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A Comparative Study of Digital Image Segmentation Algorithms for Acute Myeloid Leukemia M1 White Blood Cells Images Nurcahya Pradana Taufik Prakisya; Andika Setiawan
IJIE (Indonesian Journal of Informatics Education) Vol 4, No 2 (2020): IJIE (Indonesian Journal of Informatics Education)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijie.v4i2.48448

Abstract

Various types of algorithms have been widely used for image segmentation in digital image processing. Every algorithm has features that make it unique to be applied to specific cases. One of the applications of image segmentation is to detect white blood cells. Certain objects such as blood cells must be able to be well segmented because their existence is very crucial to support the accuracy of disease detection related to haematology or the branch of medical science that studies the morphology of blood and blood-forming tissues. Three image segmentation algorithms were compared through this study: Seed Region Growing, Otsu Thresholding and Active Contour Without Edge. Comparative analysis of the three algorithms was done by counting the number of white blood cell objects that were successfully segmented with the actual number of cells that were counted manually. A total of 30 images of blood smears were taken from people suffering from acute myeloid leukemia M1. The average accuracy values from each algorithm were used to determine which image segmentation algorithm is the most suitable for application in the case of white blood cells segmentation. The results showed that Active Contour Without Edge is the most appropriate among the other algorithms
Digitizing the School Administration Management System at SMAN 12 Bandung and its Evaluation with the System Usability Scale M Luthfi Zulfikar; Rosihan Ari Yuana; Nurcahya Pradana Taufik Prakisya
Journal of Informatics and Vocational Education Vol 5, No 1 (2022): Journal of Informatics and Vocational Education - March
Publisher : Pendidikan Teknik Informatika dan Komputer, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v5i1.61446

Abstract

Education administration is one of the vital information in learning activities. Education administration can increase the productivity of teachers and will make learning activities more focused and structured. Digitalization of education administration will help teachers manage education administration, especially planning for learning. Moreover, this application will help teachers assign students scores based on their attitudes. This system will use Laravel as a base along with a spiral model for the SDLC, and use the System of Usability Scale For Evaluation (SUS). This application is Considered easy to use because it gets the 'acceptance' grade based on acceptance, a "C" grade on the class scale, a "good" grade on the adjective rating, and a "B" grade on the percent rank. This application only needs slight requirements for adjustments, socialization, and training for teachers to be accustomed to the system.