This study delved into the impact of input factor allocation on maize production, seeking to identify strategies for enhancing productivity. The primary data for this study were collected from maize farmer households and analyzed using the binary logistic regression model (BLRM). Consequently, the simultaneous examination of the twelve independent variables using the BLRM yielded a noteworthy impact on maize production. Meanwhile, five of the twelve variables examined in part revealed a significant and positive impact on maize production. The variables that demonstrated statistically significant positive relationships consisted of land area, labor, urea fertilizers, insecticides, herbicides, and labor. Then, seed application and NPK fertilizer variables had a negative and significant influence, whereas the other variables did not. The results of this study indicate that some production factors employed by farmers significantly affected maize yield. This information may be used to develop a practical strategy for enhancing productivity in maize farming. Some practical implications in immediately oriented recommended: the expansion of maize farming area managed by farmers and the increase in the volume of application of urea fertilizers, insecticides, and herbicides, as well as the increase in the number of workers in maize farming, are expected to encourage an increase in maize production. The results of this research also contribute to the existing knowledge by providing empirical evidence that clarifies the positive and significant impact of various production inputs, which include land area, urea fertilizers, insecticides, herbicides, and labor, on maize production and productivity. It also supports the objective of promoting more efficient farming practices.

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.

The research objective was to examine the factors influencing the effectiveness of agricultural extension in clove farming in Sidrap Regency. Primary data were collected using structured interviews with 140 selected clove farmers to achieve this objective. The binary logistic regression model was employed to test the influence of fourteen independent variables on the dependent variable. The research results indicated that the variables of family size, mass communication approach, electronic media, and clove cultivation material significantly and positively impacted the effectiveness of agricultural extension in clove farming. Meanwhile, the variables of educational attainment, farming experiences, farmers’ cosmopolitanism, print media, and land area had a negative significant effect, and the other variables had no significant effect. These findings are important indicators and valuable insights in promoting and encouraging the effectiveness of extension in clove farming. The findings emphasize the significant role of family characteristics, agricultural extension approaches, and communication delivery methods in the diffusion of agricultural technology and enhancing the effectiveness of agricultural extension. Based on the research results, policy recommendations are proposed to enhance extension effectiveness in clove farming, specifically, augmented farmer education on clove cultivation and the intensification and extensification of mass extension methods, as well as using electronic media in extension activities.

Over the last two decades, the growth of the fisheries sector in Indonesia has shown an increasing trend; however, behind the rapid development of this sector, the role of small-scale fisheries as one of the main actors supporting the whole industry is often neglected. They remain poor and continue to conduct fishing activities traditionally. Therefore, this study aims to describe the real situation of small-scale fishers, analyzing the fishers’ ownership of the boat they use, analyzing their income level to reveal their poverty status, and analyzing the factors affecting their income. The regression analysis results indicate that boat category, sea fish catch, fish selling price, fixed costs, and variable costs have significant effects on fishers’ net incomes.

The research objective was to examine the factors influencing the effectiveness of agriculture in clove farming. Primary data were using structured interviews and a simple random sampling method to select 140 respondents, clove farmers. The binary logistic regression model was employed to test the influence of fourteen independent variables on the effectiveness of agricultural extension in clove farming. The research results indicated that the variables of family size, mass communication approach, electronic media, and clove cultivation materials significantly and positively impacted the effectiveness of agricultural extension in clove farming. Meanwhile, the variables of educational attainment, farming experiences, farmer cosmopolitan, print media, and land area had a negative significant effect, and the other variables had no significant effect. These findings are important indicators and valuable insights, promoting and encouraging the effectiveness of extension in clove farming. The findings emphasize the significant role of family characteristics, agricultural extension approaches, and communication delivery methods in the diffusion of agricultural technology and enhancing the effectiveness of agricultural extension. Based on the research results, policy recommendations are proposed to enhance extension effectiveness in clove farming, specifically augmented farmer education on clove cultivation and the intensification and extensification of mass extension methods alongside using electronic media in extension activities.