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Religious-Cultural Mediation in Technology Adoption: A Qualitative Study of Islamic Communities in Indonesia Ramdani, Idan; Apri Wenando, Febby; Ondri, Dino
Surau Journal of Islamic Studies Vol. 1 No. 2 (2025): Surau Journal of Islamic Studies
Publisher : MD Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63919/surau.v1i2.33

Abstract

This research aims to analyze the influence of Islamic social and cultural values on technology adoption within Muslim communities, focusing on the challenges and opportunities arising from the misalignment between technological advancements and local cultural values. Technology adoption in Muslim societies is often influenced not only by infrastructure readiness but also by societal perceptions of technology that may conflict with long-standing religious doctrines and cultural traditions. This study identifies three main factors affecting technology acceptance: infrastructure readiness, social disparities, and the cultural characteristics of Islam. The research demonstrates that successful technology adoption requires social engineering that enables integration with the existing moral and social values in Muslim communities. Using a qualitative approach, the study explores how Muslims adapt technology without compromising their religious and cultural principles. Findings indicate that effective technology adoption necessitates policies accommodating local social and cultural values and the involvement of religious leaders in introducing appropriate technology. This research significantly contributes to enriching the study of technology adoption by considering cultural and religious dimensions and opens opportunities for further research in this field. The study’s limitation lies in its geographically limited scope, suggesting the need for broader, more in-depth research involving Muslim communities in various regions.
Pembangunan dan Implementasi Sistem Informasi Pendaftaran dan Absensi Online Magang Berbasis Website pada BPTU HPT Padang Mengatas Apri Wenando, Febby; Pratama Santi, Rahmatika; Hubby Aziira, Aina; Wahyuni, Ullya Mega; Dwi Kartika, Afriyanti; Erlangga Adi, Muhammad; Fadwa Shifana, Deyola
Jurnal Pengabdian UntukMu NegeRI Vol. 7 No. 1 (2023): Pengabdian Untuk Mu negeRI
Publisher : LPPM UMRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jpumri.v7i1.4973

Abstract

Balai Pembibitan Ternak Unggul Hijauan Pakan Ternak (BPTU HPT) in Padang Mengatas is the only Livestock Breeding Center in Indonesia that specializes in producing breeding stock of Simental and Limousin beef cattle. While BPTU HPT Padang Mengatas focuses on livestock farming, they also recognize the need for technology and programs to streamline their work and keep up with the evolving times. Currently, various activities such as internship registration, cattle sales, visit requests, guest registration, and community satisfaction indexing are still carried out manually, resulting in significant time consumption for both data entry and report compilation. Specifically, in the internship process, BPTU HPT Padang Mengatas requires the implementation of an internship attendance information system for interns. This system enables evaluation of the interns based on their performance and presence during the internship period. The introduction of this information system is expected to assist the employees of BPTU HPT Padang Mengatas, enabling internship supervisors to expedite the data collection process. Additionally, it is anticipated that this application will facilitate BPTU HPT Padang Mengatas in monitoring and controlling its activities.
Transfer Learning dengan CLAHE dan Sharpening filter untuk Deteksi Pneumonia pada Citra X-Ray Karan; Firdaus, Rahmad; Mukhtar, Harun; Apri Wenando, Febby
JURNAL FASILKOM Vol. 16 No. 1 (2026): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v16i1.11374

Abstract

Pneumonia is a respiratory infection that remains a leading cause of death, especially in children, requiring an automatic detection system based on chest X-ray images. The main challenge in automatic classification is low image quality, such as suboptimal contrast and unclear lung details, which can affect the feature extraction process by deep learning models. To address these issues, this study applies Contrast Limited Adaptive Histogram Equalization (CLAHE) to enhance image contrast and a sharpening filter to clarify lung edge details. The study aims to analyze the effect of preprocessing on classification performance using EfficientNet-B0 based on Transfer Learning with a full fine-tuning strategy. The dataset used is Chest X-Ray Pneumonia from Kaggle with 5,856 images consisting of Normal and Pneumonia classes. Experiments compare the Baseline model, CLAHE, and a combination of CLAHE and sharpening in three data sharing scenarios. Evaluation is carried out using accuracy, precision, recall, and image quality metrics PSNR, SSIM, and CII. The results of the study showed that the combination of CLAHE and sharpening in the 80:10:10 scenario produced the best performance with an accuracy of 97.61%, precision of 0.97, recall of 0.99, and an increase in image quality based on a CII value of 1.157.