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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 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 Electrical & Electronics Engineering Immunology & microbiology Industrial & Manufacturing Engineering Materials Science & Nanotechnology Medicine & Pharmacology Neuroscience Public Health

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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.
Faktor yang Memengaruhi Kadar Gula Darah Puasa Pasien Diabetes Mellitus Tipe 2 di Poli Diabetes RSUD Dr. Soetomo Surabaya Menggunakan Regresi Probit Biner Indah Fahmiyah; I Nyoman Latra
Jurnal Sains dan Seni ITS Vol 5, No 2 (2016)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM), ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (733.451 KB) | DOI: 10.12962/j23373520.v5i2.17384

Abstract

Penyebab kematian untuk semua umur telah mengalami pergeseran, yaitu dari penyakit menular menjadi penyakit tidak menular (PTM), salah satu PTM adalah diabetes mellitus (DM). Dari semua jenis DM, penderita DM tipe 2 mencapai 90% – 95% dari keseluruhan populasi penderita DM. DM tipe 2 adalah penyakit gangguan metabolik yang ditandai dengan kadar gula darah tinggi akibat adanya resistensi insulin dan atau defisiensi insulin (gangguan sekresi insulin). Penderita DM tipe 2 memerlukan penatalaksanaan DM secara baik dan teratur untuk menjaga agar kadar gula darah tetap terkendali. Salah satu kadar gula darah yang dapat menggambarkan kondisi gula darah penderita DM tipe 2 adalah Gula Darah Puasa (GDP). GDP merupakan kadar gula darah seseorang yang diukur/ diperiksa setelah menjalani puasa sekitar 10-12 jam. Kadar gula darah yang tidak terkendali dapat meningkatkan terjadinya komplikasi akibat DM tipe 2, bahkan dapat menyebabkan kematian. Oleh sebab itu, dilakukan penelitian terhadap pasien DM tipe 2 di Poli Diabetes RSUD Dr. Soetomo yang sedang menjalani rawat jalan untuk mengetahui faktor yang memengaruhi kadar GDP pasien dengan mengkategorikan kadar GDP menjadi 2 kategori, yaitu GDP terkendali (GDP < 126 mg/dl) dan GDP tidak terkendali (GDP ≥ 126 mg/dl) sebagai variabel dependen sehingga analisis yang digunakan adalah analisis regresi untuk variabel dependen yang bersifat kualitatif (kategorik), yaitu salah satunya adalah regresi probit biner. Faktor atau variabel yang signifikan memengaruhi kadar GDP adalah kadar HDL, LDL, dan Trigliserida dengan ketepatan model dalam mengklasifikasikan sebesar 70%.
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.
Maximizing Millennial Students Role in Combating COVID-19 Hoaxes and Myths Astri Dewayani; Euvanggelia Dwilda Ferdinandus; Rizki Putra Prastio; Indah Fahmiyah; Amila Sofiah; Rodik Wahyu Indrawan; Mochammad Nurul; Gagas Gayuh Aji; Nanda Rachmad Putra Gofur; Siti Khaerunnisa; Dewi Sriani; Yankel Sena
Biomolecular and Health Science Journal Vol. 4 No. 1 (2021): Biomolecular and Health Science Journal
Publisher : Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/bhsj.v4i1.26910

Abstract

Introduction: Since the outbreak of Corona Disease-19 (COVID-19) spreads all over the world, various ways of health attempts have been conducted. However, overflowed information intertwines with mis/disinformation could raise public anxiety and stigma-related diseases. We aimed to assess the help of the young generation of millennials and Gen-Z whom are active college students in debunking hoaxes and myths of COVID-19 into their community.Method: The selected students were given a short course on COVID-19 basic information, prevention, and circulated myths. Later, they become ambassadors and actively educated via offline and online platforms. The impact of outspread information on audiences was investigated through a qualitative survey.Result: The knowledge of students were measured by pre- and post-test within the short course. Prior knowledge showed the least understanding part was prevention and myth of COVID-19. There was a significant improvement of knowledge in post-test after receiving seminar (p=0.0002). There were 97 respondents who filled the online survey that predominantly in young adulthood age. Respondent's insight was enhanced and they likely intend to spread the actual information to their surroundings.Conclusion: Appointing student as the spokesperson for health education can raise their social responsibility. Clarifying misinformation and health behaviour could be more influential within the same sharing community. In addition, the use of various online platforms could efficiently reach massive target, especially young ages.
Flagging clickbait in Indonesian online news websites using fine-tuned transformers Muhammad Noor Fakhruzzaman; Sa&#039;idah Zahrotul Jannah; Ratih Ardiati Ningrum; Indah Fahmiyah
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp2921-2930

Abstract

Click counts are related to the amount of money that online advertisers paid to news sites. Such business models forced some news sites to employ a dirty trick of click-baiting, i.e., using hyperbolic and interesting words, sometimes unfinished sentences in a headline to purposefully tease the readers. Some Indonesian online news sites also joined the party of clickbait, which indirectly degrade other established news sites' credibility. A neural network with a pre-trained language model multilingual bidirectional encoder representations from transformers (BERT) that acted as an embedding layer is then combined with a 100 node-hidden layer and topped with a sigmoid classifier was trained to detect clickbait headlines. With a total of 6,632 headlines as a training dataset, the classifier performed remarkably well. Evaluated with 5-fold cross-validation, it has an accuracy score of 0.914, an F1-score of 0.914, a precision score of 0.916, and a receiver operating characteristic-area under curve (ROC-AUC) of 0.92. The usage of multilingual BERT in the Indonesian text classification task was tested and is possible to be enhanced further. Future possibilities, societal impact, and limitations of clickbait detection are discussed.
Human Development Clustering in Indonesia: Using K-Means Method and Based on Human Development Index Categories Indah Fahmiyah; Ratih Ardiati Ningrum
Journal of Advanced Technology and Multidiscipline Vol. 2 No. 1 (2023): Journal of Advanced Technology and Multidiscipline
Publisher : Faculty of Advanced Technology and Multidiscipline Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jatm.v2i1.45070

Abstract

The quality of life for Indonesia's population can be measured from the human development index in each province. People who have a good quality of life indicate a prosperous life. The government has the responsibility to advance the welfare of the nation under the mandate of the constitution. The clustering of the human development index (HDI) in Indonesia is used to determine the distribution of quality of life or the distribution of social welfare. In this study, the K-Means method, which is a popular non-hierarchical clustering method, is used to classify human development in each province based on HDI indicators, namely Expected Years of Schooling, Mean Years of Schooling, Adjusted Per Capita Expenditure, and Life Expectancy at Birth. Provinces in Indonesia are clustered into 4 clusters. These results were also compared with the clustering based on HDI categories determined by Statistics Indonesia based on certain cut-off values. According to the HDI category, provinces in Indonesia fall into the medium, high, and very high categories. The results of the two groupings show that there is a trend toward appropriate characteristics for each group. Thus, K-Means can classify provinces in Indonesia according to the characteristics of the HDI indicators.
Co-Authors Annaura Nabilla Masduki Aretha Levi Astri Dewayani Dewi Sriani Euvanggelia Dwilda Ferdinandus Gagas Gayuh Aji, Gagas Gayuh I Nyoman Latra Ika Qutsiati Utami Ilham Ahmad Kamil Jannah, Sa'idah Zahrotul Mochammad Nurul Muhammad Axel Syahputra Muhammad Noor Fakhruzzaman Nanda Rachmad Putra Gofur Ratih Ardiati Ningrum Rizki Putra Prastio Rodik Wahyu Indrawan Siti Khaerunnisa Sofiah, Amila Yankel Sena