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All Journal Jurnal Informatika SISFOTENIKA Indonesian Journal on Software Engineering (IJSE) Jurnal Teknik Komputer AMIK BSI Jurnal Pilar Nusa Mandiri Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal Teknologi Terpadu INTI Nusa Mandiri JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Infortech Jurnal Teknimedia: Teknologi Informasi dan Multimedia Jurnal Sistem Informasi Computer Science (CO-SCIENCE) SPEED - Sentra Penelitian Engineering dan Edukasi Jurnal Teknologi Sistem Informasi J-Innovation Indonesian Journal Computer Science (ijcs) Journal Medical Informatics Technology Jurnal Pengabdian Kepada Masyarakat International Journal of Computer Technology and Science
Taopik Hidayat
Universitas Nusa Mandiri
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Medicine & Pharmacology Public Health Social Sciences Other

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Journal : j-innovation

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Analisis Komparatif Metode Peningkatan Kualitas Citra Digital untuk Deteksi Area Tubercoluma pada Citra MRI Hidayat, Taopik; Dama, Desi Masdin; Irmanti, Kanita Salsabila Dwi
J-Innovation Vol. 13 No. 2 (2024): Jurnal J-Innovation
Publisher : Politeknik Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55600/jipa.v13i2.289

Abstract

Digital images are essential visual representations in medical analysis, particularly for detecting tuberculoma, a severe tuberculosis complication with high mortality. This study aims to enhance the quality of MRI T1 images for identifying specific tuberculoma areas by comparing four method segmentation, thresholding, negation, and embossed. The dataset comprises T1 MRI brain scans in top and bottom positions, followed by pre-processing stages to reduce noise using gaussian blurring, median blurring, and sharpening techniques. The pre-processing results indicate all methods retain image details effectively. Further analysis reveals the Embossed method produces the clearest images with high contrast, facilitating tuberculoma identification. The advantage of this method lies in its ability to highlight structural details through a three-dimensional effect. The findings conclude that the embossed method effectively improves the accuracy of tuberculoma detection, contributing significantly to advancing medical image analysis techniques. This research is expected to positively impact imaging-based disease diagnosis, particularly in brain tumor cases like tuberculoma.
Optimalisasi Teknik Reduksi Noise: Studi Perbandingan Metode Filtering untuk Peningkatan Citra Hidayat, Taopik; Ihsan Aulia Rahman; Rianggi Silvi Anti Butar-Butar
J-Innovation Vol. 14 No. 2 (2025): Jurnal J Innovation
Publisher : Politeknik Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55600/jipa.v14i2.315

Abstract

Digital image restoration is a critical aspect of image processing, as noise introduced during acquisition, transmission, or compression can degrade visual quality and reduce the accuracy of image information. The main challenge in noise reduction lies in suppressing disturbances without damaging important image details and structural features. This study aims to evaluate the effectiveness of Gaussian Filter, Median Filter, and Mean Filter, both individually and in combination, for noise reduction in digital images. The dataset consists of JPG images with a resolution of 4032×3024 pixels (12 MP), acquired using a smartphone camera and artificially contaminated with noise to simulate real-world conditions. Performance evaluation was conducted using noise standard deviation, Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity Index Measure (SSIM). Experimental results indicate that the combination of the Median Filter and Gaussian Filter achieves the best overall performance, with a noise standard deviation of 88.08, a PSNR of 13.32 dB, and an SSIM of 0.15, demonstrating an optimal balance between noise reduction and structural preservation. The findings confirm that combined filtering approaches are more effective than single filters. Future research is recommended to explore advanced filtering methods such as Bilateral Filter, Wiener Filter, and adaptive filtering techniques under various noise conditions
Co-Authors Abdul Latif Achmad Baroqah Pohan Achmad Bayhaqy Ade Christian Ade Suryadi Andi Saryoko Aziz, Faruq Bagas Eka Saputra Dama, Desi Masdin Daniati Uki Eka Saputri Dipo Era Ginanti Eka Saputri , Daniati Uki Faruq Aziz Faruq Aziz Faruq Aziz Fitra Septia Nugraha Gata, Windu Hafifah Bella Novitasari Ihsan Aulia Rahman Ilmalia Hartina Irmanti, Kanita Salsabila Dwi Khultsum, Umi M. Rangga Ramadhan Saelan Mulia Rahmayu Naufal Muzakki Ramadhan Nurmalasari Nurmalasari Nurmalasari Nurmalasari Nurul Khasanah Nurul Khasanah Nurwijayanti Pratiwi, Risca Lusiana Rangga Pebrianto Retno Sari Rianggi Silvi Anti Butar-Butar Rina Rina Risca Lusiana Pratiwi Risca Lusiana Pratiwi - Universitas Nusa Mandiri Salsabila, Unik Hanifah Satrio Budi Santoso Septian, Rendi Siswahyudianto Siti Masturoh Siti Masturoh siti nurlela Syarah Seimahuira Tri Rivanie Uki Eka Saputri, Daniati Umi Khultsum Veithzal Rivai Zainal Windu Gata YOANDA, YURIKA PRISILIA