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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer EMITTER International Journal of Engineering Technology Jurnal Kesehatan International Journal of Health and Information System (IJHIS) International Journal of Healthcare and Information Technology Jurnal Pengabdian dan Pemberdayaan Banyuwangi
Wicaksono, Andri Permana
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Humanities Computer Science & IT Economics, Econometrics & Finance Engineering Health Professions Library & Information Science Medicine & Pharmacology Public Health Social Sciences Other

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Usability Evaluation of a Web-Based e-KMS for Toddler Nutritional Status Monitoring Using the System Usability Scale (SUS) Muna, Niyalatul; Muflihatin, Indah; Nurmawati, Ida; Mudiono, Demiawan Rachmatta Putro; Wicaksono, Andri Permana
International Journal of Healthcare and Information Technology Vol. 3 No. 2 (2026): January
Publisher : P3M Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/ijhitech.v3i2.6846

Abstract

A nutritional status assessment system is an electronic health information system that records toddler growth based on age-specific weight and height measurements. Parents may not always maintain appropriate scheduling or regular visits for periodic monitoring at healthcare facilities. This study presents a usability evaluation of a web-based nutritional monitoring system that implements an Electronic Growth Monitoring Card (e-KMS). Users interact with the system through a user interface (UI) and user experience (UX) designed to support effective interaction. The main contribution of this study is the empirical validation of the usability level of a web-based e-KMS in a healthcare context using the System Usability Scale (SUS). The evaluation involved 20 respondents, consisting of parent representatives and daycare teachers or administrators as e-KMS users, and employed 10 SUS statements measured on a five-point Likert scale. The SUS analysis yielded a score of 77.78, indicating a good and acceptable level of usability. These findings demonstrate that the developed e-KMS is suitable for supporting digital-based monitoring of toddler nutritional status in healthcare services.
Comparison of The Data-Mining Methods in Predicting The Risk Level of Diabetes Wicaksono, Andri Permana; Badriyah, Tessy; Basuki, Achmad
EMITTER International Journal of Engineering Technology Vol 4 No 1 (2016)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (813.592 KB) | DOI: 10.24003/emitter.v4i1.119

Abstract

Mellitus Diabetes is an illness that happened in consequence of the too high glucose level in blood because the body could not release or use insulin normally. The purpose of this research is to compare the two methods in The data-mining, those are a Regression Logistic method and a Bayesian method, to predict the risk level of diabetes by web-based application and nine attributes of patients data. The data which is used in this research are 1450 patients that are taken from RSD BALUNG JEMBER, by collecting data from 26 September 2014 until 30 April 2015. This research uses performance measuring from two methods by using discrimination score with ROC curve (Receiver Operating Characteristic).  On the experiment result, it showed that two methods, Regression Logistic method and Bayesian method, have different performance excess score and are good at both. From the highest accuracy measurement and ROC using the same dataset, where the excess of Bayesian has the highest accuracy with 0,91 in the score while Regression Logistic method has the highest ROC score with 0.988, meanwhile on Bayesian, the ROC is 0.964. In this research, the plus of using Bayesian is not only can use categorical but also numerical.
Co-Authors Achmad Basuki Al Ayyubi, Waridad Umais Aziz, Muhaiminul Dewi, Riskha Dora Candra Feby Erawantini Ida Nurmawati, Ida mudiono , demiawan mudiono , Demiawan rachmatta putro Mudiono, Demiawan Rachmatta Putro Mudiono, Demiawan Rahmatta Putro Muflihatin, Indah Muhammad Yunus Muna, Niyalatul Navalani, Faradita Nuraini, Novita Puspito Arum Ramadhani, Riska Isyraq Roziqin, Mochammad Choirur Sutantio, R. Alamsyah Tessy Badriyah, Tessy Wahyono, Nanang Dwi Wijayanti, Rossalina Adi