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All Journal Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) International Journal of Information Engineering and Science
Dessyanti Ryantina
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering

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Implementasi Pengembangan Media Interaktif Berbasis Website Canva untuk Meningkatkan Minat Belajar Murid TK Go Ceria Cipayung Dessyanti Ryantina; Rodhiyah; Eva Widiyanti; Wealty Sweet Charollyn Pasaribu; Satria Wira Yudha
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 3 (2025): JULI-SEPTEMBER 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i3.3827

Abstract

This study aims to develop and test the effectiveness of Canva-based interactive learning media in increasing the learning interest of Go Ceria Cipayung Kindergarten students. The research method used is a qualitative approach with observation and interview techniques. The interactive media developed is in the form of a website that integrates animation features, interactive quizzes, and design elements that are appropriate for the age of kindergarten children. Evaluation was conducted through pre-test and post-test using learning interest scale. The results showed an increase in interest in learning, with 8 out of 10 children successfully completing the test with high scores based on observations and interviews with teachers. The findings indicate that utilizing Canva in early childhood learning can be an innovative solution to increase children's learning engagement and motivation.
Satisfaction Level Analysis QRIS Users Based on Experience and Perception Twitter Users/X Using Naive Baiyes Veri Arinal; Satria Wira Yudha; Muhammad Joko Umbaran Kharis Bahrudin; Dessyanti Ryantina
International Journal of Information Engineering and Science Vol. 2 No. 4 (2025): November : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v2i4.53

Abstract

QRIS (Quick Response Code Indonesian Standard) has become a widely used national digital payment standard. User satisfaction with this service needs to be monitored continuously to ensure its sustainability. This study aims to predict the level of QRIS user satisfaction based on their experiences and perceptions expressed organically on the Twitter social media platform. The method used is sentiment analysis with the Naive Bayes classification algorithm implemented using RapidMiner software. The research data was obtained from Twitter user comments collected through web scraping techniques. The text data then went through a preprocessing stage that included cleansing, stopword filtering, stemming, and tokenizing to be prepared as features ready to be processed by the model. The data was divided into training (80%) and testing (20%) subsets for model training and validation. The results showed that the Naive Bayes model was able to predict user satisfaction sentiment with an accuracy of 80.99%. These findings indicate that the model is highly accurate in identifying satisfied comments and sufficiently sensitive in detecting dissatisfaction. This study concludes that sentiment analysis of Twitter UGC data using Naive Bayes is an effective and efficient approach for predicting QRIS user satisfaction in real time. The practical implication of this study is to provide an automatic feedback system for service providers to monitor public sentiment and take targeted corrective actions.
Co-Authors Arinal, Veri Eva Widiyanti Muhammad Joko Umbaran Kharis Bahrudin Rodhiyah Satria Wira Yudha Wealty Sweet Charollyn Pasaribu