GPS-based Classification Algorithm for Employee Attendance System using Telegram API

Abstract

The attendance system for employees, which is mostly used across the globe, is based on a fingerprint device. The drawbacks of this system are the presence of tool dependency, lower availability of fingerprint scanners, and the equipment being far away from the work premises. Due to the mentioned shortcomings, we propose an application system for presence built on the Telegram Bot using GPS. It will aid the employee in showing up in their work area. By installing the proposed system, numerous benefits will result. It will ease the overall presence system, and the processing of data on presence will be much more automated and easier. Due to the Telegram Bot method, the system can easily navigate the employee data, highlight daily attendance output, and efficiently store the presence results. It has a prediction accuracy of 87.5%, an acquired system sensitivity of 80%, and a shown specificity of about 91%.