Analisis Algoritma C4.5 Terhadap Faktor Penyebab Menurunnya Potensi Belajar Siswa Pada Masa Pandemi

Abstract

At the end of 2019 the world was shaken by the Covid-19 outbreak. The Ministry of Education has also implemented a policy of studying at home online or online. When using the online learning system, it doesn't always run smoothly, there must be problems that can occur, namely problems such as students not understanding the material presented by the teacher and many students who only have one Android and there are even students who don't have Android at all, their environmental factors also do not support them to learn with focus. The purpose of this study was to determine the factors causing the decline in student learning potential during the pandemic using the c4.5 data mining method. The source of the research data was obtained from distributing questionnaires to high school students of the Family College Foundation. In this study, there are five criteria that influence the factors that cause the decline in student learning potential during the pandemic, namely: How to learn, study time, understanding of the material, assignment and environment. The calculation results state that the environmental criteria are the criteria that have the most influence on the factor of decreasing student learning potential. Tests were also carried out using the Rapidminer software and obtained an accuracy of 73.33%.

Prediksi Kepuasan Mahasiswa Terhadap Pelayanan Akademik Menggunakan Model Decision Tree

“…Penelitian sebelumnya [6] mengusulkan penggunaan algoritma C4.5 untuk mengukur tingkat kepuasan pelanggan. Hasil penelitian tersebut menghasilkan nilai akurasi sebesar 94%, dimana nilai ini didapat dengan menggunakan data observasi dan wawancara kepada pelanggan.…”

Market Basket Analysis Using Apriori Algorithm to Find Effective Fiscal Policy Mix with R Programming

“…Based on previous research, such as the research of Hakim & Akbar (2018), namely the analysis of market baskets using the Apriori algorithm based on the R language, then Rizaldi & Adnan (2021), namely the analysis of market baskets using the Apriori algorithm as a transaction case at 212 Mart Soebrantas Pekanbaru. Also, research by Fathurrahman, Pratama, & Al-mudzakir (2023) compared the Apriori algorithm and FP growth to market basket analysis on bakery sales data. The third object discussed in this study is very different and has never been discussed in previous studies, namely the instruments used to formulate fiscal policy.…”