SVM OPTIMIZATION WITH INFORMATION GAIN FEATURE SELECTION TO INCREASE THE ACCURACY OF SENTIMENT ANALYSIS OF INCREASING THE COST OF THE HAJJ
Abstract
Everyone's freedom to express their opinions is now poured into a platform known as social media. This platform allows people in the digital world to communicate with each other using the internet. YouTube is one of the most popular social media platforms worldwide. In 2023, the Government, in this case the Ministry of Religious Affairs of the Republic of Indonesia and Commission VIII of the House of Representatives have approved the Hajj Travel Cost 1444 H/2023 AD with a range of Rp90,050,637.26 per regular pilgrim. In contrast to the government of the Kingdom of Saudi Arabia, which implemented a policy of reducing the cost of the Hajj package by 30% from 2022. This has caused pros and cons to the hajj cost increase. Public opinion on social media is the focus of this research to conduct sentiment analysis. Sentiment analysis has been developed through various methods, but there are still many challenges to produce accurate sentiment analysis. The challenges include accuracy, binary classification, data sparsity, and polarity shift. One of the challenges in improving accuracy is the focus of this research. In this study, the Support Vector Machine method is applied and Information Gain feature selection is added. The accuracy results obtained in this study are the Support Vector Machine method (87%) and Support Vector Machine combine with information gain feature selection (89%). It can be concluded, the support vector machine method combined with information gain feature selection proves an increase in accuracy by 2%.
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References
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