ANALYSIS OF TWITTER USER SENTIMENT ON PERPPU CREATION OF WORK USING PSO- BASED SUPPORT VECTOR MACHINE (SVM) METHOD

Muhamad Adyaputra Yostira (Universitas Widyatama, Bandung)
Ai Rosita (Universitas Widyatama, Bandung)

Jurnal Darma Agung
Vol 30 No 1 (2022): APRIL

analysis sentiment Twitter users against Regulation Government Replacement Copyright Law ( Perppu ) . Work use Support Vector Machine (SVM) method . Objective from study This is For know view public to policy the through analysis sentiment on Twitter data. The SVM method is used For classify sentiment Twitter users to be three category , that is positive , negative , and neutral . Data used in study This obtained from Twitter using crawling and scraping data techniques . After successful data collected , preprocessing and processing of data for _ produce a SVM classification model . Result of study show that part big Twitter users have view negative to Perppu Create work . In classification sentiment , the percentage of tweets with sentiment negative reached 54%, meanwhile sentiment positive only reached 25%, and sentiment neutral by 21 %.From results analysis sentiment that , can concluded that policy Perppu Create Work No popular among _ the Twitter community . Study This can become source information for parties related in respond and evaluate policy controversial government .