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All Journal Jurnal Bidan Prada Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Promkes: The Indonesian Journal of Health Promotion and Health Education Knowledge Engineering and Data Science Jurnal Kebidanan JURNAL INSTEK (Informatika Sains dan Teknologi) Jurnal Riset Informatika Health Information : Jurnal Penelitian Jurnal Abdidas Jurnal Pengabdian UNDIKMA Jurnal Teknik Informatika (JUTIF) Community Empowerment Lontara Abdimas : Jurnal Pengabdian kepada Masyarakat Jurnal Abdi Masyarakat Indonesia Jurnal Cakrawala Ilmiah Indonesian Journal of Health Information Management Services (IJHIMS) Jurnal Bina Cipta Husada: Jurnal Kesehatan dan Science International Journal of Health Literacy and Science
Ika Pantiawati
Faculty Of Health Science, Dian Nuswantoro University, Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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OPTIMALISASI TELEMEDICINE OLEH TENAGA KESEHATAN DI FASILITAS PELAYANAN KESEHATAN PRIMER Widya Ratna Wulan; Evina Widianawati; Ika Pantiawati
Indonesian Journal of Health Information Management Services Vol. 3 No. 2 (2023): Indonesian Journal of Health Information Management Services (IJHIMS)
Publisher : APTIRMIKI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33560/ijhims.v3i2.71

Abstract

The lack of health communication technology literacy in the elderly group affects the high mortality rate due to non-communicable diseases. Health communication and information technology media can be a medium for health workers and elderly participants such as telemedicine but there are still limitations in device use. This activity aimed to educate and socialize the concept of telemedicine applications to health workers and participants able to be independent in facilitating the community regarding health issues, especially the risk of Hypertension and Diabetes Mellitus. The implementation focused on empowering participants in the Elderly Chronic Disease Management Program and health workers in Primary Health Care Facilities in Semarang Regency with sub-activities of Communication Techniques Training and Socialization of Prolanis Telemedicine Applications to Health Workers and Elderly Participants. The results of the service show that health workers who are responsible for Prolanis activities understand the importance of communication with participants through health digitization and data recording for participants through health technology media. Participants found this application useful for communication systems and data collection, and hope it will be further developed and re-socialized.
OPTIMASI PENGGUNAAN TEKNOLOGI INFORMASI PADA PETUGAS KESEHATAN DALAM MENGOLAH DATA KESEHATAN DI FASILITAS PELAYANAN KESEHATAN KABUPATEN SEMARANG Evina Widianawati; Nugraheni Kusumawati; Widya Ratna Wulan; Ika Pantiawati
Indonesian Journal of Health Information Management Services Vol. 3 No. 2 (2023): Indonesian Journal of Health Information Management Services (IJHIMS)
Publisher : APTIRMIKI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33560/ijhims.v3i2.72

Abstract

 Di Puskesmas Lerep petugas masih kurang mengetahui beberapa rumus dan tools dalam Ms. Office untuk mempermudah pekerjaannya dalam mengolah data kesehatan. Dirancang modul penggunaan teknologi informasi untuk mempermudah petugas dalam menjalankan tugasnya yang berisi General Komputer dan Basic Office, Ms. Excel Intermediate dan QGIS. Tujuan dari kegiatan ini adalah untuk sosialisasi penggunaan teknologi informasi pada petugas kesehatan dalam pengolahan data kesehatan di Puskesmas Lerep. Metodologi pelaksanaan kegiatan yaitu tindakan atau action research yang dilakukan pada petugas kesehatan. Materi penggunaan teknologi informasi berisi langkah mengatasi eror, membuat mail merge di Ms.Word, langkah praktek rumus & tools di Ms.Excel, dan dasar aplikasi QGIS. Petugas diberi kuesioner sebelum dan setelah pelatihan untuk mengetahui peningkatan pengetahuan peserta kemudian data dianalisis secara deskriptif. Hasil pengabdian menunjukkan pengetahuan petugas keseahtan pada penggunaan teknologi informasi terjadi peningkatan sebesar 72%. Faktor peningkatan terbesar terjadi pada peningkatan penggunaan mail merge, dasar operasi QGIS dan pivot table. Berdasarkan peningkatan skor pengetahuan petugas kesehatan maka dapat disimpulkan bahwa pengenalan teknologi informasi sangat bermanfaat bagi petugas kesehatan dalam mengolah data kesehatan.
Usia, Pendidikan, dan Penggunaan Aplikasi Kesehatan Berhubungan dengan Penerimaan Penggunaan Aplikasi Deteksi Penyakit Kronis Widianawati, Evina; Kusumawati, Nugraheni; Wulan, Widya Ratna; Pantiawati, Ika
Health Information : Jurnal Penelitian Vol 15 No 3 (2023): September-Desember
Publisher : Poltekkes Kemenkes Kendari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36990/hijp.v15i3.1181

