Sentiment Analysis of Loudspeaker Regulations in Houses of Worship on Social Media Using Support Vector Machine Algorithm - Selly Novia Manihuruk; Mhd. Furqan; Aidil Halim Lubis (JURNAL TEKNOLOGI DAN OPEN SOURCE, 2025)
Social media is an online platform where users can share content or interact with each other through discussions and debates that involve sentiments, such as agreement or disagreement on various topics. User sentiments on social media can be utilized in multiple ways, such as to gauge public opinion regarding the issuance of Circular Letter Number SE 05 of 2022 by the Ministry of Religious Affairs, which provides guidelines for the use of loudspeakers in mosques and prayer rooms. Due to the high volume of comments on social media regarding this circular, a sentiment analysis system is necessary. The sentiment analysis system in this research employs the Support Vector Machine (SVM) algorithm to classify comments as positive or negative. A total of 350 comments were collected from each social media platform—Facebook, Twitter, YouTube, and Instagram—about the issuance of the circular. These comments were divided into 250 for training data and 100 for testing data on each platform. The training data from all platforms were combined, resulting in a total of 1000 training data. Based on system testing using the Support Vector Machine algorithm, the accuracy achieved was 72%. This result reflects the system's capability to analyze sentiments related to the guidelines for using loudspeakers in mosques and prayer rooms as stated in the circular