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All Journal Jurnal Ilmu Komputer dan Informasi VISIKES Jurnal Teknologi Informasi dan Ilmu Komputer Journal of ICT Research and Applications Knowledge Engineering and Data Science Jurnal Kesehatan Vokasional Jurnal Ilmu Kesehatan Masyarakat (The Public Health Science Journal) Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Pengabdian UNDIKMA Jurnal Teknik Informatika (JUTIF) Community Empowerment JPKM: Jurnal Profesi Kesehatan Masyarakat Indonesian Journal of Health Information Management (IJHIM) Jurnal Ilmu Kesehatan Masyarakat (The Public Health Science Journal) APMa Jurnal Pengabdian Masyarakat
Kusuma, Edi Jaya
Program Studi Rekam Medis Dan Informasi Kesehatan, Fakultas Kesehatan, Universitas Dian Nuswantoro Semarang
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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Pengenalan Penggunaan Aplikasi “ACOV19” Sebagai Activity Tracking dan Media Literasi Digital di Kelurahan Tanjungmas Edi Jaya Kusuma; Sri Handayani; Ririn Nurmandhani
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 5, No 3 (2022): September 2022
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/ja.v5i3.670

Abstract

Dian Nuswantoro University in particular the Faculty of Health has developed an application whose main focus is activity tracking and digital media literacy for users named ACOV19. The use of activity tracking applications in the pandemic era is expected to be able to ease the work of the government and read the data transaction process. However, some people still do not understand the importance of this. In addition, socializing the use of applications that are still less popular makes these applications less popular. The purpose of this service is to provide an understanding of literacy and the use of the "ACOV19" application as an activity tracker and digital media literacy to the community in order to minimize the difficulties of using the application in the Tanjung Mas community. The indicator of success in this service is that the community can understand information literacy and be able to use ACOV19. This service activity went smoothly and was attended by 15 members of KWT Tunas Bahagia who were active and enthusiastic in participating in the service. In this activity, members of the Tunas Bahagia KWT were given material presentations related to the Covid-19 tracking application, Covid-19 transmission points, and self-isolation protocols. After the presentation of the material, it was continued with the introduction and use of the ACOV-19 application. With a good level of understanding, it is hoped that Tunas Bahagia KWT members can take advantage of the ACOV19 application in their daily activities as a tracker application for the prevention of Covid-19.
Perancangan Aplikasi (SIKD) Sistem Informasi Kesehatan Desa sebagai Upaya Digitalisasi Pencatatan dan Pelaporan Kesehatan di Desa Penadaran Pramitasari, Ratih; Rachmani, Enny; Nurjanah, Nurjanah; Kusuma, Edi Jaya; Viala, Berlian Totti
VISIKES: Jurnal Kesehatan Masyarakat Vol. 22 No. 2 (2023): VISIKES
Publisher : Dian Nuswantoro Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/visikes.v22i2Supp.7872

Abstract

Posyandu aktif di kabupaten grobogan 50,5%, dan angka kematian ibu di posisi nomor 2 terbanyak di provinsi Jawa Tengah, angka kematian neonatal (9,6) dan bayi (13,2). Sejalan dengan hal tersebut diatas prevalensi stunting masih tinggi melebihi rata-rata di provinsi Jawa Tengah. Penerapan teknologi informasi yang dikolaborasikan dengan program pemerintah terbukti dapat mempermudah berbagai aspek di bidang Kesehatan. Tujuan penelitian untuk mengidentifikasi, merancang, dan melakukan uji coba Aplikasi SIKD bagi Desa Penadaran Kabupaten Grobogan. Urgensi dalam penelitian ini yaitu terciptanya sistem kesehatan yang terstruktur dan tersistematis untuk meningkatkan derajat Kesehatan masyarakat di desa penadaran Kabupaten Grobogan. Metode yang digunakan untuk pengembangan aplikasi SIKD memanfaatkan metode prototyping, dimana dalam metode ini menghendaki interaksi antara user dengan developer selama masa development. Pengembangan berfokus pada fitur utama dari sistem yang akan dibuat dengan metode prototyping, pengguna dapat menentukan fitur mana yang paling dibutuhkan. Hasil dari penelitian ini yaitu untuk dapat menjalankan sistem ini dapat dilakukan dengan melakukan akses di https://sikd.medialiteracy.id/. Aplikasi berbasis website ini tidak mengharuskan pengguna untuk mengunduh aplikasi. Website SIKD (Desa Sehat) dibuat menggunakan Framework PHP Codeigniter 3.11, Databse SQL Maria DB, dan Tampilan CSS Bootstrap 4.
Penggunaan Aplikasi COVID-19 dan Praktik Penerapan Protokol Kesehatan Pencegahan COVID-19 pada Remaja di Indonesia Sri Handayani; Edi Jaya Kusuma; Muhammad Iqbal
Jurnal Ilmu Kesehatan Masyarakat Vol 10 No 03 (2021): Jurnal Ilmu Kesehatan Masyarakat
Publisher : UIMA Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33221/jikm.v10i03.905

