SENTIMEN PERCAKAPAN PENGGUNA TWITTER PADA HASHTAG #NONHALAL DALAM TIPOLOGI EKSKLUSIVISME, INKLUSIVISME, PLURALISME DAN TOLERANSI BERAGAMA

Abstract

This study was conducted to analyze the negative sentiment of the impact of news coverage at a Padang restaurant in Jakarta with rendang innovation made from pork. This is unprincipled from the origins of the cultural philosophy, namely Adat Basandi Syara', Syara' Basandi Kitabullah associated with the principle of halal products as one of the characteristics of Padang food. However, it turns out that there are many public responses that view this as not reflecting tolerance in culture and religion, one of the social media used in analyzing these opinions and responses is the social media Twitter. This study uses a mix method approach with the data collection technique used is conversations (tweets) from the Twitter social media application with a special topic approach using the 'hashtag' feature. Data collection was carried out using the Twitter API (Application Programming Interface) tool. The text and sentiment analysis is carried out using several tools and stages of data analysis, including data mining assistance, namely using python with stages covering the process of crawling data, text preprocessing, language adjustment, and the results of sentiment classification (labelling) technically using Vader-TDIF. The results of these sentiments by researchers are then transformed into Alan Race's theory. This aims to apply, translate, and perceive in a simpler way social-psychological perceptions. Alan Race's typology which includes Exclusivism, Inclusivism, Pluralism is the basis for categorizing the sentiments of Twitter users in interpreting a popular issue. The sentiment results formed from the prediction model with the Naive-Bayes algorithm show the result that the percentage of dominant sentiment is neutral or represents pluralism with the highest yield, namely 47.9%. , negative sentiment represents exclusivism, namely 21.23%, and positive sentiment or inclusivism, namely 30.87% with an accuracy rate of 66.43%. By knowing the conditions of community sentiment and views, this research is expected to become a reference in decision making and increase the intensity of relevant campaigns on social media Twitter specifically in the context of religious and cultural differences in order to further enhance the understanding of tolerant religious moderation in a plural-multicultural society.