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All Journal MEDISAINS International Journal of Advances in Intelligent Informatics Jurnal Rekayasa Mesin ZOO INDONESIA JOIV : International Journal on Informatics Visualization Journal of Applied Information, Communication and Technology (JAICT) Home Economics Journal Journal of Maternal and Child Health Journal of Telenursing (JOTING) Indonesian Journal of Global Health research MAHESA : Malahayati Health Student Journal Abditeknika - Jurnal Pengabdian Kepada Masyarakat Society: Jurnal Pengabdian Masyarakat Journal Of Human And Education (JAHE) Innovative: Journal Of Social Science Research Berita Biologi
Kurnianingsih Kurnianingsih, Kurnianingsih
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Journal : medisains

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Develop a web-based system using the Naïve Bayes algorithm to predict asphyxia neonatal Arselatifa, Elviga; Sumarni, Sri; Kurnianingsih, Kurnianingsih
MEDISAINS Vol 22, No 1 (2024)
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/medisains.v22i1.19531

Abstract

Introduction: Most cases of perinatal asphyxia are caused by conditions unrelated to labor. When asphyxia occurs during childbirth, it is usually caused by an obstetric emergency that was not detected during pregnancy. It is essential to prevent asphyxia by identifying the incidence of asphyxia during pregnancy. Several studies have been conducted to identify asphyxia problems developing by predictive models. However, there has been no development of a system for predicting birth asphyxia during pregnancy and carried out in primary health facilities.Purpose: Develop a web-based system using the Naïve Bayes (NB) algorithm to predict asphyxia neonatal using a dataset of antepartum risk factors in primary health facilities.Methods: This study employed research and development, which consists of 4 stages, namely literature study, development stage, expert validity, and trial.Results: A system that health workers in primary health facilities can use to predict asphyxia neonatal and recommend referrals for determining the place of childbirth has been successfully created. The system performance test predicted asphyxia neonatal with all NB evaluation values reaching more than 98%, and the prediction accuracy in the respondent test included in the High Accuracy category (MAPE value 9.06%).Conclusion: The development of a web-based system using the NB algorithm has been proven to be able to predict asphyxia neonatal and can be implemented for health workers as an effort to anticipate delays in handling cases of asphyxia neonatal because of the predicted results along with recommendations for focusing mothers with the risk of babies born asphyxia to find out possible childbirth places.
The effectivity of mindfulness-based art therapy application-based artificial intelligence on the mental health of pregnant women Dhanio, Yeyen Wulandari; Runjati, Runjati; Suwondo, Ari; Kurnianingsih, Kurnianingsih; Sudiyono, Sudiyono
MEDISAINS Vol 21, No 1 (2023)
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/medisains.v21i1.16097

Abstract

Background: The COVID-19 pandemic has become a new stressor with significant pregnancy consequences, limiting access to health services. Mindfulness-Based Art Therapy (MBAT) has been proven to intervene in the body-mind-soul and improve mental health problems. However, no research has developed it into a form of artificial intelligence for use by pregnant women in supporting the current situation of access to health services.Purpose: This study aims to produce a system of MBAT based on artificial intelligence for early detection and to prove the effectiveness of improving mental health in pregnant women.Methods: This study employed Research & Development consisting of 4 stages, namely Literature Study, Development Stage, Validity Expert, and Trial.Results: The MBAT application has five features, from mental health information to history. The validity score of the application system is 87.33%. The trial results showed that the application effectively reduces stress levels by 91.26% and anxiety by 90.24%. Also, the application can predict the percentage reduction in stress and anxiety levels correctly and without errors using the decision tree.Conclusion: This application is helpful for pregnant women and health workers in detecting stress and anxiety levels early in pregnancy and improving mental health.
Mobile application for early detection of non-communicable diseases Kurniasih, Hesti; Widyawati, Melyana Nurul; Kurnianingsih, Kurnianingsih
MEDISAINS Vol 20, No 3 (2022)
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/medisains.v20i3.13716

