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Journal : Jurnal Teknik

Pengembangan Multimedia Pembelajaran Interaktif Berbasis Android Menggunakan Smart Apps Creator (SAC) Huzaima Mas'ud; Arip Mulyanto; Bait Syaiful Rijal; Muthia Muthia; Maemunah M
Jurnal Teknik Vol 21 No 1 (2023): Jurnal Teknik
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37031/jt.v21i1.308

Abstract

The learning process today requires us to use various kinds of learning media to mediate various kinds of student learning styles, one of which is in terms of attracting students' interest in learning and improving learning outcomes. The purpose of this study is to see the advantages of SAC, especially the suitability of SAC to be used as a tool in the development of interactive multimedia learning, this research design will discuss the design of SAC for certain subject matter. In the development of this learning media using R&D research methods that have been modified according to the needs of media development. The results of this study concluded that from the aspect of the appearance of the learning media it was very interesting, the aspect of the content of the material was very feasible and the aspect of usefulness was very useful. The results of student assessment based on the display aspect get a percentage score of 53.3% or very interesting, student assessment based on the content aspect gets a percentage score of 56.7% or very feasible, while the usability aspect gets a percentage score of 56.7% or very useful.
Analisis Sentimen pada Aplikasi Translate Google Menggunakan Metode SVM (Studi Kasus: Komentar Pada Playstore) Ashari, Sri Ayu; Saputra, Muhammad Wahyu Ade; Larosa, Esta; Rijal, Bait Syaiful
Jurnal Teknik Vol 21 No 2 (2023): Jurnal Teknik
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37031/jt.v21i2.412

Abstract

This research aims to analyze reviews in understanding the opinions and emotions expressed by users regarding the Google Translate application on the Google Play Store using sentiment analysis. By using the Support Vector Machine (SVM) method in sentiment analysis of the Google Translate application, to get a better understanding of how users respond to the application. This can help developers improve the application experience, responding better to user needs and preferences. This user review analysis uses the SVM method. The measuring tool in this research uses, firstly, the Indonesian Lexicon as a tool to obtain positive and negative results, secondly, term frequency–inverse document frequency (tf-idf) as a support for the results of the evaluation. Google Translate app has a dataset of 1000 user reviews collected from Google play store. The results of analysis using Support Vector Machine produced 95% accuracy, with "no" as the result of the most positive and negative reviews out of 1580 reviews.