<![CDATA[This far power quality analysis from the PHBTR monitoring system is still done manually. This condition creates several challenges in efficiency and accuracy in detecting and responding to changes in PHBTR power quality. With manual processes, collecting and analyzing data related to power quality can be time consuming, and there is the potential for delays in identifying disturbances or anomalies that could affect PHBTR performance. Therefore, in this research an innovative step was taken by applying the fuzzy logic method to simplify and increase the accuracy of automatic power quality analysis. From the analysis results, it was found that the power quality at the MCC4, GRL2, and CKG116 substations when viewed from voltage, current, frequency, and temperature, the three substations were at normal indications (91.32) and in good condition (76.32). However, the load balance quality of the three substations is still not balanced with load imbalance percentages of 110%, 52% and 17% respectively. This is because there are consumers in one phase using higher power than consumers in another phase, so a load imbalance will occur. This can be caused by differences in the use of electrical equipment or loads on each phase. Through this effort, it is hoped that significant improvements in the efficiency and responsibility of the PHBTR monitoring system can be achieved]]>
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