Abstract

The results of the examination of patients who take part in the Prolanis program are only recorded at health care facilities, while the patients themselves do not know the results of the examination. To bridge this, chronic disease detection applications are designed. There are several factors that can affect a user's willingness to use the application, one of which is the user's characteristics. This study aims to examine the relationship between respondent characteristics and acceptance of chronic disease detection applications. The type of research used is quantitative research with the location of the study, namely in health service facilities in Semarang Regency, namely Lerep Health Center, Ungaran Health Center and Niki Helti Clinic. Data were obtained through questionnaires with a linkert scale filled out by patients in health care facilities as system users as many as 131 respondents. The study will be conducted in June-August 2023. Data analysis techniques using Chi square test and Spearman Rank test. The results showed that there was a relationship between age (p value 0.001), education (p value 0.000), length of use of mobile phones (p value 0.001) and use of health applications (p value 0.012) on the acceptance of chronic disease detection applications. Gender (p value 0.051), occupation (p value 0.626) and length of work (p value 0.293) were not associated with acceptance of chronic disease detection applications. In further research, it is recommended to conduct a mix method study, apply a qualitative approach, and add variables such as digital literacy.
Optimalisasi Deteksi Dini Pre Eklampsia Ibu Hamil Berbasis Telehealth oleh Kader Forum Kesehatan Kelurahan Tambakrejo Wulan, Widya Ratna; Widianawati, Evina; Pantiawati, Ika
Jurnal Abdidas Vol. 5 No. 5 (2024): October 2024
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/abdidas.v5i5.971

Abstract

Masih kurangnya literasi masyarakat khususnya kelompok ibu hamil tentang tingginya angka kematian Ibu dan Anak akibat Pre Eklampsia dinilai perlu untuk dilakukan upaya peningkatan pengetahuan perihal gejala penyakit tersebut. Peningkatan pengetahuan tidak hanya dari segi bahaya namun juga upaya yang bisa dilakukan secara preventif dan promotive yang telah difasilitasi di kegiatan Forum Kesehatan Kelurahan Tambakrejo. Diperlukan media komunikasi dan informasi kesehatan dalam kegiatan upaya deteksi dini Pre Eklampsia Pada Ibu Hamil berbasis Telehealth. Alur kegiatan Pengabdian Kepada Masyarakat ini dilakukan dimulai dari persiapan, proses kegiatan, monitoring serta evaluasi. Kegiatan Pengabdian Masyarakat dilaksanakan dengan proses pelatihan dimuali dari perkenalan, pre-test, materi, ice breaking, diskusi, post-test dan evaluasi. Kegiatan Pengabdian Masyarakat dihadiri oleh 6 ibu hamil dan 12 kader Forum Kesehatan Kelurahan Tambakrejo. Kader FKK dan ibu hamil  mengalami kenaikan pengetahuan sebelum dan setelah pelatihan. Peserta dapat memahami terkait bahaya preeklampsia dan mempraktikkan penggunaan aplikasi sederhana sebagai media pencatatan hasil screening yang dapat dimonitor masing-masig oleh ibu hamil maupu kader FKK melalui pesan Whatsapp setelah pengisian datanya.
Optimasi Model Extreme Gradient Boosting Dalam Upaya Penentuan Tingkat Risiko Pada Ibu Hamil Berbasis Bayesian Optimization (BOXGB) Kusuma, Edi Jaya; Nurmandhani, Ririn; Aryani, Lenci; Pantiawati, Ika; Shidik, Guruh Fajar
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 12 No 1: Februari 2025
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2025129001

