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All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING Infokes : Jurnal Ilmiah Rekam Medis dan Informasi Kesehatan Proceeding of International Conference Health, Science And Technology (ICOHETECH)
Tamarussal, Naraya Kyesa
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Computer Science & IT Decision Sciences, Operations Research & Management Health Professions Industrial & Manufacturing Engineering Medicine & Pharmacology Nursing Public Health Veterinary

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NORMALISASI BASIS DATA SISTEM DETEKSI DINI DAN KONSULTASI KOMPLIKASI KESEHATAN MASA NIFAS Nurhayati, Nurhayati; Pertiwi, Mumpuni Intan; Kholilurrohman, Maulana Rifky; Tamarussal, Naraya Kyesa
Jurnal Infokes Vol 15 No 2 (2025): Jurnal Ilmiah Rekam Medis dan Informatika Kesehatan
Publisher : Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47701/7e91s431

Abstract

Masa nifas merupakan fase penting yang rawan terhadap berbagai komplikasi kesehatan sehingga membutuhkan pemantauan dan penanganan medis yang optimal. Untuk mendukung upaya deteksi dini dan konsultasi komplikasi kesehatan pada masa nifas, diperlukan sistem informasi yang memiliki struktur data yang efisien, konsisten, dan bebas dari penyimpangan. Penelitian ini bertujuan untuk merancang basis data perangkat lunak yang mendukung deteksi dini dan konsultasi komplikasi kesehatan masa nifas, dengan menerapkan teknik normalisasi sebagai pendekatan utama dalam perancangan struktur data. Metode penelitian yang digunakan adalah pendekatan rekayasa perangkat lunak berbasis desain basis data melalui normalisasi meliputi identifikasi kebutuhan data, analisis relasi antar entitas, bentuk tidak normal, normal bentuk kesatu, normal bentuk kedua dan normal bentuk ketiga. Penelitian ini menghasilkan rancangan basis data yang terdiri dari 11 tabel terstruktur yang telah melalui proses normalisasi sehingga bebas dari redundansi dan ketidakteraturan data. Simpulan dari penelitian ini adalah setelah melalui tahapan normalisasi, maka dihasilkan basis data yang memiliki struktur relasional yang efisien yang mampu mendukung perangkat lunak deteksi dini komplikasi dan konsultasi kesehatan masa nifas yang akurat dan terstruktur.
USABILITY EVALUATION OF EARLY DETECTION AND POSTPARTUM COMPLICATION CONSULTATION SOFTWARE BY POSTPARTUM MOTHERS Nurhayati; Pertiwi, Mumpuni Intan; Kholilurrohman, Maulana Rifky; Tamarussal, Naraya Kyesa
Proceeding of the International Conference Health, Science And Technology (ICOHETECH) 2025: Proceeding of the 6th International Conference Health, Science And Technology (ICOHETECH)
Publisher : LPPM Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47701/4wzg4y69

Abstract

The postpartum period is a phase following childbirth that is vulnerable to various health complications. This paper aims to describe postpartum mothers’ assessment of the usability of an early detection and health complication consultation software during the postpartum period. Usability evaluation was conducted using the System Usability Scale (SUS) method to efficiently assess user perceptions of the technology system in terms of satisfaction and acceptance. The paper adopts a descriptive quantitative approach, with methods including questionnaire design, data collection, SUS score processing, result interpretation, and formulation of improvement recommendations. The study results show an average SUS score of 79.67, which falls into the A- category, indicating an acceptable level of user acceptance and a rating scale classified as Good. The majority of respondents found the application useful due to its ease in selecting symptoms, speed of assessment results, and direct consultation features, although there were suggestions for further feature development and service quality enhancement
Expert System for Early Detection of Postpartum Complications Using Certainty Factor Method Nurhayati, Nurhayati; Pertiwi, Mumpuni Intan; Kholilurrohman, Maulana Rifky; Tamarussal, Naraya Kyesa
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11009

Abstract

Postpartum complications are one of the main causes of maternal mortality. The objective of this study was to design and build an expert system capable of early detection and providing consultation regarding health complications that occur during the postpartum period using the certainty factor method. The certainty factor approach is utilized to overcome the uncertainty that arises during the diagnosis process by combining the confidence values ​​of each symptom entered by the user. The research methods included needs identification, data collection, knowledge acquisition, knowledge base development, software design, software development, and testing. Needs identification generated 10 data sets, data collection was conducted through literature studies, and knowledge acquisition was obtained through interviews. The knowledge base was compiled based on information from experienced medical personnel. The software design included data flow, interface, and database. The software development resulted in a good early detection expert system. The expert system trial indicated superior performance in identifying health complications during the postpartum period with an accuracy rate of 91%. The ability to recognize positive cases reached 90.9%, and the error rate was 10%, indicating this system is reliable and accurate in decision-making.
Co-Authors Kholilurrohman, Maulana Rifky Nurhayati Nurhayati Nurhayati Pertiwi, Mumpuni Intan