Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Indonesian Journal of Data and Science
Nurul Fitri H, Sarah FIla
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Mathematics

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

Found 1 Documents
Search
Journal : Indonesian Journal of Data and Science

 1 
Comparative Analysis of Machine Learning Algorithm Variations in Classifying Body Shaming Topics on Social Media X Nurul Fitri H, Sarah FIla; Fattah , Farniwati; Azis, Huzain
Indonesian Journal of Data and Science Vol. 5 No. 2 (2024): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v5i2.82

Abstract

Machine learning is an approach in computer science where systems or models can learn from data and experience to improve performance or perform specific tasks. There are several popular machine learning algorithms, such as naïve bayes, decision tree, K-NN, and SVM. This study aims to compare the performance of accuracy, precision, recall, and F-1 score in sentiment analysis of body shaming topics on Social Media X (formerly known as Twitter) by applying decision tree, K-NN, and SVM methods and identifying the most effective algorithm in classifying the data. Based on the classification performance testing results, it can be concluded that the classification method using the trigram feature model provides the best performance compared to other methods. The trigram model is able to achieve high recall, particularly in recognizing positive classes, without significantly compromising accuracy
Co-Authors Fattah , Farniwati Huzain Azis