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Dwiza Riana
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Journal Medical Informatics Technology
Published by Asia Pacific Network for Sustainable Agriculture, Food and Energy
ISSN : 29887003     EISSN : 29887003     DOI : https://doi.org/10.37034/medinftech
Core Subject : Health, Science, Engineering,
Computer Science & IT Dentistry Engineering Medicine & Pharmacology Public Health
Journal Medical Informatics Technology publishes papers on innovative applications, development of new technologies and efficient solutions in Health Professions, Medicine, Neuroscience, Nursing, Dentistry, Immunology, Pharmacology, Toxicology, Psychology, Pharmaceutics, Medical Records, Disease Informatics, Medical Imaging and scientific research to improve knowledge and practice in the field of Medical.
Arjuna Subject : Teknik (semua kategori) - Teknik Biomedis
Articles 60 Documents
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Advanced Filtering and Enhancement Techniques for Diabetic Retinopathy Image Analysis Saut Parulian, Onesinus; Na`am, Jufriadif
Journal Medical Informatics Technology Volume 2 No. 3, September 2024
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/medinftech.v2i3.40

Abstract

Diabetic retinopathy is a leading cause of visual impairment and blindness in diabetes sufferers. Early detection is crucial to prevent severe outcomes. This study presents an image processing method for retinal images to aid early detection. The method involves four steps: image enlargement, preprocessing, enhancement, and convolution. First, an algorithm enlarges the retinal image to increase resolution and reveal finer details. Preprocessing uses a min-max filtering algorithm to reduce noise and improve image quality. Next, specific pixel range enhancement techniques further refine the image and highlight relevant features. Finally, convolution with customized kernels detects and emphasizes areas indicating diabetic retinopathy, such as aneurysms and hemorrhages. Experimental results show improvement in image clarity and detail, enabling more accurate detection of diabetic retinopathy features. The correlation results are as follows: Filtering (0.35275, 0.20157, 0.4345), Enhancement (0.3214, 0.15823 0.34674), and Convolution (0.33542, 0.15758, 0.36826). The proposed algorithm enhances early detection and diagnosis by improving retinal image quality. Future work can optimize the algorithm and validate results with larger datasets, aiming to refine the determination of areas or pixel values relevant to diabetic retinopathy.
Improved Brain Tumor Detection MRI Using Advanced Processing Techniques: Enhancement and Convolution Case Studies Kartika Puspita
Journal Medical Informatics Technology Volume 2 No. 3, September 2024
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/medinftech.v2i3.43

Abstract

Brain tumors present a significant challenge in medical imaging due to their complexity, requiring early detection and precise analysis for effective treatment. This study develops and evaluates advanced image processing workflows aimed at enhancing brain tumor image analysis. The proposed method involves four main steps: enlargement, pre-processing with min-max filters, enhancement, and convolution. The dataset used is from Kaggle, comprising 3,364 images categorized into Glioma (100 images), Meningioma (115 images), No Tumor (105 images), and Pituitary Tumor (74 images). For this study, images from the Glioma, Meningioma, and Pituitary Tumor categories were used, with one image selected from each category for technique evaluation. The results showed significant improvements in image clarity and detail, with high correlation values of 0.9851 for Meningioma and 0.9886 for Pituitary. These findings highlight the effectiveness of the proposed techniques in enhancing image quality and diagnostic accuracy.
Analyzing User Experience and User Satisfaction: Evaluating User Acceptance of the Halo Hermina App Edi Sabara; Mahendra; Riana, Dwiza
Journal Medical Informatics Technology Volume 2 No. 3, September 2024
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/medinftech.v2i3.45

Abstract

This research investigates the factors influencing user acceptance of the Halo Hermina mobile health application through an analysis of user experience and satisfaction. The study utilized a survey method to gather feedback from Halo Hermina users, assessing the questionnaire's validity and reliability. The results indicate strong validity across most items, with correlation values between 0.779 and 0.828 for performance expectancy and over 0.77 for effort expectancy. The reliability analysis shows high internal consistency, with Cronbach's Alpha values exceeding 0.976. User satisfaction scored the highest mean (4.027), indicating a consistent high level of satisfaction among users. The correlation analysis reveals significant relationships between performance expectancy, effort expectancy, facilitating condition, and behavioral intention, with the strongest correlation found between performance expectancy and effort expectancy (0.8796). Overall, the study emphasizes the crucial role of enhancing user experience and satisfaction to boost the adoption of mobile health applications like Halo Hermina, providing valuable insights for developers and stakeholders to enhance application features and service quality to meet user expectations effectively.
Fragility Fracture of Proximal Tibia in A Wheelchair-Bound 54-Year-Old Female Patient Davidia, Zaky; Abirama, Atria
Journal Medical Informatics Technology Volume 2 No. 3, September 2024
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/medinftech.v2i3.61

