The economic mechanism for the formation of land rent at agricultural enterprises

The current stage of land relations in the agrarian sector is characterized by significant development of lease relations. Today, these relationships are heavily influenced by competition for land tenure, leading to increased land payments. Considering this, as well as the prospects for the agricultural land market formation, the task was to assess the dependence of agricultural land rent on the intensity and economic efficiency of wheat, corn for grain, sunflower production. The research was carried out on the example of agricultural enterprises of Kharkiv region. Grouping, a graphical method was chosen as research methods. The subject of the study was also the rent dynamics for agricultural land in Kharkiv region and Iowa, the USA. The obtained results made it possible to establish the fact that the rent value depends on the total amount of expenses, and the expenses on the articles «wages», «depreciation». It is concluded that the reasons for this may be related to the investment of these enterprises in human capital and the fixed assets that make them lease on more favorable terms for share owners. No dependence was found between the rent value on the value of the yield and the financial result on the selected crops. At the same time, there is a clear tendency that with the increase in the value of the rent, there is an increase in the ratio of its value to the value of costs and income from the crop sector. It is concluded that this can lead to a decrease in investment opportunities for the enterprises with the highest level of lease payments for agricultural land.

Analisa Clustering K-Means Pada Data Informasi Kemiskinan Di Jawa Barat Tahun 2018

Abstract— Poverty is a condition of life that is understaffed by a person or household so that it is unable to meet the minimum or proper needs for his or her life. The poverty Data in each region will differ. It is influenced by many of its supporting indicators. By determining and measuring the indicators of poverty, it will facilitate and recognize the poverty level of the region. Grouping characteristics of a region based on poverty indicators, so that the government can precisely and quickly take policies to mitigate poverty in a region. The method used in this study uses the K-Means Clustering method. The Clustering method is selected because this method has the ability to classify large amounts of data with faster process times efficiently. The object in this study used data published by the BPS (Badan Pusat Statistik) on poverty Data and information in the Regency/city in 2018. Based on the results of this study, the results of the characteristic mapping of each group formed based on the highest and lowest value of poverty indicator of West Java province year 2018. With the characteristics found in each region, it will certainly be a solid foundation for government organizers to provide the right and quick policy/approach to overcome the poverty that is found in the region.

A Novel Coastline Detection Algorithm Based on Modified Iterative Selection Method

Misjudgment often occurred in low contrast remote sensing images, because most widely used image segmentation algorithms often have a larger threshold. To overcome this problem, a novel coastline detection algorithm is proposed. A restriction function is involved into conventional iterative selection process. According to langrage multiplier, a modified iterative selection model is formulated. This modified method utilizes the gradient of images to obtain an optimal threshold. A region grouping rule is proposed to distinguish land and sea. Experimental results show superior performance of proposed method in terms of accuracy. As an application, our method has been applied to extract the coastline of the remote sensing image with promising results.