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All Journal Khizanah al-Hikmah : Jurnal Ilmu Perpustakaan, Informasi, dan Kearsipan Jurnal Teknik Hidro International Journal of Community Service Learning JSAI (Journal Scientific and Applied Informatics) Inkunabula: Journal of Library Science and Islamic Information Maktabatun: Jurnal Perpustakaan dan Informasi Journal Medical Informatics Technology Jurnal Pengabdian Masyarakat Journal Papyrus : Sosial, Humaniora, Perpustakaan dan Informasi PEDAMAS (Pengabdian Kepada Masyarakat)
Andi Ibrahim
Jurusan Ilmu Perpustakaan UIN Alauddin
Humanities Computer Science & IT Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Medicine & Pharmacology Public Health Social Sciences

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Journal : Journal Medical Informatics Technology

 1 
Optimising Cataract Detection in Fundus Images through EfficientNet-Based Classification Ibrahim, Andi; Sabara, Edi; Dirsam, Winarlin; Aziz, Faruq
Journal Medical Informatics Technology Volume 2 No. 1, March 2024
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/medinftech.v2i1.25

Abstract

Turbidity of the lens of the eyeball that causes blindness or loss of vision is known as a cataract. By diagnosing the causes and symptoms of cataracts, early detection helps patients in prevention and treatment. The purpose of the research was to classify the image of the fundus into two classes: normal and cataract. The study also looked at how the optimizers for stochastic gradient descent, adaptive moment estimation, root mean square propagation, adaptive gradient algorithm, adaptive delta, and Nesterov-accelerated adaptive moment estimation stacked up against each other. We used the EfficientNet architecture in CNN and preprocessed the normal fundus and cataract fundus images by dividing each into training data (N = 80) and validation data (N = 20) from the Kaggle repository. We added test data from the normal fondus image (N =20) to see the accuracy of the results. We get 100% accuracy of training data, 87% and 77% validation data, and 100% and 95% test data.
Determinants of User Acceptance of the Halodoc Application: An Analysis of User Experience and User Satisfaction Aprianto, Kasiful; Ibrahim, Andi
Journal Medical Informatics Technology Volume 3 No. 2, June 2025
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/medinftech.v3i2.41

Abstract

Halodoc is one of the leading mobile health (mHealth) applications in Indonesia, offering services such as online doctor consultations, medicine delivery, and health information. This study examines the factors influencing user acceptance of the Halodoc app, focusing on the roles of user experience and satisfaction. The research involved a survey of 81 Halodoc users, followed by validity and reliability testing of the research instruments. Results showed that most items had high validity, with correlation values ranging from 0.775 to 0.851 for user acceptance, and above 0.75 for user experience (except one item). Reliability was also high, with Cronbach’s Alpha values exceeding 0.8 across categories. The highest average score was found in user satisfaction (21.77), indicating consistently high levels of satisfaction. Significant correlations were observed among user acceptance, user experience, service quality, and user satisfaction—most notably between user acceptance and satisfaction (0.8314). Regression analysis identified user experience and satisfaction as significant predictors of user acceptance, accounting for 74.4% of the variance. In contrast, service quality did not show a significant effect. The final regression model after stepwise elimination confirmed the strong influence of user experience (coefficient = 0.3513) and satisfaction (coefficient = 0.4399). These findings highlight the importance of enhancing user experience and satisfaction to increase user acceptance of mHealth applications like Halodoc.
Co-Authors Abd. Rahim Aminarti, Dea Andi Fatimah Yunus Anita Anita Aprianto, Kasiful AR. Akhmad Ramadhan Aziz, Faruq Bahruddin Berly, Alfonsius Cahyaningsih, Elin Dirsam, Winarlin Fatwa, Abdul Halil Fitriansal Hasan, Haslinda Ilmi, Uswatul Ilyas, Sitti Nurhidayah Iradhatullah Rahim Irvan Mulyadi Jasman K, Ratna Mansida, Amrullah Muarrifah, Syalwa Muliadi, Irvan Nur, Reniati Pratiwi MK R., Rika Kurnia Rahmat Hidayat Rosvita, Ita Sabara, Edi Salsabila, Nur Hikma Suriadi Syamsia Syamsuardi Saodi Syaparuddin Syukri, Fitriyani Tahir, Arsil Taqwa, Muh. Winda Ramadhani Zulharnah Zulkifli