Comparison Between Rule-Based Expert Support System and Machine Learning Expert Support System in KM

Abstract

Listen

Translate article

Machine Learning is gaining popularity nowadays, but we found some key activities involving the business core of the companies still rely on Rule-Based. Therefore, in terms of Knowledge Management, we tried to figure out how Rule-Based and Machine Learning contribute to the Knowledge Management of business (such as providing insights on business intelligence) and e-learning, specifically through their capability as Expert Support Systems. Eventually we are to figure out the comparison between Rule-Based and Machine Learning Expert Support System in the KM. While it can be arguable for the results if we only rely on the qualitative perspective gained from literature study, we then involve AHP to bring the comparison become real, quantitatively. But for reader's knowledge enhancement, we take the chance to also demonstrate quantitatively in even more real case using Orange. This research shows that ML is better than Rule-Based for some points, but there are also points in which Rule-Based is even better. Therefore, even though ML is a new trend with its undisputed capability, Rule-Based is still need; it is even not a bad idea to consider having hybrid Expert Support System in which both ML and Rule-Based exist. Ultimately, this research should bring the insights about the current usage of both through reading this paper, as well as the understanding about the comparison of both to wisely decide which one is to choose to support future business and or e-learning endeavor.