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All Journal AL ISHLAH Jurnal Pendidikan INOVTEK Polbeng - Seri Informatika MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JURTEKSI JSR : Jaringan Sistem Informasi Robotik Sains, Aplikasi, Komputasi dan Teknologi Informasi JAIA - Journal of Artificial Intelligence and Applications SATIN - Sains dan Teknologi Informasi
Susi Erlinda
STMIK Amik Riau
Aerospace Engineering Computer Science & IT Education Languange, Linguistic, Communication & Media Mathematics Other

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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.
Product Classification Based on Categories and Customer Interests on the Shopee Marketplace Using the Naïve Bayes Method Muhammad Oase Ansharullah; Wirta Agustin; Lusiana; Junadhi; Susi Erlinda; Fransiskus Zoromi
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.v2i2.888

Abstract

Marketplace is an electronic product marketing platform that brings together many sellers and buyers to transact with each other. The large variety of products sold on Shopee is one of the reasons this application is in great demand by all walks of life. However, the weakness of the large variety of products sold in a marketplace causes buyers who have no potential to buy these products. To overcome this problem, it is necessary to do a classification to determine which products are most in demand by customers. Product categories consist of: Clothing, Beauty Products, Daily Goods, Electronics, and Accessories. The classification method used is Naïve Bayes and the software used is WEKA. The next data collection is done by distributing questionnaires to the existing customers on social media namely, Whatsapp and Instagram, the distribution of the questionnaire is conducted through Google form. There are 90 questionnaires that will be distributed in this study. Some of the indicators asked in the questionnaire namely, do you like shopping online? And what marketplaces are commonly used. These results will be the training data. Interest categories are divided into 4 categories, namely: Very interested, Interested, Not interested, Very not interested. The results obtained in this study are clothing products (72 respondents) are products that are in great demand, daily goods products (7 respondents) are products of interest, beauty and electronic products (5 respondents) are products that are not in demand, and accessories (1 respondents ) is a product that is not very attractive to customers on the Shopee marketplace
Co-Authors -, Dwi Haryono -, Fachrizal -, Syapriadi -, Tashid -, Yelizar Abdul Muntholib Abdul Muntholib Ambiyar, Ambiyar Amelia Eka Putri Anam, M Khairul Astarilla, Liya Dedy Irfan Efrizoni, Lusiana Esi Tri Emerlada Fachrizal - Fransiskus Zoromi Hadi Asnal, Hadi Hamdani - Hamdani . Jamaris, Muhamad Junadhi Junadhi Karpen Khusaeri Andesa Mardainis Melda Royani Muhammad Oase Ansharullah Nasrul Sani Putri, Amelia Eka Rahmiati Rahmiati -, Rahmiati Syapriadi - T Sy Eiva Fatdha Torkis Nasution Tri Agustina Tri Agustina, Tri Unang Rio Wirta Agustin Yelizar -