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All Journal Agents: Journal of Artificial Intelligence and Data Science
Ridwan A. Kambau
Universitas Islam Negeri Makassar
Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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REKAYASA GAME EDUKASI ADAB DALAM BERSIKAP UNTUK ANAK KELAS 1-3 SEKOLAH DASAR BERBASIS ANDROID Rohada Nurman; Ridwan A. Kambau
AGENTS: Journal of Artificial Intelligence and Data Science Vol 1 No 2 (2021): Maret - Agustus
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1305.721 KB) | DOI: 10.24252/jagti.v1i2.20

Abstract

Adab is a very important part of education that relates to attitudes and values, both individually and socially. This research is motivated by the phenomena that occur today as a reflection of the decline of adab. The attitude and morals of the nation are getting worse. Seeing the importance of the role of adab in human life, it should be more serious to think about the concept of introducing and inculcating adab in attitude. The purpose of this study is to design an application for learning etiquette in attitude with a media game approach to help children in the process of forming attitudes according to adab. In conducting this research, the type of research used is an experimental method with a qualitative approach. The data collection method used in this research is in the form of observation and literature study. The design method used is the waterfall method and the testing technique used is BlackBox. The result of this research are a form of android - based education game. An application that can be used as a media towards manners education Keywords: Adab, Attitude, Game
PERBANDINGAN ANALISIS SENTIMEN ALGORITMA SUPPORT VECTOR MACHINE DAN NAÏVE BAYES TERHADAP TANGGAPAN PUBLIK TENTANG PEMBELAJARAN ONLINE DI MASA PANDEMI COVID-19 Yulia Ardana; Ridwan A. Kambau; Mustikasari
AGENTS: Journal of Artificial Intelligence and Data Science Vol 3 No 1 (2023): September - Februari
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (572.173 KB) | DOI: 10.24252/jagti.v3i1.46

Abstract

At the beginning of 2020, COVID-19 began to spread throughout the world, including Indonesia. The government continues to look for ways to prevent the chain from spreading, one of which is by implementing online learning. The background of this research is to use twitter to find out the response and public sentiment about online learning during the covid-19 pandemic. The purpose of this research is to find out public opinion about the application of online learning and also to compare the performance level of support vector machine and naïve Bayes algorithms. In conducting this research, the type of research used is qualitative research in order to be able to understand well what kind of phenomena experienced by the research subjects. The best sentiment analysis results are obtained by comparing two classification algorithms, support vector machine and naïve Bayes. Testing based on k-fold cross validation aims to obtain accuracy, precision, and recall values. The best algorithm will produce the right output with a higher test score.
Co-Authors Mustikasari Rohada Nurman Yulia Ardana