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All Journal Building of Informatics, Technology and Science PREDATECS: Public Research Journal of Engineering, Data Technology and Computer Science
Ardiansah, Yoga
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Application of The Fuzzy Mamdani Method in Determining KIP-Kuliah Recipients for New Students Ardiansah, Yoga; Luchia, Nanda Try; Hastari, Delvi; Rifat, T. M. Fathin; Rachfaizi, Rendhy; Putri, Nanda Aulia; Ginting, Ella Silvana
Public Research Journal of Engineering, Data Technology and Computer Science Vol. 2 No. 1: PREDATECS July 2024
Publisher : Institute of Research and Publication Indonesia (IRPI).

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/predatecs.v2i1.1087

Abstract

Lectures are the last level of education passed. However, the opportunity to obtain further education cannot be owned just like that by everyone because of the economic factors they experience. Therefore, an assessment method is needed to support the decision of KIP-Kuliah recipients at the lecture level for new students within the Faculty of Science and Technology, Sultan Syarif Kasim Riau State Islamic University. This research applies the Fuzzy Mamdani algorithm with Fuzzy Logic and is expected to be able to provide recommendations for worthy scholarship recipients so that the assistance provided is right on target. The results showed that 26,7% of students received the rejected status. Several experiments conducted, illustrate the performance of Fuzzy Logic in this research is very powerful in determining policies and as decision support. The implementation of the research results recommends the best selection from a series of decisions making.
Analisis Sentimen Komentar Perplexity AI di X Tentang Pendidikan Menggunakan Support Vector Machine Ardiansah, Yoga; Monalisa, Siti; Muttakin, Fitriani
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6396

Abstract

Chatbots with Artificial Intelligence are increasingly popular in everyday life. Due to its ability to reason and convey information expressively, Artificial Intelligence (AI) using Natural Language Processing (NLP) models can communicate like humans. Users find one of Perplexity's AI chatbots interesting because it can pinpoint sources of information. As time goes by and the number of Perplexity users increases, sentiment analysis is used to measure user happiness. This sentiment analysis serves as the data source for this research, helping understand how users react to social media X (Twitter). The Support Vector Machines (SVM) method was used in this study, where SVM maximises the distance (margin) between data groups to determine the ideal hyperplane. According to the survey, 90.11% of respondents expressed positive sentiments, 5.30% expressed negative opinions, and 4.69% expressed neutral sentiments. Using a ratio of 80% training data and 20% test data, the f1 score reached 96%, with accuracy and precision of 92% each.
Co-Authors Ginting, Ella Silvana Hastari, Delvi Luchia, Nanda Try Muttakin, Fitriani Putri, Nanda Aulia Rachfaizi, Rendhy Rifat, T. M. Fathin Siti Monalisa