Abstract

Sedentary behavior is one of the risk factors of fracture, in which mild activity was found to be inversely associated with hip, vertebral, and total fracture. Other study also found non-linear association of fracture risk with lower and higher physical activity was associated with higher risk of any fracture compared to a mean physical activity. In this study, we reported a 54-year-old wheelchair bound female with fracture on the proximal tibia cause by low-energy trauma. This research underscores the importance of early identification of fracture risk factors, especially in vulnerable populations such as older adults who are wheelchair-bound. Early interventions that include lifestyle changes, increased physical activity, and nutritional management are essential to prevent further fractures and improve bone health. Identifying the risk of fractures on elderly patient may be beneficial for prevention of fractures especially in wheelchair-bound elderly individual.
Comparison of Classification Results of SVM, KNN, Decision Tree, and Ensemble Methods in Diabetes Diagnosis Arsyad. H, Muhammad Iqbal; Amran, Ali; Desiani, Anita; Napitu, Michael Jackson
Journal Medical Informatics Technology Volume 2 No. 3, September 2024
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/medinftech.v2i3.62

Abstract

This study aims to determine which algorithms and test techniques are the most optimal in detecting diabetes mellitus and obtaining the best results based on the value of accuracy, precision, and recall. In this study, approaches were used in early diagnosis of diabetes using KNN, SVM, Decision Tree, and Ensemble Majority Voting methods in Percentage Split and K-Fold Cross Validation methods. Diabetes is a disease characterized by high blood sugar (glucose) levels and can cause a variety of disease complications and damage to the body's organs if not treated immediately. Early diagnosis of diabetes is becoming crucial so that people can take immediate action to the hospital for immediate treatment. The data used is Healthcare-Diabetes from Kaggle. The results of this study have found that the K-Fold Cross Validation method is better because it can provide an average improvement in Ensemble accuracy of 13.42% compared to the Percentage Split method which only gives an average increase in Ensamble accuracy of 9.15%. The best algorithm for classifying diabetes disease is the Ensemble Majority Voting algorithm using the K-Fold Cross Validation method with a 98.81% accuracy rate. These excellent research results may contribute to detecting early symptoms of diabetes before it become too severe.
Analysis of Service Quality on User Satisfaction in BPJS Kesehatan Website Trihardo, Rendra; Jumadi, J; Ernawati, Muji
Journal Medical Informatics Technology Volume 2 No. 4, December 2024
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/medinftech.v2i4.56

Abstract

BPJS Kesehatan plays a vital role in providing health insurance to millions of Indonesians, making it essential to assess the quality of service on their website to ensure efficient and accessible healthcare delivery. This study evaluates of service quality on user satisfaction with the BPJS Kesehatan website by analyzing 10 hypotheses related to information quality, system usability, and service effectiveness. The research employed a quantitative approach, utilizing a structured questionnaire and regression analysis with data from 32 respondents. Significant findings include a strong positive effect of service quality on system use (β = 0.928, p = 0.002) and a notable impact of system use on net benefits (β = 0.337, p = 0.014). The model's high R² value of 0.796 indicates that nearly 80% of the variance in net benefits is explained by the predictors, demonstrating that improved service quality and increased system use substantially enhance user satisfaction and perceived benefits. These results underscore the importance of focusing on service quality and user engagement to optimize outcomes from the BPJS Kesehatan website.
The Effect of Progressive Muscle Relaxation Therapy on Sleep Quality in Elderly Hypertensive Patients Irawan, Erna; Iklima, Nurul; Maidartati, M; Ningrum, Tita Puspita; Safira, Yulia
Journal Medical Informatics Technology Volume 2 No. 4, December 2024
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/medinftech.v2i4.66

Abstract

Hypertension causes sleep quality disturbances. A cost-effective and accessible intervention for sleep quality issues is progressive muscle relaxation therapy, a non-pharmacological approach that can improve sleep quality by alleviating negative feelings and promoting comfort and relaxation in the muscles. The objective of this study was to determine the effect of progressive muscle relaxation therapy on the sleep quality of elderly hypertensive patients at UPT Puskesmas Babakan Sari RW 14, Bandung City.   This study employed a quasi-experimental design with a one-group pre-post test. The population consisted of 118 hypertensive patients, and accidental sampling was used, resulting in 15 respondents visited at their homes. The sleep quality was measured using the PSQI questionnaire. Data analysis included univariate analysis using frequency distribution and bivariate analysis using the paired samples T-Test.  Results showed that the average PSQI score before the intervention was 9.93, which decreased to 4.0 after the intervention. The paired samples T-Test with T value of 6.615 (df=34) and a correlation of 0.770 and a significance level of 0.000 (P<0.05), indicating a significant effect of progressive muscle relaxation on sleep quality.   There is an effect of progressive muscle relaxation therapy on the sleep quality. Hypertensive patients are encouraged to continue practicing progressive muscle relaxation weekly to improve sleep quality and help control blood pressure.
Factors Affecting Nursing Students' Knowledge of Sports Injury Management Tasnim, Marwan; Fitriana, Lisna Anisa; Rohaedi, Slamet; Sumartini, Sri; Irawan, Erna; Maidartati, M; Iklima, Nurul
Journal Medical Informatics Technology Volume 2 No. 4, December 2024
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/medinftech.v2i4.70

