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p-Index From 2021 - 2026
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This Author published in this journals
All Journal Engineering, Mathematics and Computer Science Journal (EMACS) Advance Sustainable Science, Engineering and Technology (ASSET)
Dwinanda Kinanti Suci Sekarhati
Universitas Bina Nusantara
Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics

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Combating Hoax and Misinformation in Indonesia Using Machine Learning What is Missing and Future Directions Sekarhati, Dwinanda Kinanti Suci
Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 6 No. 2 (2024): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v6i2.11556

Abstract

According to survey from several organizations in Indonesia to 10.000 respondents with age range from 13-70 years at 2022 and 2023, 56% respondents are mainly found hoax and misinformation on social media and online media platform with 45% respondents are hesitant with their ability to differentiate true information with hoax. Most of the hoax and false information researchers in Indonesia also still have some challenges such as on the dataset detection method. This research will use the systematic literature review using PICOC, inclusion-exclusion rules, and quality’s checklist. The results based on 20 papers are data crawler’s application usage, labelling, and text pre-processing are the major steps to improve the dataset with more than 10.000 data. There are also already some advance methodologies for hoax and misinformation detection in text form such as graph-based learning and special architecture design, yet there’s still a little number for the detection in media form. The recommendation includes the dataset improvement steps, literature, and methodologies in media form.
Advancing Adaptive and Personalized E-Learning Systems: A Systematic Literature Review Amastini, Fitria; Kinanti Suci Sekarhati, Dwinanda; Puspitasari, Maya
Advance Sustainable Science Engineering and Technology Vol. 7 No. 2 (2025): February-April
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/m82zg802

Abstract

With the rise of Information and Communication Technologies (ICTs), adaptive e-learning has become a promising method for enhancing educational practices. This study reviews current research on personalized adaptive e-learning systems and proposes a mobile-based design to addressing the requirements toward Industry 4.0 and Society 5.0. Using a systematic literature review methodology by Kitchenham and Charters, 28 studies were analyzed further. The findings suggest a necessity for clearer definitions of "personalized" and "adaptive" learning and categorize adaptive e-learning designs into four models: learning materials, learner characteristics, pedagogical approaches, and learning structure systems. The findings show there is still a lack of clarity in the definitions of "personalised" and "adaptive" learning, emphasizing the importance of more standardized terminology. The proposed system dynamically customized learning content material based on user preferences, cognitive abilities, and performance metrics, demonstrating the potential for increased students’ engagement and their learning outcomes. This study focusses on the possibilities of blockchain-based open educational resources, artificial intelligence, and gamification as for more engaging personalized student test to improve adaptive learning environments. Future study should confirm the suggested paradigm using empirical investigations and assess its usefulness in promoting lifelong learning.
Co-Authors Amastini, Fitria Maya Puspitasari, Maya