<![CDATA[Gestational diabetes is a state of high blood sugar levels that occur during pregnancy. The presence of this disease is common and usually occurs in the 24th to 28th week of pregnancy. However, the condition of this high blood sugar level cannot be underestimated because it can cause several complications that can harm both mother and baby. In addition, untreated gestational diabetes can also increase the risk of type 2 diabetes for both mother and baby in the future. The cause of the onset of gestational diabetes is not certain. However, gestational diabetes is a multifactorial disease which the presence can be caused by various factors that play a role in increasing the risk of this disease. Therefore, gestational diabetes becomes difficult to diagnose because doctors need to consider these factors, analyze them, and compare them with previous patients under similar conditions. Eventually, the diagnosis depends on the doctor's interpretation and is prone to human error. A solution that can be applied is by using a classification algorithm that can identify the presence of gestational diabetes. Pima Indians Diabetes Dataset is a dataset that is widely used in some research of diabetes prediction. This dataset has a characteristic of imbalanced data, so that Neighbor Weighted K-Nearest Neighbor (NWKNN) can be applied to the dataset. By deleting data containing missing value and testing the value of K and E of NWKNN, the best results for sensitivity was 0,8125, specificity was 0,8788, and F1 score was 0,7879 were achieved at K = 25 and E = 2. Meanwhile for k-fold cross-validation testing, the NWKNN algorithm was found to be better than K-Nearest Neighbor (KNN). The best results were obtained by 4-fold cross-validation test i.e. sensitivity was 0,6043, specificity was 0,8703, and F1 score was 0,6383.]]>
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