KLASIFIKASI LUKA MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK PADA APLIKASI MOBILE DENGAN MODEL INCEPTION V3

GEOVARDO, FERNANDICO and Yusliani, Novi and Rizqie, M. Qurhanul (2023) KLASIFIKASI LUKA MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK PADA APLIKASI MOBILE DENGAN MODEL INCEPTION V3. Undergraduate thesis, Sriwijaya University.

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Abstract

A wound is damage that occurs to body tissue. Effective wound treatment requires a quick initial diagnosis, but often the process of manual wound diagnosis by medical personnel is not always efficient and takes quite a long time. In this research, the author developed an application to classify types of wounds using the Convolutional Neural Network (CNN) method and the Inception V3 model in a mobile application. The types of wounds categorized in this study include abrasions, bruises, burns, torn wounds, ingrown nails, lacerations and stab wounds. The data used in this research amounted to 3.150 data in image format, with a training data ratio of 80% and testing data of 20%. The results of this research are an average accuracy value of 96.82%, precision of 90.29%, recall of 89.52%, and f1-score of 89.52%. In addition, the application performance results were obtained with an average user interface assessment of 81.2%, an assessment of the ease of use of the application of 82.9%, an assessment of the speed of the classification process of 82.9%, and an assessment of the accuracy of the classification results of 75.1%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Luka, Convolutional Neural Network, Inception V3, Klasifikasi, Mobile
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Fernandico Geovardo
Date Deposited:	12 Jan 2024 01:45
Last Modified:	12 Jan 2024 01:45
URI:	http://repository.unsri.ac.id/id/eprint/137968

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