DEVELOPMENT AND DEPLOYMENT OF GENDER CLASSIFICATION WEB-BASED MACHINE LEARNING APPLICATION FOR E-KYC

• Main Author: Ivan Gunardi, Christopher
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/73941
• Institution: Institut Teknologi Bandung

E-KYC is one of the features widely used by government organizations to verify the identity of citizens. The same technology is also widely applied by banking and digital financial companies in the user registration process to ensure their identities. This is in line with Indonesia's Digital Nation 2021-2024 Roadmap on digital transformation. The e-KYC design within the government itself is also based on Presidential Regulation No. 95 of 2018 concerning the Electronic-Based Government System (SPBE). The use of e-KYC will reduce digital identity fraud while accelerating digitization through identity recognition automation. This can be achieved by applying machine learning to recognize faces (face recognition) and ensure the authenticity of the person whose face is processed (liveness detection). This final project is aimed at applying one of the e-KYC elements, namely gender classification, in the form of a web application integrated with machine learning. This system is designed to model the user identification process by taking pictures through the webcam, detecting faces and classifying gender with machine learning, and displaying the data obtained from the API. Each web and machine learning element is designed to stand independently, making it easy to integrate into the larger e-KYC ecosystem through the API.