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All Journal RABIT: Jurnal Teknologi dan Sistem Informasi Univrab ILKOM Jurnal Ilmiah Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Mitra Mahajana: Jurnal Pengabdian Masyarakat JAIA - Journal of Artificial Intelligence and Applications SATIN - Sains dan Teknologi Informasi

Hamdani -

STMIK Amik Riau

Author-ID : 2644041

Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Industrial & Manufacturing Engineering Public Health Social Sciences

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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

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.

Sentiment Analysis of Technology Utilization by Pekanbaru City Government Based on Community Interaction in Social Media Bunga Nanti Pikir; M. Khairul Anam; Hadi Asnal; Rahmaddeni; Triyani Arita Fitri; Hamdani
JAIA - Journal of Artificial Intelligence and Applications Vol. 2 No. 1 (2021): JAIA - Journal of Artificial Intelligence and Applications
Publisher : STMIK Amik Riau

Government services for the public are currently utilizing technology, especially in the city of Pekanbaru. The government has currently centralized all services for the public, both online and offline, in public service malls. The type of service that uses technology, especially for online services, has received criticism in online media such as Twitter. To see the public's response to Pekanbaru city government services, especially in terms of technology, this study will use sentiment analysis to see positive, negative, and neutral comments. The method used is to see the accuracy generated using the NaÃ¯ve Bayes Classifier (NBC) method. Bayes classifier is a statistical classifier, where the classifier can predict the probability of class membership of a data tuple that will fall into a certain class, according to the probability calculation. Accuracy results are obtained by dividing training data and testing data with a comparison of 70%:30% with an accuracy value of 55.56%, Precision 64%, recall 80%, f-score 71.2%.

Co-Authors Agustin Anam, M Khairul Bunga Nanti Pikir Edwar Ali Erlin Hadi Asnal, Hadi Helda Yenni, Helda Herwin Herwin, Herwin Johan Koko Harianto muhammad Fuad Rahmaddeni Rahmaddeni Rahmiati Sahli Andrean Sugiono Sugiono Susanti, Susanti Susi Erlinda T. Sy. Eiva Fatdha Tri Agustina Triyani Arita Fitri

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