COVID-19 has caused global problems with complex ramifications. Vulnerable households worry about disruptions to food security. Mobility restrictions, decreased salaries, and supply chain disruptions have increased food insecurity. This study examined the best food security model and its determinants. The primary research data were collected from 257 respondents via cluster random sampling. Binary logistic regression, using R-Studio, was employed to analyze the data. The study showed that the Minimal Model (MM) was optimal in explaining food security status, with three predictors: the available food stock (AFS), education of the household head (EHH), and household income (HIc). This aligned with studies showing that food purchase ability depends on income and education. Male household heads demonstrated better food security than females, while women’s education influenced consumption through improved nutritional knowledge. Higher income provides more alternatives for meeting needs, while decreased income limits options. Food reserve storage influenced household food security during the pandemic. The Minimal Model effectively influenced food security through the AFS, EHH, and HIc. The findings underline the importance of available food stock, household head education, and household income in developing approaches to assist food-insecure households. The research makes a significant contribution to ensuring food availability and promoting sustainable development post-pandemic.

The decline in the productivity of the national sugarcane commodity has become an issue in the last ten years. When domestic demand for sugar is increasing, the decline in productivity indicates a crisis in sugarcane production. At the same time, the involved institutions and strategic programs to encourage sugarcane production have not been well identified. The research aims to determine the institutions that are expected to play a role and the strategic programs that are prioritized in increasing sugarcane production in Southeast Sulawesi, Indonesia. This study uses Interpretative Structural Modeling (ISM) to formulate complexity, hierarchy (levels) and classification among elements. The results showed that of the 14 sub-elements of the acting institutions studied, five institutions were key actors for increasing production, namely banking institutions; universities; agricultural, plantation and fisheries offices; industry, trade, cooperatives, & Small and Medium Enterprises (SMEs') offices; and private companies. Then, from the 13 sub-elements of the strategic programs, there are five strategic programs that also serve as the key programs, namely extension/assisting farmers; addition of plantation labor; providing access to capital; variations of profit-sharing and buying systems of sugarcane; and accuracy of time and adequacy of the supply of raw materials to the mills. This means that these institutions must play an important role, as well as strategic programs that must be carried out effectively to address the issue of sugarcane production in the country. Thus, researchers recommend involving all stakeholders in conducting strategic programs with the key actors as the leading driving institutions.

Purpose: This study aimed to analyze the effect of Inflation on food prices in Palopo City, where the inflation rate is calculated based on index numbers collected from several commodities traded at each price level in the market, namely the Consumer Price Index (CPI). Theoretical framework: The Vector Autoregressive (VAR) method is simultaneous equation modeling that has several endogenous variables simultaneously, but each endogenous variable is explained by lags of its own value and other endogenous variables in the model. Forecasting using the VAR method is in some cases better than complex simultaneous equations. Design/methodology/approach: The stationarity test in this study uses the Augmented Dickey-Fuller (ADF) method, followed by determining lag optimal Akaike Information Criteria (AIC) and Schwarz information Criterion (SC) analysis. The stability test of the VAR model was carried out through the Johansen Cointegration Test at a 5% significance level which produced six equations with a trace statistically more significant than the critical value. Then an analysis of Impulse Response Functions (IRF) was carried out to see the dynamic response of the CPI variable to food commodity prices. The data used are time series for January 2018 to December 2020. Findings: The inflation response to food price fluctuations in Palopo City resulted in three conditions. The Palopo City CPI responded positively to the price fluctuations of garlic and red chili. In contrast, shallots and chicken meat price fluctuations responded negatively to the Palopo City CPI. The Palopo City CPI did not permanently affect the price fluctuations of cayenne pepper and chicken eggs. Research, Practical & Social implications: The practical implication of this research is that food commodity prices still have an influence on inflation movements. Local governments should cooperate with city governments in the production of food commodities by implementing cropping patterns on these commodities to overcome excess production, and it is necessary to carry out off-season production to achieve harvest deficits so that prices remain stable. Improvements to the trade system also need to be improved in addition to the production system. This is intended so that the distribution of food commodity products can be more efficient by implementing supply chain management. Originality/value: Collecting time series data of the Consumer Price Index (CPI) for 6 commodities, namely shallots, garlic, chili peppers, cayenne pepper, broiler meat, and broiler eggs, in a modern model, namely a multivariate time series model with a high level of predictive accuracy of the model among these variables to predict and analyze the effects among these series and estimate the interactions among these series with the latest data is the value of this research, and then provide recommendations for the government in making economic strategies, especially for those related to inflation and food prices.

