Including Land Area Research Articles

Technical and Economic Efficiency of Production Factors in Javanese Tobacco Farming: A Case Study of Belun Village, East Java

This study analyzes the technical and economic efficiency of production factors in tobacco farming in Belun Village, Temayang Subdistrict, Bojonegoro District, East Java. Using stochastic frontier software 4.1, the analysis was conducted with a sample of 87 Javanese tobacco farmers. The production inputs evaluated include land area, seeds, urea fertilizer, NPK fertilizer, NPK Phonska Plus fertilizer, labor, pesticides, and production output. The results indicate that the gamma elasticity coefficient for technical efficiency is 0.949, with all variables being statistically significant at the 1% level (t-table 2.64), except for pesticide input, which is significant at the 5% level (t-table 1.99). In the economic efficiency analysis, seedlings were identified as the inefficient input with an efficiency estimate (EE) of > 1 (52.4), while other inputs showed EE < 1. The study concludes that 94.9% of the inefficiency stems from production factors, while 5.1% is attributed to external factors. Moreover, the inputs used in Javanese tobacco farming are neither technically nor economically efficient. To achieve full technical efficiency, farmers should reduce inputs such as land area, NPK fertilizer, and NPK Phonska Plus fertilizer, while increasing the use of seeds, pesticides, urea fertilizer, and labor.

Technical Efficiency Of Rice Farming Around The Nickel Mining In Konawe Selatan District

South Konawe Regency has vast potential agricultural land, It can support the regional economy by supplying the food needs of the community and being a major player in trade across districts. In addition to providing food, the agricultural sector also serves as a market for goods produced by the industrial sector in rural communities and urban areas, a source of labor for industry, a source of capital for modern economic growth, particularly in its early stages, and a source of foreign exchange. Policy support is needed from the government in developing the agricultural sector considering the importance of synergy between the agricultural and mining sectors to minimize negative impacts in order to achieve economic balance so that it becomes the basis for local governments in taking appropriate policies to support the agricultural sector amidst mining activities. The purpose of this study is to examine lowland rice farming's technical effectiveness and production characteristics in the vicinity of South Konawe Regency's nickel mine. The data collected used primary and secondary data, with a total of 20 farmers as respondents. Stochastic Frontier Analysis (SFA) was utilized to analyze the data. The findings of the study indicate that lowland rice farming is technically efficient when it is conducted near nickel mining and that the production elements that actually affect lowland rice farming include land area, labour force, urea and NPK fertilisers, and insecticides.

Comparative Analysis of Multiple – Linear Regression Algorithm with Random Forest Regression for Prediction of House Plot Prices

Humans basically have a basic need to have a place to live, which can be a house or shelter. Along with the rapid population growth in Indonesia, which continues to increase every year, many people do not have or have a decent place to live. Therefore, careful planning is needed so that every family can have a decent home. One very important aspect in planning investment in the form of property is predicting future house prices. One approach that can be used is to use a Random Forest and Multiple Linear Regression algorithm, which is an algorithm from Machine Learning. There are several factors that can influence the price of a house, including land area, building area, number of bedrooms, bathrooms and garage. In this research, multiple linear regression and random forest regression methods were chosen. The aim of this research is to find the best prediction results between the two methods. To achieve accurate predictions, research was carried out repeatedly by dividing the dataset into 80% for training and 20% for testing. The research results show that the random forest regression algorithm provides the best results, with an accuracy of 81.6%.

EFISIENSI PENGGUNAAN FAKTOR PRODUKSI PADA USAHATANI CABAI RAWIT DI KECAMATAN SAKRA KABUPATEN LOMBOK TIMUR

The research aims to: (1) Analyze production factors that influence the production of cayenne pepper farming in Sakra District, East Lombok Regency; (2) Analyzing the efficiency of using production factors in cayenne pepper farming in Sakra District, East Lombok Regency. The method used is a descriptive method, while data collection was carried out using survey techniques on a sample of 30 respondents. Data were analyzed descriptively quantitatively, using the Cobb-Douglas model regression function. The results of the research show that: (1) Production factors that have a positive influence on the production of cayenne pepper farming in Sakra District, East Lombok Regency include land area, seeds, urea fertilizer, NPK, and pesticides, meanwhile. Production factors that were declared to have no effect included the variables SP-36 fertilizer and labor; (2) The use of production factors (input) for cayenne pepper in Sakra District, East Lombok Regency, in the form of land area, Urea, NPK, SP-36, and pesticides is not yet efficient (its use is still insufficient), while the use of production factors in the form of seeds and labor is not efficient (excessive).

