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All Journal Jurnal Informatika Insoded Journal (International Social and Education Journal)
Rendy Saputra
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Computer Science & IT Education Social Sciences Other

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THE INFLUENCE OF LEARNING MOTIVATION TOWARD STUDENT ACHIEVEMENT LEARNING CLASS V SD CAMPANG THREE WEST LAMPUNG: Case Studies on IPS Subjects Rendy Saputra
INSODED Journal (International Social and Education Journal) Vol. 1 No. 1 (2018): Insoded Journal (International Social and Education Journal)
Publisher : Universitas Nahdlatul Ulama Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (694.02 KB)

Abstract

This study aims to find a picture related to the influence of learning innovation on student achievement in SD N Campang Tiga, West Lampung. This study aims to: 1) find out the picture of student motivation in SD N Campang Tiga West Lampung, 2) to find a picture of student achievement in SD N Campang Tiga West Lampung, and 3) to find out how much influence the motivation to learn on student achievement at SD N Campang Tiga, West Lampung. The study was conducted using a quantitative approach to answer initial hypotheses (H0) there was no positive and significant effect between learning motivation on student achievement, and / or (H1) there was a positive and significant effect between learning motivation on student achievement. The results of data analysis showed that learning motivation had a positive and significant effect on student achievement with an influence of 18.2% and the rest (81.8%) was influenced by other factors.
Youtube Comment Sentiment Classification System With Naive Bayes TF-IDF Using Laravel IDX normawati, dwi; Rendy Saputra; Hendrik Fery Herdiatmoko
Jurnal Informatika Vol. 19 No. 1 (2025): January 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jifo.v19i1.a30441

Abstract

The development of technology has enhanced social interactions through social media platforms like YouTube, making user comments a vital data source for sentiment analysis. One emerging issue is the lack of understanding regarding consumer perceptions of smartphone brands in Indonesia, which can be explored further through YouTube comments. This study aims to build a sentiment classification system for YouTube comments related to smartphone brands in Indonesia in 2024 using the Naïve Bayes Classifier algorithm with TF-IDF weighting and FastText features. Data was collected using the YouTube Data API, followed by preprocessing, labeling, and feature extraction stages. The model was optimized through GridSearchCV and evaluated with a Confusion Matrix, achieving an accuracy of up to 97%. The system was implemented as a Laravel-based web application, providing an interface for dataset management, model training, and sentiment visualization. This research also includes the integration of IDX Projects with Laravel, enabling more efficient data management and interactive presentation of sentiment analysis results. The findings demonstrate the effectiveness of this method in classifying positive and negative sentiments, which can help users understand consumer preferences for various smartphone brands.
Co-Authors Dwi Normawati, Dwi Hendrik Fery Herdiyatmoko