Currently, cut rose centers in Batu City face many problems that threaten the sustainability of their businesses. Research that combines various dimensions to identify key variables affecting the sustainability of cut rose farming remains limited and is needed. Hence, this study aimed to map and identify the key variables influencing the sustainability of cut rose farming in Batu City, East Java, Indonesia. Primary data were collected through structured interviews with 155 cut rose farmers, selected using random sampling. The employed data analysis technique was the Matrix of Crossed Impact Multiplications Applied to a Classification (MICMAC). The results showed that the key variables influencing the sustainability of the cut flower rose farming business in Batu City are pest and plant disease attacks (PPDA), the use of chemical pesticides (UCP), market objectives (MO), the market chain (MC), and the source of capital (SC). In addition, this study identified key and representative variables from four dimensions based on the Social-Ecological-Technological & Innovation Systems (SETIS) framework, namely extension intensity (social), educational level (social), market objectives (economic), market chain (economic), capital sources (economic), pest and plant disease attack (ecological), use of chemical pesticides (ecological), and cultivation technology (technology and innovation). The study’s recommendations are: (1) increasing the extension intensity and educational level (social dimension); (2) expanding market objectives, shortening market chains, and managing capital appropriately (economic dimension); (3) implementing integrated pest and disease management and limiting the use of chemical pesticides (ecological dimension); and (4) increasing the use of cultivation technologies (technology and innovation dimension).

Maize is a significant food crop in Indonesia’s agricultural development endeavors. In South Sulawesi Province, Bantaeng Regency is one of the regencies that developed corn farming with a large land area. This study aimed to examine the impact of input application on maize yield and assess the degree of efficiency and inefficiency in maize farming. The study was conducted in Bantaeng Regency, utilizing a sample size of 180 households engaged in maize farming as the primary data collection method. The data collected was analyzed using the Stochastic Frontier Cobb-Douglas Model, Technical Efficiency Analysis, Allocative Efficiency Analysis, Economic Efficiency Analysis, and Inefficiency Model. The findings indicated that the variables of land area, seed application, urea fertilizer, insecticide, and herbicide exhibited a significant positive impact on yields of maize. Conversely, the variable of NPK fertilizer had a significant negative impact. In the meantime, it is observed that the labor variable demonstrates a negative impact. The observed values in technical (0.544), allocative (1.840), and economic (1.001) suggest that maize cultivation has not attained technical, allocative, or economic efficiency. Meanwhile, it was also found that the variables significant positive to the technical inefficiency of maize farming are farming experience and education level. Therefore, in a short-term perspective, from a technical-managerial perspective, expanding the area of land under management, increasing the volume of seeds, urea fertilizer, insecticides, and herbicides to the optimum use is the right choice and an effective way for farmers to increase maize production. On the local government side, reviewing the price of certified seeds, subsidizing the price of maize seeds, ensuring the availability of urea and NPK fertilizers, insecticides, and herbicides, and intensifying extension activities and technical guidance on maize cultivation are alternative agricultural policies that the government can implement to support the efficiency and effectiveness of maize farming management.

Agricultural production is a significant contributor to Indonesia's economy. Due to the fact that it is a staple food, rice is a crop that is extremely important to the agricultural sector of the country. The rice production in the Bantaeng Regency has had a consistent decline over the past five years, falling short of the set target. The phenomenon is believed to be attributed to several stages in the production process. Given this, our study objective was to determine the factors that impact rice production in the regency. The field survey for data collection was conducted at the beginning of 2023. The data was collected by the structured interview approach. Then, data analysis in the study was carried out using the Cobb-Douglas function model. The study showed that certain production factors, such as land area, pesticides, herbicides, land processing workers, and plant workers, had a substantial positive impact on rice production. Factors such as seeds, urea fertilizer, NPK fertilizer, maintenance labor, and harvesting labor have no effect on rice production. Rice producers can improve their rice growing practices to boost their rice production. These findings offer important perspectives and a roadmap toward improving rice production management. Variables such as land acreage, pesticides, herbicides, land processing workers, and plant workers should be considered as factors that can boost rice production in the future.