Exploring correlations between economic indicators with natural and societal factors based on linear regression model

Existing research on the determinants of a nations economic development has predominantly centered on individual factors, including energy, land resources, education, taxes, employment, and healthcare. Regrettably, there is a paucity of studies that holistically examine these factors collectively and assess their respective contributions to economic development. Therefore, the primary objective of this study is to investigate the interrelationships between economic indicators and various natural and societal factors. The article firstly uses the Pearsons correlation coefficient to filter out a portion of the higher degree of correlation from factors that may have an impact on the countrys economic development for further analysis. For the selected factors, using two linear regression models: Ordinary Least Square (OLS) method for preliminary modeling for the extent of affects between each factors and economy; and Fully Modified Ordinary Least Squares (FMOLS) method, as an optimization model, further eliminating the less influential variables. After obtaining the final impact model of the linear correlation, the data is screened based on the variables within the model. A portion of the selected data is used as a training set for training the model and the remaining data is used as a test set for testing the performance. The results of the study show that factors including land area, army size, CO2 emissions, population, minimum wage, would have varying degrees of integrated impact on the economic development of the country.

The causal-effect model of input factor allocation on maize production: Using binary logistic regression in search for ways to be more productive

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.

Motivation of farmers in crystal guava seed business in bonorowo district, kebumen regency

This study aims to determine the motivation of farmers in crystal guava farming and factors related to farmers' motivation in crystal guava farming in Bonorowo District, Kebumen Regency. The number of respondents in this study was 38 crystal guava farmers. The analysis used is descriptive analysis, scoring techniques, and Spearman Rank correlation analysis. The results show that the motivation of farmers in crystal guava farming is seen from the need for existence, the need for relatedness, and the need for growth is in the high category. Overall, motivation is also classified as high with a score of 50.7. Internal factors that have a significant relationship with existence are land area, amount of production, and income, but no significant relationship was found from internal factors with farmer relatedness, while with growth, namely land area, amount of production, and income. And internal factors that have a significant relationship with the level of farmer motivation include land area, amount of production, and income. External factors that have a significant relationship with existence are the availability of capital assistance and local cultural suitability, but no significant relationship from external factors with relatedness and growth was found. The external factors that have a significant relationship with the level of farmer motivation include capital assistance and local cultural suitability. There needs to be support from across stakeholders so that farmers' motivation can be increased.

Analysis of Input Optimization for Cassava (Manihot esculenta) Production in the Marga Tiga Sub-District East Lampung District

This study aims to ascertain how production inputs affect cassava farming production and examine how to use production inputs as efficiently as possible. The research location was selected because the research area is a center for cassava production. The Cobb-Douglas production function model is an analytical technique used to assess how production inputs affect cassava output. Analyze the level of input utilization optimization at the same time by comparing the marginal product's value to other inputs. The study's variables included land area, labor, seeds, urea-fertilizer, NPK-fertilizer, ZA-fertilizer, SP36-fertilizer, herbicides, and production yields. The result of this research is that production inputs simultaneously influence cassava production. Several production inputs used in cassava farming in Marga Tiga District are still not optimal and need to be added, including land area, organic fertilizer, urea fertilizer, and ZA fertilizer. Meanwhile, several other production inputs, namely labor, seeds, NPK fertilizer, SP 36 fertilizer, and herbicides, are not optimal, so farmers need to reduce them.

IMPLEMENTATION OF THE EDAS METHOD IN SELECTING INVESTMENT IN THE AGRICULTURAL SECTOR

Capital is one of the most important things in any business activity that will be carried out. Capital includes capital before planting, planting period until harvest time arrives and post-harvest. Because of the large number of farmers in Kuningan district, the Kuningan district Food Security and Agriculture Agency needs investors to help the farmers. In this study designing and building applications for selecting investments in the agricultural sector using a decision support system with the EDAS method. EDAS is a multi-criteria decision-making method based on the AS score. The data used is data from direct interviews with farmers to determine criteria, sub criteria and alternatives. The criteria include land area, capital, harvest period, yields, and selling price. The alternatives include the names of the farmers, namely Tati, Niryo, Odah, Umin, and Tarwa, as well as types of farming, such as chili, shallots, rice, corn, and peanuts. From the results of the overall calculation of this study, it shows that the EDAS method produces the best choice for Tati farming with the type of chili farming. This research produces a web-based application that can be used by farmers and investors and furthermore, it can be developed into an Android or mobile-based application. The goal is to make it easier for investors to find and choose the best farms to invest in.

