Climate change and its variability are some of the most critical threats to sustainable agriculture, with potentially severe consequences on Indonesia’s agriculture, such as changes in rainfall patterns, especially the onset of the wet season and the temporal distribution of rainfall. Most Indonesian farmers receive support from agricultural extension services, and therefore, design their agricultural calendar based on personal experience without considering global climate phenomena, such as La Niña and El Niño, which difficult to interpret on a local scale. This paper describes the Integrated Cropping Calendar Information System (ICCIS) as a mechanism for adapting to climate variability. The ICCIS contains recommendations on planting time, cropping pattern, planting area, varieties, fertilizers, agricultural machinery, potential livestock feed, and crop damage due to climate extremes for rice, maize, and soybean. To accelerate the dissemination of information, the ICCIS is presented in an integrated web-based information system. The ICCIS is disseminated to extension workers and farmers by Task Force of the Assessment Institute for Agricultural Technology (AIAT) located in each province. Based on the survey results, it is known that the ICCIS adoption rate is moderate to high. The AIAT must actively encourage and support the ICCIS Task Force team in each province. Concerning the technological recommendations, it is necessary to update the recommendations for varieties, fertilizer, and feed to be more compatible with local conditions. More accurate information and more intensive dissemination can enrich farmers’ knowledge, allowing for a better understanding of climate hazards and maintaining agricultural production.

Coffee is an annual crop sensitive to climate variability. Most Indonesian coffee is cultivated on marginal lands that are vulnerable to environmental changes, including climate. Indonesia's climate variability is influenced by several factors, including the monsoon, local aspects, and global climate oscillations such as the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). It is crucial to identify the impacts of climate variability on both the production and the economy to develop adaptative measures. This study aims to determine the effects of global climate variability, namely ENSO and IOD, on coffee production in several Indonesian production centers. It uses annual coffee production data in the five major production centers in Indonesia. The ENSO indicators used in this study were the Oceanic Nino Index (ONI) in the Nino 3.4 region and the IOD indicator in the Dipole Mode Index (DMI). The production anomaly analysis approach in neutral years and the extreme ENSO and IOD phases were applied in this study. The results showed that the effects of ENSO and IOD were different in each region. The highest decline in production occurred in the La-Nina year in almost all production centers. The decline in output in the La-Nina year ranged from 6 to 22%. Meanwhile, the IOD that had a decreasing effect on production was positive IOD with a decrease ranging from 1 to 15%. Key words: ENSO; IOD; Economy; Climate change.

As a result of plans to relocate the Indonesian capital city to East Kalimantan province, Kalimantan is expected to develop rapidly and the surrounding regencies and provinces will become food support areas for the new capital. However, the vulnerability of food farming in Kalimantan is a concern that must be addressed to ensure food security. This study aims to assess the vulnerability of food farming at the regency level of the island of Kalimantan, to assess the determinant factors of the food farming vulnerability and to compose adaptation measures that can reduce vulnerability. Socio economic, climate, water and land data are sorted and analyzed to represent the level of sensitivity and exposure index (SEI) and adaptive capacity index (ACI). Locations with ‘High’ and ‘Very High’ levels of farming vulnerability become interview sites with a total of 150 respondents. The results of the interviews strengthen the results of the vulnerability analysis which helps to determine the condition of farmers and food farming in vulnerable locations. The results indicated ‘Very High’ and ‘High’ level of vulnerability in 14 regencies/cities. Floods are climate-related disasters that most often affect farmers surveyed (46%), followed by droughts (30%) and pest attacks (24%) with significant impacts (49%). The identification of the determinant factors becomes the basis for adaptive measures to support decision-makers, local practitioners, and farmers by highlighting local challenges and proposing local-specific adaptation strategies.