Sentiment and Emotional Analysis of The Public Housing Savings Program (TAPERA) using Orange Data Mining - Fadly, Hawangga Dhiyaul; Jati, Handaru (Journal of Applied Informatics and Computing, 2025)
This study employs a text analysis methodology to assess public perception of the People's Housing Savings Program (TAPERA), by examining 3.078 tweets containing the keyword "tapera" using the Orange Data Mining application with two analytical approaches: the Valence Aware Dictionary and Sentiment Reasoner (VADER) for sentiment analysis and the Profile of Mood States (POMS) for emotional analysis. The sentiment analysis results indicate 1.481 tweets (48,2%) expressed negative sentiment, 830 tweets (27%) were neutral, and 767 tweets (24,8%) conveyed positive sentiment. These findings suggest that although there is a portion of positive responses toward the TAPERA policy, most of the public tends to express dissatisfaction or scepticism about the program. Furthermore, the emotional analysis identified depression as the most dominant emotion expressed by the public, appearing in 2.019 tweets (65,6%), followed by confusion (14,7%) and anger (9,6%). Positive emotions such as vigour and tension were recorded in significantly lower proportions, at 2,9% and 1,8%, respectively. These results illustrate that the public feels frustrated, confused, and anxious regarding the TAPERA policy, with minimal expressions of optimism or enthusiasm. This analysis highlights the need for a more transparent, educational, and data-driven communication approach to enhance public understanding, trust, and participation in the TAPERA policy. Therefore, the government must design more effective outreach strategies to address public concerns and ensure the successful implementation of this program.