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All Journal Proceeding of International Conference Health, Science And Technology (ICOHETECH)
Aril Rizal Saputra
Universitas Duta Bangsa Surakarta
Computer Science & IT Decision Sciences, Operations Research & Management Health Professions Industrial & Manufacturing Engineering Medicine & Pharmacology

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DEVELOPMENT OF RMEIA: A WEB-BASED ELECTRONIC MEDICAL RECORD MANAGEMENT SYSTEM FOR MATERNAL AND CHILD HEALTH SERVICES Bong Borero Lumabao; Yunita Wisda Tumarta Arif; Khoirul Mustofa; Aril Rizal Saputra
Proceeding of the International Conference Health, Science And Technology (ICOHETECH) 2026: Proceeding of the 7th International Conference Health, Science And Technology (ICOHETECH)
Publisher : LPPM Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47701/bz5g5x15

Abstract

Healthcare services for pregnant women and toddlers stillface challenges in managing medical records throughmanual registration books. This approach presents severallimitations, including the risk of data loss or damage,difficulties in retrieving patients’ medical histories, andinefficiencies in service delivery. In accordance withMinister of Health Regulation No. 24 of 2022 concerningElectronic Medical Records, digital medical recordmanagement is needed to support more effective andintegrated healthcare services. This study aimed to designand develop RMEIA (Rekam Medis Elektronik Ibu dan Anak),a webbased electronic medical record management systemfor maternal and child health services. A descriptivequalitative approach was employed, with systemdevelopment following the Waterfall model within theSoftware Development Life Cycle (SDLC). The researchvariables included outpatient registration procedures,midwife data, patient data, and registration information.RMEIA was developed using PHP and MySQL within theXAMPP environment, while system modeling wasperformed using Data Flow Diagrams (DFD) and Entity Relationship Diagrams (ERD). The results produced a web-based RMEIA system consisting of ten main database tables and providing functional modules for maternal and childhealth services, including antenatal care (ANC), toddlerimmunization, postpartum care, and family planningservices. The implementation of RMEIA facilitates medicalrecord management, accelerates patient data retrieval,reduces dependence on paper-based records, and supportsthe availability of more structured and secure healthinformation. RMEIA also supports the digitaltransformation of maternal and child health services in accordance with national policies on electronic medicalrecord implementation.
CERTAINTY FACTORS FOR DETECTING PREECLAMPSIA RISK BASED ON PREGNANCY TRIMESTER: A LITERATURE REVIEW Nurhayati; Yunita Wisda Tumarta Arif; Darah Ifalahma; Veronica Agesta Adyastuti; Aril Rizal Saputra
Proceeding of the International Conference Health, Science And Technology (ICOHETECH) 2026: Proceeding of the 7th International Conference Health, Science And Technology (ICOHETECH)
Publisher : LPPM Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47701/6d5m7c05

Abstract

Preeclampsia is a leading cause of maternal and fetaldeath. Early detection of the risk of preeclampsia isessential. This study aims to analyze the application of theCertainty Factor method in an expert system for earlydetection of preeclampsia risk, identify preeclampsiasymptoms based on trimester of pregnancy, and developrecommendations for developing a knowledge base thatmatches the characteristics of preeclampsia symptoms. Thestudy used a literature review method through articlesearches in the Scopus and Google Scholar databases, aselection process based on inclusion and exclusion criteria,extraction, descriptive analysis, and synthesis of eligiblearticles. The analysis focused on the application of theCertainty Factor method, knowledge sources, symptomsused, inference techniques, diagnostic results, and thecharacteristics of preeclampsia symptoms in each trimesterof pregnancy. The results show that the Certainty Factormethod has been widely applied in expert systems tosupport early detection of preeclampsia and otherpregnancy-related diseases through rule-based reasoningand diagnostic confidence level calculations. Research stilluses a static knowledge base without considering changesin symptom characteristics according to gestational age. Itis proposed that the development of a knowledge basestructured by trimester of pregnancy aims to improveinference accuracy and reduce misinterpretation ofsymptoms.
Co-Authors Bong Borero Lumabao Darah Ifalahma Khoirul Mustofa Nurhayati Veronica Agesta Adyastuti Yunita Wisda Tumarta Arif