Improvement of experts’ weights based on Tat Twam Asi in the TOPSIS method as a supporting parameter for optimization of blended learning evaluation results

This research aimed to show the calculation process of the improvement of the experts’ weight values based on Tat Twam Asi in the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method. The calculation process was conducted to obtain an equalization of experts’ weight values. The equivalent experts’ weight values will support the evaluation results optimization of the blended learning implementation. The approach was used in this research was a quantitative approach by simulating the improvement calculation toward experts’ weight values in the TOPSIS method. There were four experts involved in giving weights to each evaluation indicator. Data collection tools of experts’ weight values using questionnaires. The analysis technique of the weighting results was carried out by comparing the fives’ scale effectiveness standards with the total percentage of the expert's assessment average toward the evaluation indicators. The research results showed that the experts’ weights on each evaluation indicator were categorized as very effective because the effectiveness percentage obtained was 90.65%.