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All Journal Journal of Computer Networks, Architecture and High Performance Computing Public Health and Safety International Journal (PHASIJ) Engineering and Technology International Journal (EATIJ) Journal of Engineering and Technology Innovation MPKM
sherly agustini
Universitas Ibnu Sina
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Transportation Veterinary Other

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Journal : engineering and technology international journal eatij

 1 
Sistem Informasi Pengajuan Judul Skripsi Mahasiswa Program Studi Teknik Informatika (Studi Kasus Fakultas Teknik Universitas Ibnu Sina): Information System for Submission of Thesis Title for Informatics Engineering Study Program Students (Case Study of the Faculty of Engineering, Ibnu Sina University) David Saro; sherly agustini
Engineering and Technology International Journal Vol 3 No 02 (2021): Engineering and Technology International Journal (EATIJ)
Publisher : YCMM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (676.916 KB) | DOI: 10.55642/eatij.v3i02.74

Abstract

Research is a term used in Indonesia to illustrate a scientific paper in the form of a written presentation of research results, discussing a problem in a particular field of science using applicable rules. The Informatics Engineering study program at Ibnu Sina University is still not effective and efficient in terms of campus services for final year students, especially when submitting the title of the final project because it is still using the manual method. The author uses the PHP programming language and MYSQL database which aims to build an information system for submitting the title of the final project which is expected to support and facilitate the process of submitting the title of the final project and easily get information about campus services, especially when submitting a final assignment at Ibnu Sina University.
Digital Image Processing Current Trends, Technologies, and Innovations Across Various Fields Sherly Agustini
Engineering and Technology International Journal Vol 7 No 02 (2025): Engineering and Technology International Journal (EATIJ)
Publisher : YCMM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55642/eatij.v7i02.1081

Abstract

This study aims to examine the latest trends, technological developments, and innovative applications of digital image processing across various sectors. Using a qualitative descriptive method with a literature review approach, the research analyzes ten recent and relevant scholarly articles published between 2017 and 2025. The findings reveal a significant shift toward deep learning-based methods, particularly convolutional neural networks (CNNs), which dominate tasks such as classification, segmentation, and object detection. Digital image processing is increasingly applied in healthcare, agriculture, industrial automation, traffic surveillance, and smart city infrastructure. The integration with real-time systems and Industrial Internet of Things (IIoT), as well as the availability of large public datasets, has further accelerated innovation in this field. Despite its advancements, challenges such as high computational requirements, ethical concerns, and the need for large-scale annotated data remain. This research highlights the importance of interdisciplinary approaches and responsible AI development to address these limitations and maximize the potential of image processing technologies in real-world applications.
Literature Review: Segmentation Methods and Feature Extraction in Bone Imaging Nofri Yudi Arifin; Sherly Agustini
Engineering and Technology International Journal Vol 7 No 03 (2025): Engineering and Technology International Journal (EATIJ)
Publisher : YCMM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55642/eatij.v7i03.1165

Abstract

This study presents a systematic literature review on the development of segmentation and feature extraction methods in bone imaging, which play a crucial role in improving the accuracy and efficiency of medical image analysis. The review follows the PRISMA guidelines to ensure that the literature selection process is transparent, structured, and replicable. Out of 200 initially identified studies, six articles met the inclusion criteria after undergoing the stages of identification, screening, eligibility assessment, and final inclusion. The findings reveal that traditional segmentation methods—such as thresholding, watershed, and active contour—remain widely used but exhibit limitations when applied to bone images with complex structures. Deep learning–based approaches, particularly U-Net, have emerged as a dominant trend due to their ability to produce more precise segmentation and support automated feature extraction. Commonly used feature extraction techniques include GLCM, LBP, HOG, and CNN-based deep features. Overall, recent studies emphasize the importance of combining preprocessing, adaptive segmentation, and robust feature extraction to enhance the detection of bone structures, including micro-fractures. This review also highlights the need for more comprehensive datasets and broader clinical validation to ensure that these techniques can be optimally implemented in computer-aided diagnostic systems.
Co-Authors Albertus L. Setyabudhi David Saro Larisang Mahdi Aulia Suheri Nofri Yudi Arifin Okta Veza