BACKEND MODULES DEVELOPMENT FOR THE CV SCREENING SYSTEM WITH APPROPRIATE TECHNOLOGY AND AUTHENTICATION & AUTHORIZATION SYSTEMS - Gabriel Mulyawan, Warren
The CV screening process is an important stage in the recruitment process for selecting job applicants based on the submitted CVs. Manual processing would be time-consuming and prone to high errors. Therefore, the author's team developed a machine learning-based CV screening system, with the focus of this report on the development of the backend module in the form of an Application Programming Interface (API) service. This Final Project analyzes the appropriate technology to build the backend module of the CV screening system. The Final Project also focuses on the authentication and authorization processes of the system. The analysis results indicate that the MERN web stack, comprising components such as Node.js, Express, and MongoDB, is the best choice for building the backend module. The system also employs JWT with the HMAC SHA-512 encryption algorithm for the implementation of authentication and authorization processes. The backend module was tested using a tool named Postman with four types of testing: functional testing, system performance, security testing, and integration with the frontend module and machine learning model. The results demonstrate that the system performs well, with a response time of approximately 951.71 ms, meeting the Nielsen Norman standards. The authentication and authorization system also effectively maintain data security. The conclusion of this Final Project is that the MERN stack is suitable for the backend module of the CV screening system, and the security of the authentication and authorization system meets the requirements effectively. However, there are several steps that can be taken to improve the quality of this Final Project, including conducting testing with different technologies, optimizing the code, exploring alternative security systems, and enhancing web server performance (CPU usage).