Characteristics of Rainfall Influence Indian Ocean Dipole (IOD) and Madden Julian Oscillation (MJO) Phenomena Based on Machine Learning in Deli Serdang Region

Abstract : Rainfall in the Deli Serdang region is influenced by global climate phenomena. This study aims to determine the characteristics of rainfall based on machine learning due to the simultaneous occurrence of IOD and MJO in the Deli Serdang region. This study uses a descriptive method and Pearson correlation analysis using rainfall, IOD, and MJO data. The results of the study with machine learning showed that the accuracy value of the SVM model was 56.16% and when the MJO was strong and the IOD was positive in January – December 2024 in the Tuntungan region, the highest was 258 mm and the lowest was Bandar Khalipa 167 mm. Strong MJO and Negative IOD were found in December 2022, the highest area was Sibiru-biru 264 mm and the lowest was 146.16 mm. Weak MJO and Positive IOD in the low-lying Bandar Khalipa region were 140 mm. Dry months can be predicted using several indicators, including the MJO (Madden-Julian Oscillation) and IOD (Indian Ocean Dipole). However, dry months are more often predicted using the IOD indicator. IOD has a significant influence on rainfall in Indonesia, especially in eastern Indonesia. When IOD is in a positive phase, rainfall in Indonesia tends to decrease, increasing the possibility of a dry month. MJO has a greater influence on rainfall on a shorter time scale, such as weekly or monthly. MJO can affect rainfall in Indonesia, but its influence is not as great as IOD in predicting dry months.