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All Journal 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

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Journal : JAIA - Journal of Artificial Intelligence and Applications

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The Use of Panel Data Regression to Identify Students Reading Interest in the Library Susi Erlinda; Tashid; Ambiyar; Liya Astarilla Dede Warman; Mardainis; Fransiskus Zoromi
JAIA - Journal of Artificial Intelligence and Applications Vol. 2 No. 1 (2021): JAIA - Journal of Artificial Intelligence and Applications
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (577.405 KB) | DOI: 10.33372/jaia.v2i1.785

Abstract

Library visit is an indicator of college academic literacy. The current problem was a decrease on the students’ visit and read at the library of STMIK Amik Riau. Based on the visit data in the library, there was a reduction of the students’ visit for each year, as well as books lent by the students has decreased significantly. The purpose of this study was to identify the correlation between the library facilities and the library services on the students’ reading interest at the library of STMIK Amik Riau by using Panel Data. This study used qualitative and quantitative approach. The population of this study were the visitors at STMIK Amik Riau Library that chosen by using simple random sampling. The data were collected through observation, interviews, questionnaires and documentation. The method used to identify the interest on the students’ to read in the library was Panel Data regression. The procedures of this method were to determine the Panel Data Regression Model Estimation, the selection of Panel Data Regression Model (Estimated Technique) which includes the F Statistical Test (Chow Test), Hausman Test, and Lagrange Multiplier Test. Furthermore, conducted testing the Classical Assumptions (Multicollinearity and Heteroscedasticity) which includes the Multicollinearity test and heteroscedasticity test, followed by a feasibility test (Goodness of Fit) with the F-test hypothesis and Partial t-test. The result of this study showed that there was a correlation between the library facilities and the library services on the students’ reading interest at library of STMIK Amik Riau.
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.
Co-Authors -, Tashid Ambiyar, Ambiyar DEDE WARMAN Fransiskus Zoromi Mardainis Rika Desmalita Susi Erlinda Susi Erlinda M. Kom Warman, Dede