## 6 Conclusions  
For the first time, rice price volatility was measured by involving climate dynamics and macroeconomic variables. For most Asian countries, the results are significant because food security is often linked to staple food availability for the community. Especially after the global food crisis that caused global food prices to jump, knowledge about maintaining price volatility is fundamental, mainly to not interfere with the ability of the poor to provide food for their households. With the threat of future climate change, knowledge of rice price controlling factors must be improved. Attention must also be paid to reducing poverty, which is closely related to the lack of sustainability, due to the higher potential for environmental damage, due to land clearing to meet food needs. The model for measuring rice price volatility has high complexity, and it depends on many variables. An interrelated pattern can be obtained using a combination of market price data at the consumer level and macroeconomic variables with climate variables. The use of models for each province also shows better results than using only one ideal setting for the entire nation. Estimates and predictions of rice price volatility can be used to support the process of determining policies that promote the level of access to food for the community. The ARCH-GARCH model was successfully built after going through several stages. The stationarity ADF test shows a stationary value in the first difference. The Box-Jenkins model for rice prices in Indonesia uses the ARIMA model. ARCH-LM is also proven to be useful in testing the ARCH effect, so that some models continue to use the GARCH method, and some also efficiently use EGARCH. The model can also be used to describe the dependent variable that affects the level of price volatility. The price of rice at the market level in Indonesia demonstrates an increase in value. The volatility that has arisen in the last few years is also getting steeper. In general, low-income farming communities will have a substantial impact on the economy at the household level. It is feared that employment in agriculture will be abandoned because the average farmer's income is low. The macroeconomy is still the most significant factor in Indonesia influencing the levels of price volatility, exchange rate, global price, GPP, and harvest areas as the most dominant factors. These results indicate that although import factors do not predominantly influence the Indonesian market, shocks in the exchange rate can affect rice price volatility. Other factors that are also quite dominant include the inflation rate, farmers' exchange rate, fuel oil prices, and farm wages. Even though they are not as prevalent as the main factors, they can be considered mainly for their impact on the local market level because they can also appear on the micro level. The influence of climate on rice prices is also shown through the indices used, with the SOI and ONI values being the most dominant. This shows that the influence of El Nino and La Nina is the primary driver of the volatility of rice prices in Indonesia, so in the future, we must look not only at the impact of climate on rice production, but also at macroeconomic factors. The influence of phenomena in the Pacific and the effect of IOD, which is a phenomenon in the Indian Ocean, are also quite dominant in influencing rice price volatility in several regions. The combination of climate index data and macroeconomic variables successfully represents the characteristics and patterns of volatility at the provincial level in Indonesia. Of the 33 provinces analyzed, only 3 provinces had a group of representation below 50%. An explanation of other variables that may arise due to the region's uniqueness is needed. However, for provinces that are well described, they can start to use the climate and macroeconomic approach to maintain the sustainability of both agriculture and the economy of the community. Conceptualization, A.W.P., J.S., R.H.K., T.E.B.S.