Juvenile Myoclonic Epilepsy (JME) is part of the Idiopathic Generalized Epilepsies (IGEs), of which electroencephalographic (EEG) background activity is normal for age. Consequently, this behavior makes its diagnosis challenging by visual inspection if there are no clinical manifestations. Despite this, previous works suggest that JME patients have significant differences in their connectivity and frequency patterns when compared to healthy controls. In this work, the Approximate Entropy (ApEn) and Multiscale Sample Entropy (MSE) measures are proposed to elucidate the significant differences in the level of irregularity of scalp EEG signals from untreated JME patients vs healthy individuals. Thirty-seven recordings were obtained from a database of JME patients without medication and healthy controls (17 and 20 recordings, respectively) with mean ages of 20.6 years in both groups with a standard deviation of ±7.7 and ± 7.9, respectively. A 150 s-window of background activity (without epileptiform discharges) was selected from each recording. Signals were conditioned and the ApEn and MSE indexes were calculated for subdivided 1 s-segments without overlapping. The Mann-Whitney U test and a Bonferroni correction were applied to obtain the significant differences. The results show a significant increase in entropy values of JME patients, referring to healthy ones (p < 0.05); the differences are predominant in frontocentral and temporal regions. These findings suggest a potential biomarker to identify JME background activity using entropy measures and lead to an insight into the brain dynamics of this disease.