Evolutionary Fuzzy Rule-Based Classification System dalam Analisis Sentimen terhadap Danantara

Abstrak

In order to improve the Indonesian economy, the government launched Danantara, a Sovereign Wealth Fund that serves to manage data owned in investment instruments such as stocks, bonds or property where the profits from this are returned to the state into the APBN, besides that Danantara aims to stabilize the economy and drive national development. However, with the huge amount of money being managed and its vital purpose, the existence of danantara has been the subject of much debate. Some people support the existence of danantara because it can help raise the Indonesian economy, but others reject the existence of danantara because they are afraid of being a place for corruption if there is mismanagement of large funds and can disrupt the current Indonesian economy. For this reason, the research aims to analyze public sentiment using the Evolutionary Fuzzy Rule-Based Classification System which has an approach to fuzzy rules that can overcome the level of ambiguity in sentiment analysis. The stages carried out in this research start from data collection using the webscraping method on platform x, data cleaning, data pre-processing, data labeling, classification of Evolutionary Fuzzy Rule-Based Classification System and at the end of the evaluation stage. The results obtained in this study are the accuracy and recall rates of 69%, then precision 72% and f1-score 70%. This shows that the Evolutionary Fuzzy Rule-Based Classification System model is less suitable in analyzing and classifying public sentiment regarding the existence of danantara.