Implementasi Sistem Otomasi Order Mentoring Pada Marketplace Mentoring Platform Nusademy

Abstract

The COVID-19 pandemic has caused the acceleration of digitalization to occur throughout the world in various aspects of life, one of which is in the world of education. The openness of access to learning resources has not been the right solution for humans to learn independently. There are details in the learning process that require the guidance of a teacher called a mentor. In line with this, PT Nusademy Solusi Indonesia (Nusademy) built a marketplace mentoring platform that allows learning to take place in a network between users and mentors. Nusademy provides an opportunity for users to able to choose learning topics and mentors according to their needs. In it, there are steps for mentoring orders, which are currently still being processed manually by the admin every time there is a transaction. So, we need a system that can bridge users with mentors to share benefits without having to depend on admin availability. Python is a programming language that has characteristics suitable for autonomous system development and integration with third-party services. This study aims to create, implement, and test an automated order mentoring system on the Nusademy Web Application which is integrated with the Xendit payment application, the Google Calendar scheduling application, and the Google Hangouts video-conferencing application. The automation system provides automatic services in billing, checking payment status, communication processes between users and admins, communication processes between admins and mentors, creating virtual mentoring rooms, and notification of mentoring agenda reminders. The system is launched on a cloud computing-based server which can enable automatic capacity scaling based on user requests using Google Cloud Run. Testing of the order mentoring automation system is carried out by considering aspects of system capability, system reliability, level of effectiveness, user experience, and business analysis.