Smart automation for credit point compilation of instructor

Credit point is the accumulation value of each item or activity that must be accomplished by instructor in Ministry of Manpower and Transmigration of Republic Indonesia. Instructors were facing difficulties in preparing credit point manually. Different understandings of the rules led error in the weighting of each activity assessed. Efficiency in the government operations has been a demand of institutional performance assessment. This research aims to decide the most appropriate expert system model which is used to automate credit point submission and manage information, as well as improve the quality and productivity of the instructor. Rule-based expert system was proposed to automate credit point reporting of instructors. The expert system was developed as a web based system in order to its interoperability and simple distribution. Knowledge base was built using MySQL database and modelled using UML (Unified Modeling Language). The prototype was built using the PHP programming language and CSS to display user interface. The study produced a prototype iPAK (Intelligent Formulation of Credit), which was an intelligent system in the preparation of instructor´s credit point rate applied with rule-based approach to obtain the number of credits that reflect the performance of instructor. IPAK prototype illustrated three main activities of instructor, the assessment team / verification, and approver official. Testing of the prototype conducted with functional testing and triangulation for data validation. Prototype run in expected activity scenarios both in terms of functionality and appearance. Stakeholders recommended to develop a real-scale applications to automate the preparation of instructor´s credit point at branch level.