Articles

Sentiment Analysis Based on Questionnaires: A Case Study on the Use of Induction Stove

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Indonesia’s reliance on subsidized Liquefied Petroleum Gas (LPG) for household cooking places a significant burden on the national energy subsidy budget and increases dependence on imported fossil fuels. As part of the clean energy transition strategy, the Indonesian government has promoted the conversion from LPG stoves to electric induction stoves. However, public acceptance and actual post-use experiences at the household level remain diverse and insufficiently examined empirically. This study aims to analyze public sentiment toward induction stove use based on post-adoption user reviews to identify factors that encourage interest and reveal existing adoption barriers.

This study employs a machine learning–based sentiment analysis approach using primary data collected through open-ended questionnaires distributed to induction stove users. A total of 265 valid textual responses were analyzed. Text preprocessing was conducted using Python with the NLTK and Sastrawi libraries, including data cleaning, case folding, tokenization, stopword removal, stemming, and duplicate removal. Sentiment classification was performed using the Term Frequency–Inverse Document Frequency (TF-IDF) method and the Naive Bayes algorithm, while WordCloud visualization was applied to identify dominant keywords.

The results indicate a relatively balanced sentiment distribution, with positive sentiment accounting for 33.6%, neutral sentiment 32.5%, and negative sentiment 34.0%. Positive sentiment is mainly associated with energy efficiency, safety, and ease of use, whereas negative sentiment is driven by concerns regarding initial costs and electricity dependence. Neutral sentiment reflects an evaluative phase among users. These findings provide empirical insights to support user-oriented policies and strategies for accelerating the sustainable adoption of induction stove technology in Indonesia’s clean energy transition.

Optimizing User Experience: A Data-Driven Approach to Enhancing B2B Invoicing Efficiency across Multiple Platforms PT Pakar Digital Global

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This study is a deep dive into applying data-driven decision-making strategies to enhance user experience and efficiency in B2B invoicing across multiple platforms at Paper.id. Given the fintech industry’s rapid evolution, maintaining a competitive edge requires constant innovation, particularly in user activation and retention within the first month of usage. This research employs a comprehensive data analysis framework, integrating Time Series Analysis, Descriptive Analysis, and Correlation Analysis methods to extract actionable insights from user data stored in MySQL databases. The study also incorporates strategic planning tools like SWOT and TOWS analysis to identify and implement UI/UX enhancements using the Agile Scrum methodology. The effectiveness of these interventions is evaluated through a robust post-analysis, comparing metrics before and after the implementation across mobile and desktop platforms. Results demonstrate a significant improvement in user activation and retention rates on mobile platforms, validating the efficacy of the applied strategies. This paper contributes valuable insights into optimizing user experience in a dynamic market, emphasizing a structured, iterative approach to achieving sustained user engagement and business growth.

Investigating Factors Influencing Customer Churn in the Online Bill Payment Services

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In Indonesia’s growing digital economy, the high churn rate in online services, such as bill payment platforms, is a critical concern. An example is BillsXYZ, a pseudonym used in this research for confidentiality, where similar services are readily available, and customer switching is effortless. The study conducted an analysis of the external environment to gain insights into the competitive landscape of the market. Using the Theory of Planned Behavior, a framework including key elements like customer experience and satisfaction, price and promotions, service quality, social influence, brand image, ease of use, and features of the service. The research involved 110 survey participants and four detailed interviews. Key findings from the analysis indicate that while there is moderate satisfaction with the online bill payment service, there are areas that require improvement, including recurring payment failures, limited availability of certain payment methods, and insufficient awareness of certain features. To address these issues and enhance customer retention, recommendations were put forth, such as increasing feature awareness, improving service quality, and implementing strategic promotions. This study provides valuable insights for online bill payment services to improve customer retention strategies.