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All Journal AL-ISHLAH: Jurnal Pendidikan Proceedings of the 1st UR International Conference on Educational Sciences JOURNAL OF ENGLISH FOR ACADEMIC JEE (Journal of English Education) ELP (Journal of English Language Pedagogy) JAIA - Journal of Artificial Intelligence and Applications
Astarilla, Liya
STMIK AMIK Riau
Humanities Computer Science & IT Education Languange, Linguistic, Communication & Media Social Sciences

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Expert System to Detect the Level of Parental Stress in Online Learning by Using Forward Chaining Method Susi Erlinda M. Kom; Rika Desmalita; Liya Astarilla Dede Warman
JAIA - Journal of Artificial Intelligence and Applications Vol. 2 No. 2 (2022): JAIA - Journal of Artificial Intelligence and Applications
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33372/jaia.v2i2.879

Abstract

This research was aimed to make an expert system application to detect and identify the parental stress level in online learning by using the Forward Chaining method. The system was designed and implemented based on Desktop by using basic programming language. The data were collected through questionnaire consisted of 30 questions. The final score would determine the stress level of the respondents. The respondents were chosen by using random sampling technique. XAMPP data with the results obtained from 150 respondents who have educational backgrounds; elementary school (4 respondents), junior high school (6 respondents), high school (120 respondents), associate degree (11 respondents), bachelor degree (9 respondents).There were 123 respondents do not work, and 27 respondents were working parents. The findings showed that from 150 respondents there were 22% or 33 respondents were at normal level, 6% or 9 respondents were at mild level of stress, 8% or 12 respondents were at moderate level of stress, and 64% or 96 respondents were at severe level of stress. It was concluded that this application can be used to detect the parental stress level in online learning. It was also expected through the use of this application can help parents to detect their stress level earlier and find solution of it in order to avoid the negative impact of their problems.
Empowering Introvert Students: How Artificial Intelligence Applications Enhance Speaking Ability Liya Astarilla Dede Warman; Susi Erlinda; Tashid Tashid; Karpen Karpen; T Sy Eiva Fatdha
AL-ISHLAH: Jurnal Pendidikan Vol 15, No 4 (2023): AL-ISHLAH: JURNAL PENDIDIKAN
Publisher : STAI Hubbulwathan Duri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35445/alishlah.v15i4.4435

Abstract

The rapid development of technology has increased the use of Artificial Intelligence (hereafter, AI) applications to improve students’ English skills, especially in speaking skill. This study aimed to investigate the effectiveness of AI applications to improve the introvert students’ speaking ability. Pre-experimental one group pre-test and post-test design was utilized in this study. This study conducted with 85 introvert students from two universities in Riau, Indonesia chosen by using MBTI test and purposive sampling technique. The data were collected through the questionnaire and speaking test. The data were analyzed by using SPSS 25th version to find out the descriptive statistic, normality test, and paired sample t-test. This finding shed light AI applications were effective in improving the introvert students’ speaking ability. It was proved that the t-test was higher than the t-table value (12.8231.663) with the level of significance p0.05. In short, there was significant difference on the students’ speaking ability before and after using AI applications for English speaking practiced. In conclusion, AI applications can be implemented to improve university students’ speaking ability.
Co-Authors -, Tashid Ambiyar, Ambiyar DEDE WARMAN Fransiskus Zoromi Karpen Mardainis Rika Desmalita Susi Erlinda Susi Erlinda M. Kom T Sy Eiva Fatdha Warman, Dede