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All Journal Andalasian International Journal of Applied Science, Engineering, and Technology Proceedings Series on Social Sciences & Humanities Bulletin of Social Informatics Theory and Application
Wahyuningsih, Kartika
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Energy Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Social Sciences

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Social media learning on Indonesian university students Istiyanto, S. Bekti; Priyantono, Mochammad Bagus; Rifai, Muhammad Abdul Faiz; Wahyuningsih, Kartika; Fansyiari, Dzanun; Ramdhani , Lalu Gilang Obidia
Bulletin of Social Informatics Theory and Application Vol. 5 No. 1 (2021)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v5i1.433

Abstract

This study aims to compare social media as appropriate learning media for University students at Universitas Negeri Malang in the era of the covid-19 pandemic. The method used in this study is EUCS (End-user computing satisfaction) with a sample of 100 people. This study indicates that the google-classroom media is more in demand as a learning medium in terms of satisfaction by UM students. All the variable values are superior to the other two social media, namely Facebook and Schoology.
The Influence of Learning Models Core (Connecting, Organizing, Reflecting and Extending) to Critical Thinking Ability and Achievement Students of Grade V of Tritih Kulon 05 State Elementary School Wahyuningsih, Kartika; Purwandari, Ristiana Dyah
Proceedings Series on Social Sciences & Humanities Vol. 25 (2025): Proceedings of International Conference on Social Science (ICONESS)
Publisher : UM Purwokerto Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/pssh.v25i.1734

Abstract

This research aims to determine the effect of the CORE (Connecting, Organizing, Reflecting and Extending) Learning Model on students' critical thinking abilities and learning achievement. This research uses a quantitative experimental research type with a quasi-experimental method. The research sample in the VA class was 20 students as the experimental group and 21 students in the VB class as the control group. The data collection method uses the test method, 10 multiple choice questions to test learning achievement and 4 essay questions for critical thinking skills. Based on the results of data processing on the posttest scores through the Independent Sample T-test, the critical thinking ability variable showed a result of 0.03 < 0.05, meaning Ha was accepted. processing the posttest score data through the Independent Sample T-test for the learning achievement variable also showed a result of 0.00 < 0.05, meaning Ha was accepted. Thus, the CORE (Connecting, Organizing, Reflecting and Extending) Learning Model has a positive effect on students' critical thinking abilities and learning achievements.
Analysis of Public Sentiment Towards the Prabowo-Gibran Administration Using Deep Neural Network Algorithms Wahyuningsih, Kartika; Istiqlal, Adib Ahmad; Armin, Armin
Andalasian International Journal of Applied Science, Engineering and Technology Vol. 6 No. 1 (2026): March 2026
Publisher : LPPM Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/aijaset.v6i1.257

Abstract

The leadership of Prabowo and Gibran has drawn significant public attention, particularly in the early phase of the administration. In the digital era, public opinions both supportive and critical are widely expressed through platforms such as YouTube, generating large volumes of data. Manual analysis of this data is impractical, while previous machine learning and deep learning approaches have produced suboptimal results. Therefore, this study applies a Deep Neural Network (DNN) to analyze public sentiment more effectively. The process involves inputting a dataset derived from YouTube comments obtained through scraping using the v3 API. This is followed by preprocessing, labeling, data splitting, applying IndoBERT word embedding, and DNN, with the final step being evaluation using a confusion matrix. The results of this study indicate that as the depth of the hidden layers increases, the accuracy improves, though not significantly. The best model performance was obtained by without SMOTE using a depth of 6 hidden layers, with an accuracy of 68.84%, precision of 67.5%, recall of 68.84%, and an F1 score of 64.22%.
Co-Authors Armin Armin, Armin Fansyiari, Dzanun Isani Kulup, Luluk Istiqlal, Adib Ahmad Priyantono, Mochammad Bagus Ramdhani , Lalu Gilang Obidia Rifai, Muhammad Abdul Faiz Ristiana Dyah Purwandari S. Bekti Istiyanto, S. Bekti