Discussion of some legal provisions on complaints related to land field and modification recommendations

Complaints are one of the constitutional rights, in order to ensure the direct democratic rights of individuals and organizations when having grounds to believe that administrative decisions and acts of competent State agencies, persons authorized by the State the empowering country is illegal, infringing upon its legitimate rights and interests. Currently, the law on complaints does not have specific provisions to deal with land-related complaints, but only in the Law on Complaints 2011. Therefore, it is necessary to amend and supplement some legal provisions are objective requirements to meet the protection of the legitimate rights and interests of land users. On that basis, the author of the article presented, analyzed and explained the contents related to complaints and settlement of complaints; including land areas such as: (i) The statute of limitations for making a complaint; (ii) The inheritance obligation to settle administrative complaints and the right to inherit administrative complaints; (iii) Apply temporary emergency measures; (iv) Responsibility for first-time complaint settlement; (v) Simplified procedures for settlement of complaints in case agricultural land is recovered for construction of irrigation and hydropower projects. Through legal provisions and practical application of complaint settlement in the field of land, the author has proposed to amend and supplement a number of relevant legal provisions, in order to contribute to the improvement of the law.

Pengaruh Luas Lahan dan Produksi CPO Terhadap Pertumbuhan Industri Kelapa Sawit Indonesia Tahun 2000-2020

This study aims to analyze the effect of economic indicators including land area and palm oil (CPO) production on the growth of the palm oil industry in Indonesia. Data on land area variables includes all land planted with oil palm, both smallholder plantations, large state plantations and large private plantations. This study uses secondary data with a time span of 21 (Twenty One) years, namely from 2000-2020. The method used in this research is descriptive and verification method with a quantitative approach. The population of this study includes the six largest palm oil producing provinces in Indonesia, namely Riau, Central Kalimantan, West Kalimantan, North Sumatra, East Kalimantan and Jambi. Thus, the sample size used in this study is 6 provinces times 21 years, namely 126 panel data samples using the Random Effect Model (REM) model. This study uses data processing software Eviews 12. The results of this study indicate that the variables of land area and production of palm oil (CPO) together have a positive and significant effect on the growth of the Indonesian palm oil industry. If tested partially, the area of ????oil palm plantations is significant and has a positive influence on the growth of the Indonesian palm oil industry. However, CPO production has a negative effect on the growth of the Indonesian palm oil industry.

Rancangan Penyuluhan untuk Mengubah Persepsi Petani Ubi Jalar Terhadap Pengendalian Hama Lanas Menggunakan Daun Mimba dan Feromon

One of the obstacles in the sweet potato production system is the attack of the sweet potato weevil (Cylas Formicarius) that is the main pest on sweet potato plants. The efforts of farmers in Maja District to deal with these pests are still low and depend on the use of chemical pesticides. The behaviour of farmers is influenced by the perception of farmers who consider chemical pesticides to be the main solution in controlling plant-disturbing organisms. Innovations in pest control can be carried out with preventive measures such as the use of pheromone that trap and disrupt pest mating and plant-based insecticides that are more environmentally friendly. The study aims to analyze the perception of sweet potato farmers on controlling sweet potato weevil pests through the use of pheromones and neem leaf vegetable insecticides, related factors and strategies that can be done in increasing farmers' perceptions. The results of descriptive analysis of 72 sample respondents can be seen that the perception of sweet potato farmers in Maja District on the use of pheromones and neem leaf vegetable insecticides in controlling sweet potato weevil pests is in the poor category with a value of 49.9%. The results of the correlation analysis of rank spearman at a significance level of 5% (0.05) show related factors including land area, income, technical aspects and social interaction.

Factors affecting the income of organic shallot farmers in Boyolali Regency

The consumption of organic products has become a new trend that is more environmentally friendly, healthy, and at better prices advantageous for farmers. Furthermore, organic farming reduces the greenhouse effect and global warming by absorbing carbon into the soil. This study aimed to determine the income factors of organic shallot farming and the cultivation efficiency in Boyolali Regency using the descriptive method. A simple random sampling technique was used to obtain the sample, consisting of organic shallot farmers in Cepogo District, Boyolali Regency. The R/C Ratio measured the efficiency of Shallots farming, and multiple linear regression analysis was used to determine the factors that affect farmers’ income. The results showed that the efficiency of organic shallot farming was very good, as evidenced by the R/C ratio of 2,34. Farmers produce their farm inputs to reduce production costs. Factors that affect the income of organic shallot farming include land area, seeds, organic fertilizers, pesticides, and labor. Furthermore, they need improvements on the timeliness of application and how to apply a liquid organic fertilizer to create efficiency in cultivating shallots.

