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Opinion Mining for Customer Satisfaction in Culinarypreneur Ventures Using Naive Bayes Cahyadi, Hadi; Rahayu, Sri; Rangi, Noah
Technomedia Journal Vol 10 No 2 (2025): October
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/5mqgtb60

Abstract

Examining consumer evaluations of food on social media provides relevant in- formation for anyone searching, especially immigrants and tourists. This infor- mation is also highly valuable for food stall owners and restaurant managers be- cause it helps them improve the quality of the food they serve based on customer feedback. However, sentiment analysis of food reviews often faces challenges due to inadequate data preprocessing, which leads to low classification accuracy. This study aims to improve sentiment recognition accuracy in food reviews by optimizing the feature attribute selection process in the classification model. The classification model employed in this research is Naive Bayes (NB), enhanced through a hybrid feature selection approach that combines the information gain (IG) algorithm and the genetic algorithm (GA). This combination is designed to maximize the selection of the most relevant feature attributes, thereby improving the model’s ability to identify positive, negative, and neutral sentiments in con- sumer food reviews on social media. The experimental results show that the hybrid IG-GA model achieved the highest accuracy rate of 93%, outperform- ing models that use individual algorithms. These findings demonstrate that the hybrid feature selection method effectively enhances the sentiment analysis performance of the Naive Bayes model. This study contributes to the develop- ment of food recommendation systems, the improvement of service strategies for culinary businesses, and supports the achievement of SDG 8 (Decent Work and Economic Growth) and SDG 9 (Industry, Innovation, and Infrastructure).
The Impact of Educational Information Systems on Learning Accessibility in Higher Education Sudadi Pranata; Arif Komara, Maulana; Amelia, Fhia; Rangi, Noah
CORISINTA Vol 2 No 2 (2025): August
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/corisinta.v2i2.132

Abstract

This study explores the impact of educational information systems on enhancing learning accessibility in higher education, as digital tools increasingly become integral to academic support, and student engagement. The main objective is to assess how these systems improve access to learning resources and facilitate communication, particularly for students from diverse backgrounds and with varying educational needs. Using a mixed-methods approach, this research combines quantitative analysis of accessibility metrics with qualitative insights from surveys and interviews with students and faculty across different higher education institutions. The findings show that educational information systems significantly enhance learning accessibility by providing flexible access to resources, facilitating real-time feedback, and supporting personalized learning paths. These systems also improve student engagement by enabling convenient access to materials and fostering a collaborative learning environment that accommodates different learning styles. However, the study identifies several barriers, including gaps in digital literacy, usability challenges, and unequal access to the necessary infrastructure, which can limit the effectiveness of these systems in reaching all students equally. Additionally, concerns around data privacy and system complexity are noted as areas needing attention to build user trust and ensure smoother system integration. The study concludes that while educational information systems hold great promise for improving accessibility and inclusivity in higher education, addressing these barriers through targeted training, digital equity initiatives, and robust data protection policies is essential for maximizing their potential. These insights offer valuable guidance for educational institutions aiming to create more inclusive learning environments through strategic integration of educational information systems.