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Indonesia, a tropical maritime continent between the Pacific Ocean and the Indian Ocean, frequently experiences extreme rainfall (ER) that lead to a major disaster such as floods and landslides. These disasters are effect economic activity and impact human daily life, and the future change projection, therefore, is important to reduce the impact of extreme rainfall in Indonesia. In this study, we examined the linking of the annual maximum (AM) of daily rainfall series with climate variability including El Nino Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Madden-Julian Oscillation (MJO) by optimizing statistical extreme value analysis based on daily rainfall data (1985– 2014) observed at ten meteorological stations around the Java and Makassar Islands. Using the trend-free pre-whitening (TFPW) Mann-Kendall test, the AM had significantly increased by 0.983 mm/year (p < 0.001), probably due to intensified sea surface temperature (SST) anomaly by global warming. Furthermore, based on the best selected non-stationary generalized extreme value distribution model, Waingapu and Luwuk covariate significantly with ENSO, while Perak and Jakarta station covariate insignificantly to IOD. The intensified AM during La Nina and negative IOD tend to increase Indonesia SST and then corresponding with the low-level wind convergence that produces upward moisture flux motion, increasing cloud cover that enriches the convection activity. On the contrary, the Madden-Julian Oscillation signal in AM was less prominent in all stations possibly due to weakened mesoscale circulation. During active MJO over Indonesia region, increasing in cloud cover will reduce the solar radiation. This condition is unfavorable for convection activity and therefore, ER is reduced. Finally, analyses of Indonesia ER variability reveal some sensitivity to climate variability in adjacent parts of Indian and Pacific Ocean and trough extreme value analysis, this study highlights the interaction between ER variability and sea-air phenomena around Indonesia.