Author(s):
1. RANGGA PRADIPTA:
Information Systems Management Department, BINUS Graduate Program – Master of Information
Systems Management, Bina Nusantara University, Jakarta, Indonesia
2. RIYANTO JAYADI:
Information Systems Management Department, BINUS Graduate Program – Master of Information
Systems Management, Bina Nusantara University, Jakarta, Indonesia
Abstract:
This research is a sentiment analysis of opinion data obtained from the Twitter social network about the palm oil industry in Indonesia. The opinion data used is text in Indonesian to show the palm oil industry in Indonesia and text in English to show issues of the palm oil industry happening globally. The palm oil industry in Indonesia is one of the strategic industries engaged in agriculture, so it is necessary to monitor public sentiment with information on the Internet, especially on social media. This research has produced a model for classifying public opinion on the palm oil industry from Twitter data. The data collection technique used is the Twitter Developer API, and it obtained 14,048 words for Indonesian and 12,421 words for English. This data collection begins in July and ends in September 2021. This study uses a machine learning model with the Naïve Bayes Classifier and Support Vector Machine algorithms to separate sentiment into two labeling classes, namely positive and negative, then compares which algorithm best serves to classify opinion data. The model generated by the Naive Bayes algorithm has the highest accuracy value, namely for domestic (Bahasa Indonesia) data of 82% and international (English) data of 85%.
Page(s):
4532-4542
DOI:
DOI not available
Published:
Journal: Journal of Theoretical and Applied Information Technology, Volume: 100, Issue: 12, Year: 2022
Keywords:
machine learning
,
Sentiment analysis
,
Palm Oil Industry
,
Naïve Bayes
,
support vector machine SVM
References:
References are not available for this document.
Citations
Citations are not available for this document.