Abstract

Kehamilan pada ibu hamil memiliki beragam risiko selama prosesnya seperti preeklampsia, diabetes dan hipertensi gestational. Seiring dengan perkembangan teknologi dan pemanfaatan data, implementasi machine learning dalam pengembangan early diagnosis system untuk tingkat risiko kehamilan telah banyak dilakukan. Namun kendala dalam penerapan machine learning adalah sulitnya menemukan konfigurasi parameter yang tepat agar model machine learning mampu memberikan akurasi prediksi yang mumpuni. Pada penelitian ini diusulkan metode optimasi berbasis Bayesian untuk mengoptimalisasikan hyper-parameter dari model Decision Tree (DT) dan Extreme Gradient Boosting (XGB). Kedua model teroptimasi tersebut dilatih dan diuji dengan menggunakan data risiko kehamilan yang diperoleh dari hasil pengukuran medis pada ibu hamil. Dari hasil evaluasi diketahui terdapat pengaruh jumlah iterasi pada Bayesian Optimization (BO). Implementasi BO pada model Decision Tree (BODT) menunjukkan adanya sedikit peningkatan nilai performa dibandingan dengan penelitian sebelumnya. Sementara itu, capaian performa tertinggi diperoleh oleh kombinasi model XGB dan Bayesian (BOXGB) dimana capaian nilai akurasi pada model BOXGB yaitu 87% diikuti dengan nilai rata-rata presisi, recall, dan F1-score masing-masing sebesar 88%, 87%, dan 88%. Secara keseluruhan implementasi Bayesian Optimization mampu memberikan setelan hyper-parameter yang dapat meningkatkan kemampuan model machine learning khususnya dalam memprediksi tingkat risiko kehamilan pada ibu hamil berdasarkan data pengukuran klinis.   Abstract During pregnancy process there are various risks such as preeclampsia, gestational diabetes and gestational hypertension. Along with the developments in technology as well as data science, the implementation of machine learning in early diagnosis system for pregnancy risk levels prediction has been widely carried out. However, there is a challenge in implementing machine learning, which is find the suitable yet effective parameter configuration in training machine learning model to provides better prediction accuracy. This research proposes a Bayesian-based Optimization (BO) method to tune up the hyper-parameters of Decision Tree (DT) and Extreme Gradient Boosting (XGB) models. These two optimized models were trained and tested using maternal risk dataset obtained from the clinical-based measurement on pregnant woman. From the evaluation result, it can be found that the number of iterations has high influence on the BO performance. The implementation of BO toward DT model has slight increase in performance result compared to the previous research. Meanwhile, the highest performance result achieved by the combination of BO and XGB (BOXGB) model where the proposed model reaches 87% of accuracy, followed by average value of precision, recall, and F1-score of 88%, 87%, and 88%, respectively. Overall, the implementation of BO is able to direct the hyper-parameter configuration which improves the machine learning performance especially in predicting maternal risk level based on clinical-based measurement data.
Edukasi dan Praktik Penanggulangan Stunting bagi Ibu Balita Stunting di Desa Lokus Stunting Kabupaten Banyumas Ika Pantiawati; Widya Ratna Wulan; Evina Widianawati; Tiara Fani; Nurrisa Ananda
Jurnal Pengabdian UNDIKMA Vol. 4 No. 4 (2023): November
Publisher : LPPM Universitas Pendidikan Mandalika (UNDIKMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/jpu.v4i4.9250

Abstract

This community service aims to improve the knowledge, attitudes, and behavior of mothers of toddlers regarding stunting prevention. The method for implementing this service used assistance and practice carried out on mothers who had stunted toddlers in Lokus Stunting Village, Banyumas Regency. Detailed activities included preparation, pre-test, checking toddler growth and development, providing education, practice of cooking MP ASI, and post-test. The evaluation instrument for this activity used a questionnaire and was analyzed descriptively. The results of this service showed that above-average participants experienced an increase in knowledge after training by 6%, indicating that participants' knowledge increased compared to before mentoring. The attitude aspect after mentoring also increased by 17%, and the practical aspect increased by 3%.
A Random Forest and SMOTE-Based Machine Learning Model for Predicting Recurrence in Papillary Thyroid Carcinoma Kusuma, Edi Jaya; Nurmandhani, Ririn; Pantiawati, Ika; Manglapy, Yusthin Meriantti; Widianawati, Evina
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.4854

