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All Journal Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) International Journal of Information Engineering and Science
Eva Widiyanti
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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.
Implementation of the Naive Bayes Model Multicategory for Analysis Sentiment Product Wardah on Shopee E-Commerce Mesra Betty Yel; Sopan Adrianto; Rasiban Rasiban; Eva Widiyanti
International Journal of Information Engineering and Science Vol. 2 No. 2 (2025): May : 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.v2i2.6

Abstract

The growth of information technology has driven changes in consumer behavior, one of which is through e-commerce platforms such as Shopee. This phenomenon has generated a large number of customer reviews, including those for local cosmetic products such as Wardah. These reviews serve as an important source of information for understanding customer perceptions and satisfaction levels. However, manual analysis of large and linguistically diverse datasets is inefficient and potentially subjective. This study aims to implement the multi-category Naive Bayes algorithm to classify the sentiment of Wardah product reviews on Shopee into three categories: positive, negative, and neutral. The data were collected using a web scraping technique and processed through a series of preprocessing stages including case folding, tokenization, stopword removal, stemming, and text cleaning. Subsequently, term weighting was performed using the TF-IDF method prior to classification. Model performance was evaluated using a confusion matrix as well as accuracy, precision, and recall metrics. The results indicate that the multi-category Naive Bayes algorithm achieved an accuracy of 86.00%, a precision of 86.63%, and a recall of 98.24%. This approach can assist business practitioners in objectively understanding customer opinions and supporting decision-making in business strategy and product development.
Co-Authors Betty Yel, Mesra Dessyanti Ryantina Rasiban Rasiban Rodhiyah Satria Wira Yudha SOPAN ADRIANTO Wealty Sweet Charollyn Pasaribu