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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Ilmiah Matrik Sebatik Jurnal Nasional Komputasi dan Teknologi Informasi JURNAL IT: Media Infromasi STMIK Handayani Makassar Journal of Technopreneurship and Information System (JTIS) Building of Informatics, Technology and Science Journal of Applied Science, Engineering, Technology, and Education TEPIAN JPM: JURNAL PENGABDIAN MASYARAKAT Journal of Education Research Informatika Wicida
Nursobah, Nursobah
STMIK Widya Cipta Dharma
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Journal : Building of Informatics, Technology and Science

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Penerapan Algoritma K-Medoids Untuk Pengelompokan Data Penerima Bantuan Uang Kuliah Tunggal Bagi Mahasiswa Terdampak Covid-19 Andrea, Reza; Nursobah, Nursobah
Building of Informatics, Technology and Science (BITS) Vol 3 No 4 (2022): March 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (462.019 KB) | DOI: 10.47065/bits.v3i4.1294

Abstract

The ongoing Covid-19 pandemic period greatly affects various aspects of life, one of which is the issue of the economy. This problem has an impact on the field of education, one of which is at the university level. where many students whose parents/insurers of tuition fees are experiencing financial constraints due to the impact of the Covid-19 pandemic. So we need an effective way as a recommendation in analyzing student data based on the socioeconomic status of each student's parents in determining the group of UKT recipients. There are many ways that can be used, one of which is by utilizing data mining to group data for students who are entitled to get UKT using the K-Medoids method. The application of the K-Medoids method is used to group data on students who are eligible to receive UKT assistance funds with the aim of being a recommendation in analyzing student data based on the socioeconomic status of each student's parents in determining the UKT recipient group for the university. Whatever the results of the application of the K-medoids method, a group that deserves to be recommended is based on the results of Cluster / Grouping 0 with a total student data of 8 people based on the results of consideration of the criteria used, namely Parents' Occupation, Home Ownership Status and Parents' Income
Penerapan Data Mining Untuk Prediksi Perkiraan Hujan dengan Menggunakan Algoritma K-Nearest Neighbor Nursobah, Nursobah; Lailiyah, Siti; Harpad, Bartolomius; Fahmi, Muhammad
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.v4i3.2564

Abstract

Rain is a condition where water droplets fall from clouds to the earth. In life, the presence of rain is highly anticipated, rain can help people who have a profession as farmers. Rain that occurs on a large scale will really provide obstacles for the community, in addition to hampering activities or activities especially those carried out on outdoor rain can also cause disaster for the community in the form of flooding. Estimating rain for the community is very important, knowing whether it will rain or not can make it easier for the community to anticipate the possibilities that may occur due to rain. However, in the process of delivering forecasts, there is often an uneven distribution of information and delays in conveying information to the public regarding whether or not rain will occur. The community should be able to independently predict whether or not rain will occur. Data processing should be done properly and correctly. Data mining is a way that can be done to assist in data processing. In this study, the settlement process will be carried out using the K-Nearest Neighbor (K-NN) algorithm. The results obtained show that the data testing decision is NO. In other words, data mining and the K-Nearest Neighbor algorithm can help the problem solving process
Co-Authors Ahmad Abul Khair Ahmad Fahrijal Pukeng Andi Wahyudi Andrie Ramadhan Anisa Purnama Azahari Bambang Kurniawan Basukiyatno, Basukiyatno Bustomi, Tommy Ekawati, Hanifah Fachry Abda El Rahman Harpad, Bartolomius Hartinah , Sitti Heny Pratiwi Hutapea Dwi Agustian Ita Arfyanti Jaelani, Jan-Jan Jan-Jan Jaelani Kansil, Joese Andrew Josly Kurnia, Asri Kusnandar Kusnandar Malalla, Syamsuddin Mallala, Syamsudin Muhammad Fahmi Nur Lipi Jumadil Sapari Nurhuda, Asep Pahrudin, Pajar Pitrasacha Adytia Pukeng, Ahmad Fahrijal Rajiansyah, Rajiansyah Reza Andrea Rizky Zakariyya Rasyad Saad, Muhammad Ibnu Sadya Winda Sari Salmon Salmon Sapran Hanafi Siti Lailiyah Sri Ratmini Sugeng Suryani Supriady Supriady Suryani, Sugeng Syamsuddin Mallala Tommy Bustomi Yunita Yunita