Abstract

PTC (Papillary Thyroid Carcinoma) is one subtype of thyroid cancer occurred most frequently in thyroid cancer cases. Although the prognosis of this cancer is typically positive, its recurrence remains a key challenge requiring early detection. This study proposes machine learning models to predict PTC recurrence, explicitly addressing the inherent class imbalance in the recurrence data. This study implemented three supervised learning algorithms, namely Random Forest (RF), Extreme Gradient Boost (XGB), and Support Vector Machine (SVM) with the Synthetic Minority Oversampling Technique (SMOTE) to balance the dataset. SMOTE was chosen for its capacity to generate synthetic minority class samples while minimizing information loss, thus effectively addressing class imbalance and improving classification outcomes. Model performance was assessed using accuracy, precision, recall (sensitivity), and F1-score. Among all approaches tested, RF with SMOTE demonstrated superior performance, achieving 0.98 accuracy, perfect precision (1.0), high recall (sensitivity) (0.95), and a strong F1-score (0.97), outperforming previous methods including SMOTEENN-based approaches. The result of this study demonstrates SMOTE specifically outperforms SMOTEENN in this clinical context, likely due to better preservation of subtle prognostic indicators with minimal information loss. This improvement suggests SMOTE's effectiveness in preserving valuable decision boundary information while addressing class imbalance in PTC recurrence prediction. These findings establish RF with SMOTE as a robust and well-balanced approach for predicting PTC recurrence, contributing significantly to the development of more precise and responsive AI-driven decision support tools for thyroid cancer.
Pemberdayaan Masyarakat Melalui Penerapan Metode Ovitrap dan Budidaya Tanaman Pengusir Nyamuk Sebagai Upaya Penanganan Demam Berdarah Dengue (DBD) di Kelurahan Tanjung Mas Kota Semarang Fahmi, Fatimatul; Pantiawati, Ika; Anggraini, Reny Diva; Nuraeni, Puspa Ayu; Abiyasa, Maulana Tomy
Jurnal Pengabdian UNDIKMA Vol. 5 No. 2 (2024): May
Publisher : LPPM Universitas Pendidikan Mandalika (UNDIKMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/jpu.v5i2.9524

Abstract

This service activity aims to increase the knowledge and skills of community members in handling dengue hemorrhagic fever through the ovitrap method and cultivating mosquito-repellent plants. The method of implementing this service uses empowerment with socialization and practical activities. This service establishes a partnership with Dian Nuswantoro University (UDINUS) in the form of Assisted Village Partners, Semarang City Health Service, and Bandarharjo Community Health Center providing support in the form of mentoring and speakers, and the Forest Plant Certification and Seedling Center (BSPTH) providing support in the form of 100 eucalyptus plant seeds. The evaluation instrument for this activity uses a pre-test and post-test. This service data analysis technique uses descriptive analysis. The results of this service show that community members have the knowledge and skills to deal with dengue hemorrhagic fever through the ovitrap method and cultivating mosquito-repellent plants in Tanjung Mas Village. This is proven by residents participating in the process of making Ovitrap tools and planting mosquito-repellent plants. There was a change in community knowledge from before the counseling was carried out to after the counseling was carried out (the score before the counseling was 35, and the score after the counseling was 50).
Pelatihan WhatsApp Telemedicine Stunting untuk Meningkatkan Literasi Kader Posyandu di Desa Lokus Stunting Kabupaten Banyumas Pantiawati, Ika; Wulan, Widya Ratna; Widianawati, Evina; Fani, Tiara; Kusuma, Edi Jaya; Ananda, Nurrisa
Jurnal Pengabdian UNDIKMA Vol. 5 No. 4 (2024): November
Publisher : LPPM Universitas Pendidikan Mandalika (UNDIKMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/jpu.v5i4.13088

