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Jurnal CoreIT
Published by Universitas Islam Negeri Sultan Syarif Kasim Riau
ISSN : 2460738X     EISSN : 25993321     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi published by Informatics Engineering Department – Universitas Islam Negeri Sultan Syarif Kasim Riau with Registration Number: Print ISSN 2460-738X | Online ISSN 2599-3321. This journal is published 2 (two) times a year (June and December) containing the results of research on Computer Science and Information Technology.
Arjuna Subject : -
Articles 162 Documents
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Implementation of BiLSTM-SVM Algorithm to Detect Fake News on Text-Based Media Liman, Felix; Carsten, Carsten; Sufinata, Sufiandy; Irviantina, Syanti; Winardi, Sunaryo
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 9, No 2 (2023): December 2023
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v9i2.18982

Abstract

Online media is one of the places where news can spread quickly and everyone can access it easily and freely. Not only real or valid news is spread on online media, but fake news can also be easily spread on online media, and readers sometimes do not realize that the news they read is fake. As a result, wrong opinions arise that can lead to disputes, as well as divisions between individuals or groups. This study implements the BiLSTM-SVM algorithm to detect fake news that is spread on one of the online media, namely Twitter. The steps taken are tidying up the news text (text preprocessing), converting every word from the news text into numbers in vector form (word embedding), processing the numbers, and then classifying the results of the processing with the BiLSTM-SVM model formed with TensorFlow 2.0 help, and see the performance generated by the BiLSTM-SVM algorithm. The results obtained include an accuracy rate of 86% and an F1 Score value of 87.5% in detecting news from data validation with the same news topic.
Integration of G2M Weighting and MOORA in Accurate Decision Making for Best Alternative Selection Setiawansyah, Setiawansyah; Wang, Junhai; Palupiningsih, Pritasari
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 11, No 2 (2025): December 2025
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v11i2.36679

Abstract

The goal of the integration of the G2M Weighting and MOORA methods is to produce the best alternative selection decisions that are more accurate and objective. By combining rational criteria weighting through G2M Weighting and alternative evaluation using MOORA, it is hoped that it can reduce bias and increase transparency in decision-making. In addition, this study compares alternative ratings from the application of the MOORA method and other weighting methods. The results of the evaluation and ranking of scholarship recipients using G2M weighting and MOORA, CF candidates managed to occupy the first position with a final score of 0.2727, showing the best performance among all candidates. In second place, UT candidates obtained a score of 0.2630, followed by DF candidates with a score of 0.2445 and SS candidates with a score of 0.2425. This approach makes it a very useful solution in the selection of the best alternatives in a wide range of multi-criteria decision applications. The results of the Spearman correlation test showed that the G2M weighting method had the highest correlation of 0.9879, which showed a very high similarity with the initial rating. The Entropy Weighting and CRITIC methods also showed a strong correlation, of 0.9515 and 0.9636, respectively, although there was slight variation in the alternate sequence. Meanwhile, the MEREC weighting has the lowest correlation of 0.9273, but still shows a very strong relationship. Overall, these results suggest that the G2M method produces rankings consistent with the initial rankings, with variations indicating sensitivity to criterion weighting.

Page 17 of 17 | Total Record : 162

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