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All Journal International Journal of Electrical and Computer Engineering Jurnal Sains dan Seni ITS Bulletin of Electrical Engineering and Informatics Biomolecular and Health Science Journal Jurnal Layanan Masyarakat (Journal of Public Service) Journal of Community Development Journal of Advanced Technology and Multidiscipline (JATM)
Indah Fahmiyah
Department Of Engineering, Faculty Of Advanced Technology And Multidisipline, Universitas Airlangga, Surabaya
Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Materials Science & Nanotechnology Medicine & Pharmacology Neuroscience Nursing Public Health Social Sciences Other

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Journal : Bulletin of Electrical Engineering and Informatics

 1 
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.
Short birth intervals classification for Indonesia’s women Ratih Ardiati Ningrum; Indah Fahmiyah; Aretha Levi; Muhammad Axel Syahputra
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3432

Abstract

Birth interval is closely related to maternal and infant health. According to world health organization (WHO), the birth interval between two births is at least 33 months. This study is the first to discuss the short birth interval (SBI) in Indonesia and used data from the Indonesian Demographic and Health Surveys 2017 with a total of 34,200 respondents. Birth interval means the length of time between the birth of the first child and the second child. Categorized as SBI if the distance between births is less than 33 months. The variables used include mother's age, mother's age at first giving birth, father's age, household wealth, succeeding birth interval, breastfeeding status, child sex, residence, mother's education, health insurance, mother's working status, contraception used, child alive, total children, number of living children, and household members. Machine learning algorithms including logistic regression, Naïve Bayes, lazy locally weighted learning (LWL), and sequential minimal optimization (SMO) are applied to classify SBI. Based on the values of accuracy, precision, recall, F-score, matthews correlation coefficient (MCC), receiver operator characteristic (ROC) area, precision-recall curve (PRC) area, the Naïve Bayes is the best algorithm with scores obtained 0.891, 0.889, 0.891, 0.885, 0.687, 0.972, and 0.960 respectively. Additionally, 18.25% of mothers were classified as still giving birth within a short interval.
Co-Authors Affandi, Moch Agus Supriyanto Annaura Nabilla Masduki Aretha Levi Astri Dewayani Ferdinandus, Euvanggelia Dwilda Gagas Gayuh Aji, Gagas Gayuh I Nyoman Latra Ika Qutsiati Utami Ilham Ahmad Kamil Jannah, Sa'idah Zahrotul Khiftiyah, Ana Moch. Affandi Muhammad Axel Syahputra Muhammad Noor Fakhruzzaman Nanda Rachmad Putra Gofur Ni'matuzahroh Nurul, Mochammad Ratih Ardiati Ningrum Rizki Putra Prastio Rodik Wahyu Indrawan Sari, Silvia Siti Khaerunnisa Sofiah, Amila Sriani, Dewi Yankel Sena