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

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SISTEM INFORMASI PENCATATAN DAN PENGONTROLAN IBU HAMIL BERBASIS ANDROID (STUDI KASUS DESA KOLAI KABUPATEN ENREKANG) Ririn Syaputri; Mustikasari
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 (1047.813 KB) | DOI: 10.24252/jagti.v1i2.21

Abstract

The Maternal and Child Health Book (KIA) is the administrative book for pregnant women and midwives whenever control the health of the fetus during pregnancy until giving birth. The KIA book contains records of pregnant women as well as various information on how to maintain and care for the health of mothers and children. Therefore the KIA handbook is very important and must always be considered because it is an administrative completeness during control. It is also a guide for pregnant women in maintaining their health after giving birth during the postpartum period. In Kolai Village, pregnant women use KIA handbooks, so they are not very effective because easily scattered or even lost. Thus, this research can provide an effective solution, with an Android-based information system for recording and controlling pregnant women as a substitute for manual bookkeeping for pregnant women. The method used in system design is a prototype method with black box testing which is equipped with implementation as a system test and questionnaire with the results of the questionnaire being processed quantitatively. The results are in the form of recording and controlling pregnant women as an information system which is the main feature of the application.
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 Ridwan A. Kambau Ririn Syaputri Yulia Ardana