Abstract

Knowledge about handling sports injuries is crucial for nursing students at Universitas Pendidikan Indonesia (UPI), who actively participate in various sports activities. This study analyzes the factors influencing students' knowledge in managing injuries. The influencing factors are categorized into internal factors—such as education, experience, age, and interest—and external factors, including mass media, socio-cultural influences, economic conditions, and environmental aspects. A cross-sectional research design was employed, involving 84 nursing students from UPI. Data were collected using a 90-item questionnaire, and analysis was conducted using the t-test. The results indicate that internal and external factors significantly influence students' knowledge of handling sports injuries, with a significance level of less than 0.05 (p < 0.05). This suggests that improvements in the internal and external factors correlated with enhanced knowledge among nursing students regarding sports injury management. These findings underscore the importance of enhancing both internal and external factors to improve nursing students' capabilities in sports injury management. Conversely, a decline in these factors corresponds with diminished knowledge levels. It is recommended that further research include a larger sample size to strengthen these findings.
Formation of Antiviral Calcium Alginate Layers Analyzed by Combining Theory, Computational Chemistry and Experiments Youssef, Ali; Georgakis, Michail; Yaxley, Daniel; Kuennemann, Eva
Journal Medical Informatics Technology Volume 2 No. 4, December 2024
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/medinftech.v2i4.79

Abstract

Alginate, a sugar polymer derived from algae, crosslinks with calcium ions to form a stable gel or film. Several studies already analyzed the antiviral properties of calcium alginate, whereby only some studies showed viral inhibition. This research investigates the biochemistry and conditions of calcium alginate networks to form gels and membranes by a combination of literature analysis, computational simulations, and spraying experiments. Cell culture assays were applied to test the potential of calcium alginate to inhibit viral entry into cells. These investigations demonstrate that protective effects on cultured cells depend on the specific alginate substance, the concentrations and the manner of deposition. The results confirmed conditions so that the calcium alginate forms effectively gel-like networks and thin membranes. Additionally, the experiments proved that over 50% of the infections of cells with viral particles can be inhibited easily by calcium alginate overlaying cells.
Risk Factors for Multidrug-Resistant Bacterial Infections in Hospital-Acquired Pneumonia at Cipto Mangunkusumo Hospital Murwaningrum, Artati; Kamelia, Telly; Chen, Khie; Loho, Tonny; Abdullah, Murdani
Journal Medical Informatics Technology Volume 2 No. 4, December 2024
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/medinftech.v2i4.94

Abstract

Multidrug-resistant (MDR) hospital-acquired pneumonia (HAP) is linked to high mortality, extended hospital stays, and increased healthcare costs. Identifying risk factors for MDR HAP is essential to formulate effective management strategies. This study analyzed the proportion of risk factors associated with MDR bacterial infections in HAP patients treated at Cipto Mangunkusumo General Hospital. Using a retrospective cohort design, data were collected from medical records of HAP patients hospitalized between 2015 and 2016. A total of 68 patients met the inclusion criteria, while 10 were excluded due to fungal or non-pathogenic bacterial growth in sputum cultures. Patients were categorized as infected with MDR or non-MDR bacteria based on the resistance profile of their initial sputum cultures. Descriptive analysis was conducted using Microsoft Excel to calculate proportions of risk factors, without applying inferential statistical tests due to the limited sample size. The incidence of HAP was 6.12 per 1000 admissions in 2015 and 6.15 in 2016. MDR bacterial infections were observed in 95% of cases in 2015 and 82.1% in 2016. Key risk factors for MDR infections included prior antibiotic use within 90 days (100%), albumin levels <2.5 g/dL (100%), Charlson Comorbidity Index ≥3 (95.9%), age >60 years (95.2%), hospitalization >5 days (92.5%), nasogastric tube (NGT) insertion (92.1%), prior ICU/HCU admission within 90 days (81.8%), and steroid use >10 mg/day for >14 days (28.6%). These results emphasize that most HAP cases were caused by MDR bacteria, with prior antibiotic use and low albumin as predominant risk factors, necessitating targeted interventions for at-risk populations.

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