Automate offline employability (AOE) data analysis as analytic learning tool for evaluating trends in students’ graduate employability

The substantial benefit to analyze graduate employability is known to describe Higher Education Institutions (HEIs) capability in producing career-ready graduates. The outcomes signify the success of the diploma or degree programs in meeting the market and stakeholder's demands. It is essential to identify how curriculum design and student activities can enhance the prospective ability to secure jobs. Therefore, Universiti Teknologi MARA (UiTM) gathers data about employment and employability to understand the current trends. However, developing a fast and accurate programming language for analyzing enormous data is a challenging task. This paper presents the development of an Automate Offline Employability (AOE) data analysis using Microsoft Excel; it reduces the time consumption in analyzing many data and increases the accuracy of data analysis. The system utilizes the combination of various types of Excel formulas and functions to execute multitasking algorithms simultaneously; it processes two data (initial and current information of graduates) obtained from online surveys. Graduates must answer the first survey during the last semester of their study, and the second survey during the sixth month after their graduation. The system is capable of sorting the data according to different study fields, matching the initial and current data, analyzing them based on employability attributes, and generating multiple interpretable graphs. In addition, it can extract the Uniform Resource Locator (URL) of email and WhatsApp of graduates who did not respond to the second online survey. Besides, it has a desktop layout to facilitate the user to retrieve any information by a single click. All functions provided by the system has successfully executed and verified. UiTM and HEIs can take benefit from the AOE system for assessing the correlation between the curriculum design, student activities and the employability prospects.