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All Journal Indonesian Journal of Electrical Engineering and Computer Science Advance Sustainable Science, Engineering and Technology (ASSET)
Yogan Jaya Kumar
Universiti Teknikal Malaysia Melaka
Chemistry Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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Feature-based approach and sequential pattern mining to enhance quality of Indonesian automatic text summarization Dian Sa'adillah Maylawati; Yogan Jaya Kumar; Fauziah Binti Kasmin
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1795-1804

Abstract

Indonesian automatic text summarization research is developed rapidly. The quality, especially readability aspect, of text summary can be reached if the meaning of the text can be maintained properly. Therefore, this research aims to enhance the quality of extractive Indonesian automatic text summarization with considering the quality of structured representation of text. This research uses sequential pattern mining (SPM) to produce This research use SPM to produce sequence of words (SoW) as structured text representation using PrefixSpan algorithm. Then, SPM is combined with feature-based approach using sentence scoring method to produce summary. The experiment result using IndoSum dataset shows that even though the combination of SPM and sentence scoring can increase the precision value of recall-oriented understudy for gisting evaluation (ROUGE)-1, ROUGE-2, and ROUGE-L, from 0.68 to 0.76, 0.54 to 0.69, and 0.51 to 0.72. Especially, combination of SPM and Sentence Scoring can enhance precision, recall, and f-measure of ROUGE-L that consider the order of word occurance in measurement. SPM increases ROUGE-L f-measure value of sentence scoring from 0.32 to 0.36. Moreover, combination of sentence scoring and SPM is better than SumBasic that used as feature-based approach in the previous Indonesian text summarization research.
Non-Verbal Cues in Interactive Systems: Enhancing Proactivity through Winking and Turning Gestures Siti Aisyah Binti Anas; Mazran bin Esro; Ahamed Fayeez bin Tuani Ibrahim; Yogan Jaya Kumar; Vigneswara Rao Gannapathy; Yona Falinie binti Abd Gaus; R. Sujatha
Advance Sustainable Science Engineering and Technology Vol. 7 No. 1 (2025): November-January
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v7i1.1011

Abstract

This investigation investigates the extent to which proactive behaviours in interactive objects—specifically animated eyes that exhibit behaviours such as blinking and turning—improve user interaction. Through a two-phase process, we investigate the influence of these behaviors on users’ perceptions of proactivity in both physical and virtual environments. In Phase I, we conducted a real-world study using a tangible box with animated eyes to evaluate user responses to expressive behaviours in single- and multi-person interactions. The results indicate that blinking significantly improves perceptions of the box’s intentionality and engagement, thereby fostering a more robust sense of proactivity. Phase II expands this investigation to a virtual environment, where 240 participants on Amazon Mechanical Turk (MTurk) participated, thereby validating the real-world findings. The online study confirms that perceived proactivity is consistently increased across contexts by blinking and turning. These findings indicate that integrating basic, human-like behaviors into interactive systems can enhance user engagement and provide practical advice for the development of sustainable, low-complexity interactive technologies. These discoveries facilitate the future development of resource-efficient and accessible human-computer interaction and robotic systems by simulating intentionality through minimal behavior.
Co-Authors Ahamed Fayeez bin Tuani Ibrahim Dian Sa'adillah Maylawati Fauziah Binti Kasmin Mazran bin Esro R. Sujatha Siti Aisyah Binti Anas Vigneswara Rao Gannapathy Yona Falinie binti Abd Gaus