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Journal : Building of Informatics, Technology and Science

 1 
Implementasi Algoritma K-Modes Untuk Mengukur Tingkat Kepuasan Mahasiswa Terhadap Pembelajaran Daring Desyanti, Desyanti; Yusrizal, Yusrizal; Sari, Febrina
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 (623.929 KB) | DOI: 10.47065/bits.v3i4.1401

Abstract

The outbreak of the corona virus outbreak has made the economic system, education system and other systems very chaotic. That is why Dumai College of Technology has participated in implementing online learning from March 2020 to June 2021 in accordance with government regulations. Brave learning is an alternative in overcoming the lecture system, so students no longer come to campus and only attend lectures from home. Although learning activities are carried out boldly, lectures must still pay attention to the quality and quality of learning, that's why we need a method to analyze the level of student satisfaction in the bold learning process, which can later be used as evaluation material by the campus. The use of the k-modes clustering algorithm is to group the satisfaction results into several clusters including very satisfied, satisfied, dissatisfied and very dissatisfied and the data processed is data in the form of categorical data or data in the form of classification by performing matching equations between training data and centroids for looking for the closest distance and the value of the objective equation, the sample used was 100 respondents who filled out the satisfaction assessment questionnaire, from the results of the questionnaire data processing the cluster was very satisfied with a percentage of 22%, the cluster was satisfied 69%, the cluster was not satisfied 5% and the last in the very dissatisfied cluster as much as 4%
Implementasi Algoritma K-Nearest Neighbour dalam Memprediksi Stok Sepeda Motor Desyanti, Desyanti; Wulandari, Denok
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.v4i3.2579

Abstract

PT. Dasatama Cemerlang Motor is a company engaged in the automotive sector. With the increasingly fierce competition among the automotive industry, companies are required to be able to handle inter-industry competition. Sales system PT. Dasatama Cemerlang Motor uses a cash or credit system. For every motorcycle sale, the admin inputs sales data using Ms.Excel. Even though Ms.Excel has many features and functions that are used to process numbers, it cannot predict annual motorcycle sales for the future as a reference in marketing strategy. Because of that, forecasting is needed which will help the company to find out the trend in the number of motorcycle sales for the coming year. The KNN algorithm is one of the methods used for classification analysis, but in the last few decades the KNN method has also been used for prediction. KNN looks for the shortest distance between the data to be evaluated and its K closest neighbors. The results achieved in this study resulted in the number of motorcycles for each brand that will be sold in 2022 obtained from the addition of 5 motorcycles for each sale of each motorcycle brand. Based on the research results, the prediction accuracy rate using the KNN method is 97%.
Co-Authors AA Sudharmawan, AA Adi Supriyatna Arif, M Azmi, Azmi Cut Mala Azzura Deby Monalisa Simanjuntak Denok Wulandari Desi Novianti Devit Satria Devit Satria Dewi Anjani Dewi Anjani Elisa Hafrida Febrina Sari Febrina, Wetri Frieyadie Frieyadie Gellysa Urva Hendri Mual Munson Hetty Rohayani John Suarlin Juanda Hakim Lubis Julimar Julimar Juwita Yanti Pakpahan M Arif Mahmud, Soni Fajar Melingga Milyani Mesran, Mesran Muhammad Arif Muhammad Arif Mustazihim Suhaidi Mustazihim Suhaidi Novri Jenita Marbun Nur Ardhi, Alfian Pratiwi, Elsa Radillah, Teuku rahma melati Revaldi Fauzi Riski Ferita Wahyu Rudi Faisal Sari, Febrina Sembiring, Rinawati Shinta Esabella Siti Nurjannah Siti Nurjannah Soni Fajar Mahmud Sri Wulan, Sri Srihandayani, Susy Suarlin, John Suhaidi, Mustazzihim Susy Sri Handayani Syamsiar, Syamsiar Tri Handayani Valian Yoga Pudya Ardhana Wulandari, Denok Yuliati, Tri Yusrizal Yusrizal