Analisis Efisiensi Penggunaan Input Produksi Usahatani Bawang Merah Pada Masa Pandemi Covid-19 di Kecamatan Peukan Bada Kabupaten Aceh Besar

Shallot production in Peukan Bada experiences ups and downs every year. During the Covid-19 pandemic, shallot production in Peukan Bada decreased due to the high price of production inputs which resulted in the inability of farmers to meet production inputs as usual. This study aims to determine the effect of using production inputs in the form of land area, seeds, organic fertilizers, inorganic fertilizers, pesticides and labor on shallot production during the Covid-19 pandemic in Peukan Bada and to determine the level of efficiency in the use of production inputs in shallot farming. during the Covid-19 pandemic in Peukan Bada. This research uses Cobb Douglas production function analysis method and price efficiency analysis. The results showed that the coefficient of determination was 0,935 which explained that 93,5% of shallot farming production was influenced by the variables of land area, seeds, organic fertilizers, inorganic fertilizers, pesticides and labor, while the remaining 6,5% was explained by other factors. outside of this research. At a significant value of 0,000 0,05, which means that the use of production inputs which include land area, seeds, organic fertilizers, inorganic fertilizers, pesticides and labor simultaneously have a significant effect on the production of shallots in Peukan Bada District. While partially only seeds have a significant effect on shallot production with a significant value of 0,007 0,05 while for land area, organic fertilizers, inorganic fertilizers, pesticides and labor, it is known that the sig (p-value) 0,05 so it has no effect. significant effect on shallot production in Peukan Bada. In the efficiency analysis, it is known that the value of NPMx/Px 1, so that the use of seeds, inorganic fertilizers and labor is not efficient when observed in terms of price so that the use of production inputs must be added to achieve efficiency. Then on the variables of land area, organic fertilizers and pesticides, the value of NPMx/Px 1 is known so that the use of these inputs is not efficient when observed in terms of price so that the use of production inputs must be reduced in order to achieve efficiency, achieving efficiency will optimize the production inputs used so that the production results become maximum and increase farmers' income.

Faktor Yang Mempengaruhi Produksi Tembakau (Nicotiana tabacum) Di Kecamatan Sulang Kabupaten Rembang

This study aims to determine the factors that influence tobacco production and determine the level of efficient use of inputs on tobacco production factors. This research uses a stratified random sampling method with 63 farmers as respondents. The analysis used is multiple linear regression and calculation of economic efficiency. The results stated that the R2 value obtained through multiple linear regression analysis was 0.890, meaning that the contribution of independent variables (land area, number of laborers, number of seedlings, amount of TSP fertilizer, amount of ZA fertilizer, amount of ZK fertilizer, number of pesticides) to tobacco production was 89 percent, while 11 percent is influenced by other variables outside the model. The results of the F-test were jointly influential and the t-test showed variables that influenced tobacco production including land area, number of laborers, number of seeds, amount of ZA fertilizer, and amount of pesticides. Variables such as the amount of TSP fertilizer and the amount of ZK fertilizer had no significant effect. The use of production factors in tobacco farming has not been efficient. Keywords: Efficiency, Production, Tobacco.

Prediksi Harga Rumah Menggunakan Web Scrapping dan Machine Learning Dengan Algoritma Linear Regression

Tempat tinggal atau rumah merupakan salah satu dari banyaknya kebutuhan primer bagi manusia. Maka dari itu sangat penting untuk membuat perencanaan agar tiap keluarga dapat memiliki tempat tinggal pribadi. Dalam perencanaan tersebut dibutuhkan prediksi atau perkiraan harga di masa mendatang. Maka, tujuan penelitian ini bertujuan untuk membuat model prediksi harga rumah menggunakan metode machine learning adapun algoritmanya adalah linear regression. Dengan melakukan web scraping untuk mengumpulkan data, melalui beberapa website yang bergelut dibidang jual beli rumah. Adapun menurut developer rumah yang berhasil ditanyakan dilapangan terkait variabel yang mempengaruhi harga rumah diantaranya luas lahan, luas bangunan berdiri, banyaknya kamar tidur, banyaknya kamar mandi, dan ketersediaan tempat parkir mobil. Untuk mendapatkan nilai prediksi yang tinggi penelitian dilakukan secara berulang kali namun nilai prediksi terbesar dengan menggunakan 80% dataset untuk training dan 20% dataset digunakan untuk testing menghasilkan nilai output dengan tingkat akurasi dalam memprediksi sebesar 88%.