Abstract

Background: The number of deaths and illnesses caused by non-communicable diseases (NCDs) is increasing. One of the leading causes of NCDs is the behavior or patterns of people's daily habits. In the absence of a system that is used to detect NCDs with a behavioral approach, it is essential to research and create an application system for the early detection of NCDs.Purpose: This study aims to produce a system for the early detection of NCDs in pregnant women and provide recommendations based on an expert system.Method: This study employed Research & Development consisting of 4 stages, namely Literature Study, Development Stage, Validity Expert, and Trial.Results: This application has features that the public can use to detect NCDs independently. Users can perform early detection independently as needed; all user detection history data will be recorded in the detection history menu. In addition, users get health information through the health article menu. The results of trials conducted on pregnant women found that this application system was more effective than the manual. A mobile application can also increase the speed of diagnosis to 42%.Conclusion: This application is helpful for health workers and the public in conducting early detection of NCDs and providing education. This early detection application will make it easier for users to know their condition based on their behavior and make it easier for health workers to detect early and control the user's condition even from a distance.
Development of an electronic measuring device for height and nutritional status equipped with artificial intelligence for screening stunting toddlers Istiqomah, Nursita; Widyawati, Melyana Nurul; Kurnianingsih, Kurnianingsih; Mulyantoro, Donny Kristanto
MEDISAINS Vol 21, No 3 (2023)
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/medisains.v21i3.19134

Abstract

Background: Technological advancements have changed various aspects of human life, including in the world of health. One technological breakthrough that dominates attention is artificial intelligence (AI). Artificial intelligence has proven its potential to revolutionize many fields, including the health sector. One of the urgent health problems that requires innovative solutions is detecting the problem of stunting in children under five.Purpose: The study aims to develop and test a measuring device that effectively determines the body height and nutritional status in toddlers 0-5 years.Method: This study is in Research and Development (R&D); it consisted of 5 stages: stage I (literature study), stage II (product development), stage III (expert validity and phase trials), stage IV (product revision and final product), and stage V (phase II trials).Results: The electronic measuring device for height and nutritional status has been created. The result is that the tool effectively determines the height and nutritional status. The value of the ultrasonic sensor works quite well, with a maximum test error value of 0.11 and an average of 0.033, which means the calibration value of the tool's sensitivity is valid in determining body height.Conclusion: The electronic measuring device effectively determines the body's height and nutritional status.
Co-Authors Abu Hasan Adi Wibowo alfiah alfiah Alifiansyah, Muhammad Fikry Amalia, Dhanty Nurul Amin Suharjono Anindya Wirasatriya Anis Roihatin Apandi, Apandi Aquarista, Nita Ari Suwondo Arselatifa, Elviga Avisyah, Gisnaya Faridatul Azka Khoirunnisa Chin, Wei Hong Darmawan Darmawan Dhanio, Yeyen Wulandari Diana, Tri Rettagung Donny Kristanto Mulyantoro edy susanto Fahriah, Sirli Fatahul Arifin, Fatahul fatimah Fatimah Fitriyani, Rizki Putri Gustiyana, Fikri Nizar Haerul, Haerul Hajrianti, Siti Hashimoto, Takako Henra, Mustika Hesti Kurniasih I Ketut Agung Enriko Ika Rahmawati Istiqomah, Nursita Kubota, Naoyuki Kuntarjo, Samuel Beta Kusuma, Yanti Yandri Lutfan Lazuardi Maharadatunkamsi Maharadatunkamsi, Maharadatunkamsi Mardiyono Mardiyono Masuyama, Naoki Melyana Nurul Widyawati Miyar, Miyar Muhammad Anif Mulyadi Mulyadi Nana Supriatna Nojima, Yusuke NOVA MUJIONO Nur Ghaniaviyanto Ramadhan Nurhaman, Ujang Nurhaswinda Nurseno Bayu Aji, Nurseno Bayu Oktaviani, Nur Hilda Prayitno Prayitno Prihandini, Riena Priyanti, Esteria Priyatna, Yayat Puspita Sari, Erika Lety Istikhomah Putri Hana Pebriana Putri, Winda Astria Rachmatiyah, Rina Rakasiwi, Rizky Khaerul Maulana Runjati Santosa, Naufal Adli Santoso, Pramono Hery Sarino . Sauri, Sopian Septiani, Camilla Sidiq Syamsul Hidayat, Sidiq Syamsul Sofyani, Umar Sri Sumarni Sudiyono Sudiyono Suparno Suparno Susmiyati, Susmiyati Tatag Bagus Putra Prakarsa Tri Raharjo Yudantoro Triastuti, Unggul Yuyun Trilaksono, Wahyu Triyono, Liliek Veryal, Veryal Wahyu Sulistiyo Wahyudin, Mohamad Walin Walin Wikanta, Hadi Wiktasari Wiktasari, Wiktasari Yanwari, M. Irwan Yanwari, Muhammad Irwan Yusuf Dewantoro Herlambang