Melinda, Tashya Eka
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Excellence Service Strategy through Laboratory System Development in Health Department Selviyanti, Erna; Roziqin, Mochammad Choirur; Putra, Dony Setiawan Hendyca; Swari, Selvia Juwita; Alfiansyah, Gamasiano; Melinda, Tashya Eka; Tazania, Nur Shabrina Artaf
International Journal of Healthcare and Information Technology Vol. 3 No. 1 (2025): July
Publisher : P3M Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/ijhitech.v3i1.5561

Abstract

The Health Department has nineteen laboratories that serve various important purposes, including practicums and learning, supporting clinical research, clinical case simulations, research and system development, professional training, and health services. Despite their significance, these laboratories face challenges in presenting their profiles effectively to the public and stakeholders. This research aims to develop an Information System designed specifically for these laboratories to improve visibility and access to information regarding their services, technology, achievements, and advantages. The research follows a prototyping method to develop the system, which is chosen due to its flexibility, the complexity of the laboratories' needs, and the iterative nature of system development. The research was conducted over a period of six months, and the main steps involved included: early prototype development, rapid design and system testing. The web-based Laboratory Information System has been successfully developed and deployed, effectively addressing the challenges of information presentation, and supporting the growth and development of the laboratories.
Sistem Deteksi Dini Pneumonia Balita Berdasarkan Rekam Medis Menggunakan Algoritma C4.5 Melinda, Tashya Eka; Roziqin, Mochammad Choirur; Vestine, Veronika; Putra, Muhammad Ifantara
J-REMI : Jurnal Rekam Medik dan Informasi Kesehatan Vol 6 No 3 (2025): June
Publisher : Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/j-remi.v6i3.5369

Abstract

The detection of pneumonia cases in children under five at Jabung Public Health Center has not reached the targeted rate. From 2019 to 2022, the number of identified cases remained below the expected target of 4.45%. This study aimed to design and develop an early detection system for childhood pneumonia based on medical records using the C4.5 algorithm. The research applied the waterfall development method and utilised data collection techniques including interviews and document analysis. The subjects were program officers for childhood pneumonia and medical record staff, while the objects were medical records of children diagnosed with pneumonia and acute respiratory infections (ARI). System development involved several stages, starting with data preprocessing, including data cleaning, selection, reduction, and transformation. Data mining was conducted using the C4.5 algorithm with the help of RapidMiner software. The result was an early detection system tailored to the needs of Jabung Public Health Center. The system achieved an accuracy rate of 97.50% based on the confusion matrix. This system was expected to assist health workers in identifying pneumonia cases in children more effectively, thereby improving disease monitoring and early treatment efforts at the community healthcare level.