Abstract

The community service aims to increase the literacy and skills of Posyandu cadres in preventing stunting of toddlers as an effort to support the success of the 2030 SDGs in Banyumas Regency. The method of implementing this service used assistance and practice carried out on mothers who had stunted toddlers in Lokus Stunting Village, Banyumas Regency. Detailed activities included preparation, pre-test, providing education, training on the WhatsApp Telemedicine Stunting application and post-test. The evaluation instrument for this activity used a questionnaire and was explained descriptively. The results of this service showed that above average participants experienced an increase in Stunting Telemedicine Knowledge before and after the training by 87%, indicating that participants' Stunting Telemedicine Knowledge increased compared to before the training. The Toddler Stunting Knowledge aspect before and after mentoring also experienced an increase of 4%, then there was the Toddler Nutrition Knowledge aspect with an increase of 7%. The implications that can be taken from this service were increasing the literacy of Posyandu cadres, improving knowledge of toddlers with stunting, increasing knowledge of toddler nutrition, as well as contributing to SDGs 2030.
Pendampingan Aplikasi Personal Health Record Berbasis AI untuk Deteksi Dini dan Monitoring Penyakit Kronis bagi Warga Desa Kalongan Kabupaten Semarang Widianawati, Evina; Pantiawati, Ika; Wulan, Widya Ratna; Kusuma, Edi Jaya
Jurnal Pengabdian UNDIKMA Vol. 6 No. 1 (2025): February
Publisher : LPPM Universitas Pendidikan Mandalika (UNDIKMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/jpu.v6i1.13276

Abstract

This community service activity aims to improve the knowledge, attitudes, and behaviors of residents in Kalongan Village, Semarang Regency, for early detection and monitoring of chronic diseases through the use of an Artificial Intelligence (AI)-based Personal Health Record (PHR) application. The implementation method of this service included Survey, Socialization and Mentoring the practice of using the PHR-AI application. The evaluation instrument used a questionnaire and the data was analyzed descriptively in percentage growth. The results of this activity showed active participation from all attendees in discussions and socialization sessions on chronic diseases, PHBS, and the PHR-AI application for chronic disease detection. There was a significant improvement in participants’ knowledge, attitudes, and behaviors, indicating that the socialization of the PHR-AI application was highly beneficial in raising awareness about chronic disease risk factors. Participants were able to understand and practice the material presented during the sessions, which involved a combination of presentations, hands-on practice, and discussions. Additionally, participants actively consulted with facilitators during health screenings and enthusiastically joined the exercise sessions to maintain their health.
Co-Authors Amik Khosidah Ananda, Nurrisa Anggraini, Reny Diva Anyelir Khailla Eurissetaqtha Aprillia Putri Wulandari Citra Hadi Kurniati Desy Karlita Sari Dina Saputri Hindiyastutik Evina Widianawati Evina Widianawati Evina Widianawati Evina Widianawati Evina Widianawati Fahmi, Fatimatul Fatimatul Fahmi Fitria Wulandari Fitria Wulandari Guruh Fajar Shidik Handayani, Sri Iin Astuti, Iin Ima Syamrotul Muflihah Khomsatun . Kusuma, Edi Jaya Kusumawati, Nugraheni Lenci Aryani Lidya Citra Nirmala Magumi Avrora Iftita Manglapy, Yusthin Meriantti Maria Maya Purnamasari Maulana Tomy Abiyasa Maulana Tomy Abiyasa Minah . Muhammad Gymnastiar Aziz Mushovah, Devi Mutiara Dwi Rahayuni Nanda Zahrotul Maulidah Naning Pipit Ernawati Neva Marsela Nor Amalia Muthoharoh Nugraheni Kusumawati nugraheni kusumawati Nur Rizki Darmawan Nuraeni, Puspa Ayu Nurmandhani, Ririn Nurrisa Ananda Nurrisa Ananda Ossie Happinasari Pramitasari, Ratih Puji Rahayu, Lina Dwi Puspa Ayu Nuraeni Rachmansyah Adityo Nugroho Ratna Kartika Dewi Reny Diva Anggraini Respati Wulandari Rohmi, Rohmi Salsabila, Dinar Indri Bakti Soflina Nur Cholifah Sri Handayani Susilo Rini Syifa Sofia Wibowo Tiara Fani Tiara Fani Tri Anasari Tri Anasari Vira Aditya Putri Widianawati, Evina Wulan Margiana Wulan, Widya Ratna Yuli Trisnawati