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Journal : JAIA - Journal of Artificial Intelligence and Applications

SMART method utilization for meetinghouse elections in Pekanbaru City M. Khairul Anam; Purwanto; Agustin; Aniq Noviciatie Ulfah
JAIA - Journal of Artificial Intelligence and Applications Vol. 1 No. 1 (2020): JAIA - Journal of Artificial Intelligence and Applications
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (772.491 KB) | DOI: 10.33372/jaia.v1i1.632

Abstract

Choosing and looking for information about the meetinghouse in Kota Pekanbaru is a problem for people in need. A Distance of distant location and limited information obtained. This application is built based on Android using Simple Multi-Attribute Rating Technique (SMART) method, there are several criteria used are rental price, capacity, and facilities. The application is built using the JAVA programming language with Android Studio. This system design analysis uses the Unified Modeling Language (UML). The results that this application can help users to choose existing meetinghouses in Pekanbaru City using the SMART method. The search result is a list of meetinghouse names in which there are various information about the meetinghouse and the location to the meetinghouse. The test results of the built-in application can work well and can address the problems faced by the user in determining the multipurpose building elections.
Neural Network Method in Text Message Categorization of Online Discussion Erlin; Johan; Triyani Arita Fitri; Agustin; Hamdani
JAIA - Journal of Artificial Intelligence and Applications Vol. 1 No. 2 (2021): JAIA - Journal of Artificial Intelligence and Applications
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (484.401 KB) | DOI: 10.33372/jaia.v1i2.704

Abstract

This paper presents research in neural network approach for text messages categorization of collaborative learning skill in an online discussion. Although a neural network is a popular method for text categorization in the research area of machine learning, unfortunately, the use of neural network in educational settings is rare. Usually, text categorization by neural network is employed to categorize news articles, emails, product reviews, and web pages. In an online discussion, text categorization that is used to classify the message sent by the student into a certain category is often manual, requiring skilled human specialists. However, human categorization is not an effective way for a number of reasons; time- consuming, labor-intensive, lack of consistency in a category, and costly. Therefore, this paper proposes a neural network approach to code the message automatically. Results show that neural networks achieving useful classification on eight categories of collaborative learning skills in an online discussion as measured based on precision, recall, and balanced F-measure.