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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika International Journal of Informatics and Computing
Pendit, Ulka Chandini
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Computer Science & IT Electrical & Electronics Engineering

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Food and Physical Activity Tracking Application with Simple Dietary Pattern Analysis Setyadinsa, Radinal; Pendit, Ulka Chandini; Novi Trisman Hadi
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 1 (2025): Research Article, January 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.14234

Abstract

This study focuses on the development of a mobile application to track food intake and physical activity while offering simple dietary pattern analysis. The primary goal was to create an intuitive tool enabling users to log meals, record physical activities, and receive actionable feedback on caloric balance. Developed using Agile methodology, the application includes user-friendly interfaces for data entry, a dashboard for visualizing caloric intake and expenditure, and feedback to enhance users’ understanding of dietary habits. Results from a one week user testing phase demonstrated high user satisfaction, with participants appreciating the app’s simplicity and clarity in presenting health-related insights. The app effectively encouraged users to engage with their dietary and activity habits, promoting informed lifestyle decisions. However, limitations such as the lack of detailed macronutrient tracking and integration with wearable devices were identified, which could improve accuracy and broaden the app's appeal. Future improvements are suggested, including the addition of macronutrient analysis, wearable device compatibility, and features like goal-setting and gamification to enhance engagement. These findings indicate that a straightforward, user-friendly health tracking app can significantly increase health awareness and support behavior change, particularly for individuals new to health monitoring. The research highlights the potential of simple digital tools to foster sustainable health improvements while addressing users’ needs effectively.
Sentiment Analysis of Application X on The Impact of Social Media Content on Adolescent Mental Well-Being using Naïve Bayes Algorithm Rizal, Randi; Pendit, Ulka Chandini; Ramli, Nuraminah; Annisa, Siti
JICO: International Journal of Informatics and Computing Vol. 1 No. 1 (2025): May 2025
Publisher : IAICO

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Abstract

Since the pandemic, the use of social media has increased significantly. However, its presence has raised significant concerns about its impact on the mental well-being of teenagers. The pervasive influence of social media has led to substantial changes in the social system within society. Despite this influence, there is currently no comprehensive understanding of the specific impact of social media on mental health. To address this gap, this research proposes the use of sentiment analysis of social media posts with the Naive Bayes algorithm as an approach to identify and classify positive and negative sentiments in these posts related to the mental well-being of teenagers. This solution aims to provide a deeper understanding of the impact of social media content on this vulnerable demographic. In this study, a total of 555,361 social media posts were successfully collected and analyzed using the Naive Bayes algorithm, which was trained with a sample of 27,977 test data. The research results demonstrate that sentiment analysis with the Naive Bayes algorithm is effective in classifying social media sentiment, with 50.55% of the posts classified as positive and 46.97% classified as negative. The identified sentiment patterns have provided valuable insights into the positive and negative impact of social media content on the mental well-being of teenagers.
Co-Authors Novi Trisman Hadi Ramli, Nuraminah Rizal, Randi Setyadinsa, Radinal Siti Annisa, Siti