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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics Jurnal Layanan Masyarakat (Journal of Public Service)
Fakhruzzaman, Muhammad Noor
Universitas Airlangga
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Environmental Science Social Sciences Other

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Journal : bulletin of electrical engineering and informatics

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Customized moodle-based learning management system for socially disadvantaged schools Ika Qutsiati Utami; Muhammad Noor Fakhruzzaman; Indah Fahmiyah; Annaura Nabilla Masduki; Ilham Ahmad Kamil
Bulletin of Electrical Engineering and Informatics Vol 10, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i6.3202

Abstract

This study aims to develop Moodle-based LMS with customized learning content and modified user interface to facilitate pedagogical processes during covid-19 pandemic and investigate how teachers of socially disadvantaged schools perceived usability and technology acceptance. Co-design process was conducted with two activities: 1) need assessment phase using an online survey and interview session with the teachers and 2) the development phase of the LMS. The system was evaluated by 30 teachers from socially disadvantaged schools for relevance to their distance learning activities. We employed computer software usability questionnaire (CSUQ) to measure perceived usability and the technology acceptance model (TAM) with insertion of 3 original variables (i.e., perceived usefulness, perceived ease of use, and intention to use) and 5 external variables (i.e., attitude toward the system, perceived interaction, self-efficacy, user interface design, and course design). The average CSUQ rating exceeded 5.0 of 7 point-scale, indicated that teachers agreed that the information quality, interaction quality, and user interface quality were clear and easy to understand. TAM results concluded that the LMS design was judged to be usable, interactive, and well-developed. Teachers reported an effective user interface that allows effective teaching operations and lead to the system adoption in immediate time.
Fear of missing out during a pandemic: the driving factors of telemedicine application acceptance Muhammad Noor Fakhruzzaman; Ghea Sekar Palupi; Thinni Nurul Rochmah
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i4.3848

Abstract

COVID-19 pandemic changed how society behaves. Travel and social restrictions, commonly associated with the term lockdown became popular and ubiquitous. Given the rise of gig economy and mobile app delivery in the past several years, combined with lockdowns during the pandemic, and the application of telemedicine becomes essential. Halodoc is one of the popular telemedicine applications in Indonesia, having several useful features such as text-based doctor consultation and prescription drug order-delivery, and Halodoc is easily preferred by many. This article explored the motivation behind using Halodoc as the preferred method of getting health service during the pandemic, behind the perceived usefulness and perceived ease of use of the application, we found that fear of missing out (FOMO) has an indirect role in the application adoption in society, especially during lockdowns, where social interaction is limited to social media and other internet-based platforms. The reason why FOMO can be an important factor in technology adoption and how advertisers should explore FOMO is further discussed.
IndoPolicyStats: sentiment analyzer for public policy issues Muhammad Noor Fakhruzzaman; Sa'idah Zahrotul Jannah; Sie Wildan Gunawan; Angga Iryanto Pratama; Denise Arne Ardanty
Bulletin of Electrical Engineering and Informatics Vol 13, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i1.5263

Abstract

The government requires some vaccination for public health. This has led to a debate in recent years, especially during the Covid-19 pandemic. This research aims to analyze the two sentiments of the public regarding the vaccination policy. This would be helpful to ensure the acceptance of the government campaign about vaccination. The data used was text data obtained from Twitter when Indonesia was facing the second wave of the Covid-19 pandemic. The data were pre-processed by removing noise data, case folding, stemming, and tokenizing. Then, the data were classified with random forest, Naïve Bayes, and XGBoost. The results showed that all classifiers exhibit satisfying performance but XGBoost performs slightly better in accuracy value. This method can be deployed to be an automatic sentiment analyzer to help the government understand public feedback about its policies. This would be given by proper pre-processing and enough datasets.
Co-Authors Angga Iryanto Pratama Annaura Nabilla Masduki Basuki, Lintang Sabrang Kinasih Denise Arne Ardanty Ghani, Mohammad Ghea Sekar Palupi Ika Qutsiati Utami Ilham Ahmad Kamil Indah Fahmiyah Jannah, Sa'idah Zahrotul Maryamah Ratih Ardiati Ningrum Sie Wildan Gunawan Susanto, Putri Dwidhamayanti Thinni Nurul Rochmah