Efendi, Ridwan (2023) Pengembangan Website Klasifikasi Kanker Kulit Menggunakan Convolutional Neural Network. Project Report (Praktek Kerja Lapang). Publish. (Unpublished)
![[img]](https://repository.upnjatim.ac.id/style/images/fileicons/text.png) |
Text (Cover)
20081010071_Cover.pdf Download (585kB) |
|
Text (Bab 1)
20081010071_Bab1.pdf Download (159kB) |
|
Text (Bab 2)
20081010071_Bab2.pdf Download (354kB) |
|
Text (Bab 3)
20081010071_Bab3.pdf Restricted to Repository staff only until 30 July 2027. Download (781kB) |
|
Text (Bab 4)
20081010071_Bab4.pdf Restricted to Repository staff only until 30 July 2027. Download (420kB) |
|
Text (Bab 5)
20081010071_Bab5.pdf Restricted to Repository staff only until 30 July 2027. Download (152kB) |
|
Text (Daftar Pustaka)
20081010071_DaftarPustaka.pdf Download (269kB) |
|
Text (Lampiran)
20081010071_Lampiran.pdf Restricted to Repository staff only Download (617kB) |
Abstract
Skin cancer is one type of cancer that is very dangerous for human health. Early detection and accurate diagnosis are important for people to identify whether it is skin cancer or just a common skin disorder. To detect skin cancer, we can use the biopsy method where skin tissue is taken and examined. The biopsy method is expensive and has a complicated process. In this study, a website is developed that can classify skin cancer by utilizing images or digital images of the patient's skin which are then processed using Convolutional Neural Network (CNN). The development process is carried out by following the Artificial Intelligence (AI) Project Cycle. AI Project Cycle is a cycle or stages carried out in creating a complete AI project. The stages are Problem Scoping, Data Acquisition, Data Exploration, Modeling, Model Evaluation, and Deployment. The dataset used is 10.015 images of skin cancer. The dataset consists of seven types or classes of skin cancer, namely Actinic Keratosis (akiec), Basal Cell Carcinoma (bcc), Benign Keratosis (bkl), Dermatofibroma (df), Melanocytic Nevi (nv), Melanoma (mel), and Vascular (vasc). The data will be processed through several stages such as preprocessing, augmentation, modeling, and evaluation. The process aims to get the best accuracy value that will be used in the deployment process of a website. The results of this study show that the website can function properly. The website can detect skin cancer images uploaded by users with an accuracy rate of 74%. This skin cancer classification website was developed using the knowledge and training that has been obtained through the AI Mastery program from Orbit Future Academy (OFA). OFA is a company engaged in the business of education and skills training that is relevant for the community or students to improve the quality of life and face future challenges. One of its programs is AI Mastery. The AI Mastery program contains an explanation or training of AI with the aim that participants are able to develop a useful AI technology. Therefore, the development of this skin cancer classification website is in accordance with the objectives of the program.
| Item Type: | Monograph (Project Report (Praktek Kerja Lapang)) | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Contributors: |
|
||||||||
| Subjects: | T Technology > T Technology (General) | ||||||||
| Divisions: | Faculty of Computer Science > Departemen of Informatics | ||||||||
| Depositing User: | Ridwan Efendi Efendi | ||||||||
| Date Deposited: | 30 Jul 2024 03:34 | ||||||||
| Last Modified: | 30 Jul 2024 03:34 | ||||||||
| URI: | https://repository.upnjatim.ac.id/id/eprint/28000 |
Actions (login required)
 |
View Item |