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All Journal JUITA : Jurnal Informatika Jurnal Ilmiah Perekam dan Informasi Kesehatan Imelda (JIPIKI)
Dyah Megawati Surip Solekhah
Universitas Gadjah Mada
Computer Science & IT Health Professions Public Health

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Tinjauan Pelaksanaan Penyusutan dan Pemusnahan Rekam Medis di RSUD Muntilan Hanifah Shofiarini; Makhrum Irmaningsih; Dyah Megawati Surip Solekhah; Adinda Dwi Nurul ’Ain; Esa Maheswari; Marko Ferdian Salim; Emi Nugroho; Bagus Setyadi
Jurnal Ilmiah Perekam dan Informasi Kesehatan Imelda Vol. 8 No. 1 (2023): Jurnal Ilmiah Perekam dan Informasi Kesehatan Imelda Edisi Februari
Publisher : Akademi Perekam dan Informasi Kesehatan Imelda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52943/jipiki.v8i1.1136

Abstract

Medical records are crucial documents in a hospital's patient care. Long-term use of paper-based or conventional medical records might result in issues including misfiles, disorganized shelves, and limited storage space. As a result, it's important to implement a procedure for the retention, elimination, and destruction of medical record files in order to eliminate useless files, decrease the growth in the number of files, and maintain the standard of medical record services. This study aims to evaluate the 5 M (Man, Money, Method, Material, and Machine) components of the process of eliminating and destroying medical record files at RSUD Muntilan. The object of research is medical record files, storage facilities, storage, implementation, and destruction of medical files. The method used in this study is a qualitative method through data collection by observation and interviews with medical record officers. The research was carried out at the Muntilan Hospital from June to July 2022. Based on the research that has been done, the process of implementing and destroying medical records is in accordance with applicable procedures and the regulation of the Ministry of Health No. 269 of 2008.
Decision Tree Model for Maternal Risk Classification Based on Kartu Skor Poedji Rochjati Dyah Megawati Surip Solekhah; Annisa Maulida Ningtyas
JUITA: Jurnal Informatika JUITA Vol. 14 Issue 2, July 2026
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v14i2.28509

Abstract

Maternal mortality remains a serious public health issue. This can be prevented by taking preventive measures through early identification of pregnancy risks. This study aims to develop a classification model for screening maternal pregnancy risks using the “Kartu Skor Poedji Rochjati” (KSPR) as a clinical basis for data labelling. This research applies the Cross-Industry Standard Process for Medical Data Mining (CRISP-MED-DM) methodology to ensure a systematic and clinically relevant modelling process. A dataset containing 998 medical records from the Maternal Health and High-Risk Pregnancy Dataset was used, with rule-based labelling adapted from KSPR to classify maternal risk into three categories: Low-Risk Pregnancy, High-Risk Pregnancy, and Very High-Risk Pregnancy. Experiments were conducted with three Decision Tree models, namely the Baseline Model, Model with SMOTE, and Model with Class Weighting. Based on these experiments, it was found that the Decision Tree algorithm enhanced with the Synthetic Minority Oversampling Technique (SMOTE) to overcome class imbalance was the most optimal model. This model achieved balanced performance across all classes with an accuracy of 0.86 and a weighted average F1-Score of 0.87.
Co-Authors Adinda Dwi Nurul ’Ain Annisa Maulida Ningtyas Bagus Setyadi Emi Nugroho Esa Maheswari Hanifah Shofiarini Makhrum Irmaningsih Marko Ferdian Salim