Factors Affecting the Production of the Coffee Farming in Uluway Village Mengkendek Sub District Tana Toraja District

This study aimed to determine what factors influence coffee production in Uluway Village, Mengkendek Sub District of Tana Toraja District. The research was conducted from March to May 2020 where these factors include land area, labor, fertilizers, and pesticides. This study aimed to determine what factors influence the people's coffee production in Uluway Village, Mengkendek Sub District of Tana Toraja District. The population of this study was all the farmers who cultivated coffee in Uluway Village, Mengkendek Sub District of Tana Toraja District. The sample of this study was 78 respondents who were determined by using the census method. The analytical method used is descriptive qualitative data analysis, the second data analysis using multiple linear regression analysis, and the third. The research results can be drawn from several conclusions, including the coffee farming processing techniques in Uluway Village, namely land preparation, planting, maintenance, harvesting, and postharvest. Factors that have a real effect include land area, fertilizers, and pesticides, while factors that do not affect coffee production are labor

The effect of attractant production factors on the income of curly red chili (Capsicum annum L.) farming (case in Pasirwangi District, Garut Regency)

Curly red chili (Capsicum sp) is one of the commercial horticultural commodities that has a major obstacle in its cultivation, namely of the attack of Plant Pest Organisms. One type of pests that often damages chili plants is fruit flies (Bactrocera spp) which can be controlled using an attractant. This study aims to analyze the factors that influence the production of curly red chili in farm with attractant utilization and without it and also their effect to farmers’ income. This research was conducted in Pasirwangi District, Garut Regency using a survey method on 72 farmers of red curly chilies. Data were analysed using multiple regression of a production function where one of the dummy production factors was the usage of attractant and non-attractant. The results showed that the production factors including land area, seeds, NPK fertilizer, organic fertilizer, labor and attractants had a positive effect on the production of curly red chilies. Partially, the production factors such as urea, Za fertilizer, KCl fertilizer and pesticides did not have any effect on the production of curly red chilies The income of attractant users was higher than those who were not using attractants.

Сравнительный анализ и интерпретация данных grace и grace-fo

The study is devoted to the analysis of the features of the change in the Equivalent Water Height (EWH) parameter over the geoid based on satellite measurements of space systems. The study used the GRACE and GRACE-FO satellite data archive. The assessment was carried out on Earth as a whole, including land areas and the World Ocean. Interpretation of the anomalous state of the geoenvironment is performed using digital maps of the spatial distribution of the EWH parameter based on the histogram approach and correlation analysis. Also, a comparative analysis of the studied data from the GRACE mission and data from the new GRACE-FO satellite system launched into orbit in the summer of 2018 was carried out.

Comparing k-nearest neighbor and k-means methods for clustering Indonesian farmers’ welfare

A farmer’s welfare classification can be performed to accommodate all significant issues that will assist policymakers, government, and scientists. This study aims to compare K-Nearest Neighbor (K-NN) and K-Means methods for clustering Indonesian farmers’ welfare using the fifth wave of Indonesia Family Life Survey (IFLS 5) data. The K-Means method is an unsupervised learning algorithm by classifying the data according to the closest distance between observed and centroids. The K-NN method is a supervised learning algorithm by classifying most of the nearest neighbour data. This study used fifteen factors affecting farmers’ welfare including land area, type of water, type of rice, income, expenditure, loan, mobile phone use, harvest frequency, crop failure, land ownership, gender, age, level of education, home ownership, and ownership of health insurance. The K-NN performed well to classify farmers’ welfare as the K-Means methods in the district data, with an accuracy of 89.8% compared to 53.7%. The K-NN classification results in provinces data showed that the provinces of Bali, East Java, South Kalimantan, Lampung, West Nusa Tenggara, South Sulawesi, and South Sumatra were included as prosperous provinces; while the provinces of Banten, DI Yogyakarta, West Java, Central Java, West Sumatra, and North Sumatra were included as non-prosperous provinces.