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Setyawan Widyarto
Universiti Selangor
Computer Science & IT

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Comparison of Seven Machine Learning Algorithms in the Classification of Public Opinion Sri Redjeki; Setyawan Widyarto
Tech-E Vol. 5 No. 2 (2022): Tech-E
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v5i1.1046

Abstract

Sentiment analysis is one way that is widely used to identify the beginning of public opinion in various fields of life which are associated with very massive and a lot of information through social media. This study aims to compare several algorithms in machine learning to see the best ability in sentiment classification. The research dataset uses a dataset of public opinion related to tourism in Indonesia. The number of datasets used is 10,228 twitter data that have been cleaned and labelled. The machine learning algorithm used is Logistic Regression, KNN, AdaBoost, Decision Tree, SVM, Random Forest and Gaussian. The seven algorithms for sentiment classification from the Twitter public opinion each produce a Gaussian accuracy of 0.52; SVM 0.78; KNN 0.98; Logistic Regression, Random Forest, Decision Tree, AdaBoost of 0.99. This study shows that the selection of the right machine learning algorithm will have a very good impact on the classification of public opinion through social media
Systematic Literature Review: Smart City Framework Riki Riki; Setyawan Widyarto; Saliyah Kahar
Tech-E Vol 5 No 1 (2021): Tech-E
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v5i1.667

Abstract

Smart cities are currently becoming the trend of large cities in the world and large cities in Indonesia. As the center of human civilization, cities cannot do without the problems of excess capacity and comfort. More and more people are migrating from the countryside to the cities, which brings new problems to the cities. Cities need to change to survive in the future. Strong indicators are needed to support cities, whether in terms of natural environment, society, communities, infrastructure, and education. In this article, we discuss a systematic literature review of research related to smart cities. The systematic literature review is divided into three stages, introduction stage, demographic analysis stage and result analysis. The results reveal important indicators of smart cities based on the conclusions of previous research
Co-Authors RIKI RIKI, RIKI Saliyah Kahar Sri Redjeki