Alternative Policy Management Framework in Determination of Long-Distance Travel Permit Based on Covid-19-like Symptoms Using Data Mining

Abstract

Even though the obligation to carry out a Covid-19 booster vaccination still applies to long trips using public transportation in Indonesia. One clause regarding checking policy for symptoms of Covid-19 is still often ignored by train passengers because the symptoms of Covid19 are still similar to those of influenza. Somehow, the travel policy is not fair for comorbid person which cannot have Covid-19 vaccination. This research goal is to propose an alternative policy, which is a part of policy management framework, to prevent the transmission of covid19 by long-distance train travel in new era when the enforcement of Covid-19 regulation has been repealed. As alternative of Covid-19 vaccination requirement, the use of data mining algorithm will be proposed ning algorithm to determine whether or not it is permissible to travel long distances by using the dominant covid-19 like symptoms. The results of this study are in the form of a reasoning knowledge regarding the symptoms that passengers need to pay close attention to avoid the risk of transmission of Covid-19. Even though the accuracy of the decision is still 66.67% using C4.5 algorithm, it is the first step to be implemented in a new era, namely the era of prevention of Covid-19, no longer an era of mitigation. The publication of this result is put on bulletin board design