Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Jurnal Informatika Universitas Pamulang
Nalda Kresimo Negoro
Magister Teknik Informatika - Universitas Amikom Yogyakarta
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Analisis Kebakaran pada Hutan dan Lokasi Lahan di Provinsi Riau Menggunakan Metode C4.5 Nalda Kresimo Negoro; Mardiana Mardiana; M. Izul Ula; Fajar Dwi Insani
Jurnal Informatika Universitas Pamulang Vol 7, No 1 (2022): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v7i1.17176

Abstract

Data mining is a step of the process that is useful and necessary to analyze the data that has been obtained from a particular situation with mathematical calculations. A decision tree (decision tree) is an algorithm that is widely used in data mining classification. One of the algorithms that can help produce decision tree outputs is the C4.5 algorithm. Data mining consists of preprocessing, evaluating patterns, and presenting knowledge from an application. The dataset used in forest fires is taken from the BMKG website and classified according to its attributes so that the data can be processed to produce output for decision-making. The classification process used to process datasets with specific methods can predict events such as weather forecasts and traffic jams to predict natural disasters. Forest fires are very detrimental disasters because they can pollute the environment, interfere with health such as breathing and vision, and weaken the economy of a region. This study aims to apply the C4.5 algorithm, which can analyze and predict forest fires in the Riau province. The implementation of the C.45 algorithm method with an average value attribute has an accuracy value of 92.54% and a decision tree, which is an accuracy value of 99.2% with an equation test and test results with a confusion matrix.
Co-Authors Fajar Dwi Insani M. Izul Ula Mardiana Mardiana