Analysis of School Community Sentiment towards Personal Data Protection Law Using Support Vector Machine (SVM) Method - Gusti Fachman Pramudi; Gerry Firmansyah; Budi Tjahjono; Agung Mulyo Widodo (Asian Journal of Social and Humanities, 2023)
This research aims to analyze the awareness status of the school community regarding the right to personal data protection, test and analyze the sentiments of the school community towards the implementation of the Personal Data Protection Law and as a means of outreach regarding personal data protection laws in the world of education, especially school community besides that to find out whether the Support Vector Machine method can be used as a method in conducting Sentiment Analysis research. The results of this study can be concluded that only 38% of the school community knows about this regulation while the other 62% still don't know much about this rule. Then for the use of the Support Vector Machine method which has been carried out five (5) trials using different variations of training data and test data produces an average accuracy rate of 85.97% with the highest results on training data and test data 50% - 50% that is equal to 88.00% and the lowest result is in the experiment of training data and test data of 90% - 10% which is equal to 84.44%. For the school community's sentiment towards the Personal Data Protection Act, it was 56% or as many as 496 of 887 words. which shows a neutral response and 8% or as many as 72 out of 887 sentiment words show a negative response.