Abstract

Remaja merupakan pengguna internet tertinggi dibandingkan dengan kelompok usia lain yang memiliki pengetahuan terbatas mengenai teknologi Kesehatan. Pada situasi pandemi COVID-19 remaja sering dijumpai positif COVID-19 tanpa gejala yang dapat menularkan pada kelompok resiko tinggi lain. Oleh sebab itu penelitian ini bertujuan untuk menganalisa pemakaian aplikasi COVID-19 dan hubungannya dengan praktik protokol kesehatan dalam pencegahan COVID-19 pada remaja. Penelitian ini menggunakan pendekatan survey dengan menggunakan kuesioner pada google form yang disebar secara online melalui sosial media. Dari hasil penelitian menunjukan bahwa ada hubungan antara penggunaan aplikasi COVID-19 dengan praktik protokol kesehatan sebagai pencegahan COVID-19 pada remaja (Pv= 0,002; PR: 3,475; CI: 1,598-7,559). Pengguna aplikasi COVID-19 pada kelompok remaja masih sangat minim yaitu sebesar 22,1%. Diperlukannya upaya peningkatan sosialisasi terkait aplikasi COVID-19 dan telemedicine lain pada kelompok remaja sehingga dapat menjadi salah satu cara edukasi kesehatan pada kelompok remaja.
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.
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.
Penguatan Kader Posyandu ILP dalam Skrining PTM Usia Produktif dan Lansia Manglapy, Yusthin Meriantti; Fani, Tiara; Muthoharoh, Nor Amalia; Kusuma, Edi Jaya
APMa Jurnal Pengabdian Masyarakat Vol. 5 No. 2: Juli 2025
Publisher : STIKES Bhakti Husada Mulia Madiun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47575/apma.v5i2.716

Abstract

Kegiatan pengabdian ini bertujuan meningkatkan kapasitas kader posyandu Integrasi Layanan Primer (ILP) dalam melakukan skrining PTM pada kelompok usia produktif dan lanjut usia. Metode kegiatan mencakup perekrutan kader, pelatihan partisipatif, serta evaluasi melalui pre-test dan post-test. Dari 29 pendaftar, 21 kader mengikuti pelatihan secara aktif dan menyerahkan lembar komitmen sebagai bentuk kesiapan untuk terlibat berkelanjutan. Pelatihan mencakup penyampaian materi dan praktik lima meja posbindu menggunakan metode ceramah interaktif dan simulasi. Hasil evaluasi menunjukkan peningkatan rata-rata skor dari 16,76 menjadi 19,35, yang mencerminkan peningkatan signifikan dalam pemahaman dan keterampilan kader. Kegiatan ini menunjukkan bahwa pendekatan pelatihan berbasis praktik efektif dalam membekali kader dengan keterampilan teknis skrining PTM, serta memotivasi mereka untuk berkontribusi aktif di komunitas.
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 Ananda, Nurrisa Arif Kurniadi Christy Atika Sari De Rosal Ignatius Moses Setiadi Dwi Indah Puspitasari Eko Hari Rachmawanto Enny Rachmani Eti Rimawati Evina Widianawati Guruh Fajar Shidik Handayani, Sri Ika Pantiawati Ika Pantiwati Kriswiharsi Kun Saptorini Lenci Aryani Manglapy, Yusthin Meriantti Marko Ferdian Salim MG Catur Yuantari Muhammad Iqbal Muthoharoh, Nor Amalia N. Nurjanah Nurmandhani, Ririn Pramitasari, Ratih Ririn Nurmandhani Sri Handayani Tiara Fani Viala, Berlian Totti Widianawati, Evina Wulan, Widya Ratna