Assistance Fund (BOS) is a financial aid given to underprivileged students/I to be able to meet learning needs such as tuition fees, book fees or personal needs that support the implementation of education for students/I. For private schools, the School Operational Assistance Fund (BOS) has its own quota to be given to students. The organizing committee for the recipients of the School Operational Assistance Fund (BOS) is required to be fair and honest in the selection process. The error is because there is still no special provision used for the selection process or the assessment process carried out by the school. Decision Support System (DSS) is a system that has been integrated with a computer, where the decision support system is used to provide certain provisions that can be used to assist in providing recommendations in the decision-making process. TOPSIS uses the principle that the chosen alternative must have the closest distance from the positive ideal solution and the farthest from the negative ideal solution from a geometric point of view by using Euclidean distance to determine the relative proximity of an alternative to the optimal solution. By applying the TOPSIS method, Alternative 4 (A4) was selected as the beneficiary with a final score of 0.7251
Co-Authors Amelia Yusnita Azahari, Azahari Dair, Muhammad Filza Al Dicky Ary Setiawan Harianto, Kusno Harpad, Bartolomius Heny Pratiwi Karyn, Alesandra Gabriella Khair, Ahmad Abul Kusnandar M Yuditia Arfiyanto T Nassa M.Raihan Ramadhan Muhammad Fahmi Nur Lipi Jumadil Sapari Nursobah, Nursobah Palayukan , Teresa Dominika Palayukan, Teresa Dominika Paul, Debora Rasyad, Rizky Zakariyya Reza Andrea Salmon Salmon, Salmon Siti Lailiyah Syamsuddin Mallala Veran Goraldy Cosmas Yulindawati Yulindawati, Yulindawati Yunita Yunita