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All Journal RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Jurnal Keperawatan dan Fisioterapi (JKF)
Nurmala Sari
Universitas Prima Indonesia
Computer Science & IT Engineering Other

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Relationship Between Hemodialysis Adequacy and Quality Of Life of Chronic Renal Failure Patients in RSU. Royal Prima Medan in 2022 Chairunnisa Novinka; Delpianus Gea; Fadhilla Fadsya; Nurmala Sari; Ritha Meicindy Br. Tarigan; Tiarnida Nababan
JURNAL KEPERAWATAN DAN FISIOTERAPI (JKF) Vol. 5 No. 1 (2022): Jurnal Keperawatan dan Fisioterapi (JKF)
Publisher : Fakultas Keperawatan dan Fisioterapi Institut Kesehatan Medistra Lubuk Pakam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35451/jkf.v5i1.1114

Abstract

More than 750 million additional persons are added to the world population each year due to the prevalence of chronic renal disease. The Global Burden of Chronic Kidney Disease Study conducted in 2017 found that chronic kidney disease is directly responsible for roughly 2.59 million deaths worldwide caused by impaired kidney function. Dialysis is a life-prolonging treatment that is administered to about 78.8 percent of chronic renal failure patients across the world. The purpose of this research is to evaluate whether or not there is a correlation between the appropriateness of hemodialysis treatment and the quality of life of patients with chronic renal failure who are receiving treatment at the RSU. Royal Prima Medan 2022. Methodologies such as descriptive analysis and cross-sectional research are utilized in this kind of investigation. In this study, a total of 25 people were randomly selected for participation in the study using the accidental sampling approach. According to the findings of the chi-square test, which had df = 2 and a p value that was less than 0.05, the hypothesis of Ho was not supported. As a consequence of this, the provision of proper hemodialysis has a significant bearing on the quality of life enjoyed by patients who suffer from chronic renal failure. It is anticipated of respondents that they will have an understanding of the function and purpose of the hemodialysis adequacy process in line with the recommendations for hemodialysis prescriptions in order to attain a good quality of life.
IDENTIFIKASI SEL DARAH ABNORMAL PADA PENYAKIT POLYCYTHEMIA VERA MENGGUNAKAN DEEP LEARNING: IDENTIFICATION OF ABNORMAL BLOOD CELLS IN POLYCYTEMIA VERA USING DEEP LEARNING Valentino Tinambunan; Aldo Hia Aldo; Rianto Sahputra Berutu; Nurmala Sari; Saut Dohot Siregar
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.7964

Abstract

Polycythemia Vera is a blood disorder characterized by an excessive number of red blood cells. This study aims to identify abnormal blood cells using a deep learning method based on convolutional neural networks (CNN). The dataset used consists of 1,200 blood cell images, including 600 normal images and 600 abnormal images. The steps in the study include data pre-processing, training a convolutional neural network model, model testing, and implementing a web-based application using Streamlit. The research findings show that the CNN model can classify blood cell images very effectively, with a training accuracy of 98.33%, a validation accuracy of 97.92%, and a testing accuracy of 100% with a loss value of 0.0136. In addition, the application created is able to classify blood cell images quickly and automatically. Based on these results, the CNN method is proven to be effective in identifying abnormal blood cells in cases of Polycythemia Vera.
Co-Authors Aldo Hia Aldo Chairunnisa Novinka Delpianus Gea Fadhilla Fadsya Rianto Sahputra Berutu Ritha Meicindy Br. Tarigan Siregar, Saut Dohot Tiarnida Nababan Valentino Tinambunan