Agricultural extension workers play an essential role in the productivity of agricultural systems. Based on the actual conditions in the field, it can be seen that the level of extension services still needs to be higher due to a lack of human resources in the field of extension services. This research was conducted to determine the effectiveness of agricultural extension services andthe factors that influence the effectiveness of agricultural extension to farmers in Baubau City, Indonesia. The analytical method includes exogenous latent variables: human resources, technological progress, farming capital, farmer age, education, and farming experience. The effectiveness of agricultural extension is used as an endogenous latent variable. The research sample consisted of 110 rice farmers in Baubau City, and the Slovin formula was used to calculate the sample. The data collection for this research was carried out by distributing questionnaires to respondents, in-depth interviews, and direct observation in the city of Baubau. Using the AMOS application, quantitative analysis was carried out through structural equation modeling (SEM). The study results show that: (1) The factors that influence the effectiveness of agricultural extension in Baubau City are farming capital, farmer age, education, farming experience, and human resources, and (2) the influence of these factors on the effectiveness of agricultural extension is as follows: if the farming capital is high, human resources can be increased. In addition, the higher the farmer’s age, the lower the need for human resources. It is also noted that higher farmer education contributes to increased human capital, and increased experience in farming is associated with increased human capital. Thus, an increase in human resources will increase the effectiveness of agricultural extension. Significant factors that influence the effectiveness of agricultural extension in Baubau City, Southeast Sulawesi, are farming capital, farmer age, education, farming experience, and human resources.

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.

This study examined the socioeconomic factors that influence the adoption of information and communication technologies (ICTs) in enhancing farm productivity among farmers in Ba Province, Fiji. A structured questionnaire survey was administered to a sample of 320 randomly selected farmers across the province’s 16 mainland districts. The analysis demonstrated that, although farmers possessed conventional ICTs, there was no direct correlation between ownership and actual utilisation. Significant determinants affecting ICT use were identified as education, experience, type of farming, and business model. These findings underscore critical implications for both policy and theoretical frameworks, emphasising essential factors to consider in the implementation of ICT solutions for agricultural practitioners.