Amount Of Rice Production Research Articles

Calculation of Rice Farming Insurance Premium Price in Magelang City Based on Rainfall Index with Black-Scholes Method

Indonesia is a country with two seasons, the rainy season and the dry season. Unstable rainfall can affect rice production and may cause crop failure. The amount of rice production in Indonesia, one of which is in Magelang City, is quite large, so the losses that may be experienced are quite significant. Therefore, a way to reduce the impact of losses experienced by farmers is needed, one of which is through the rice farming insurance program. The purpose of this study is to determine the premium price of rice farming insurance based on rainfall index based on the exit value and trigger value in each growing season. Insurance using the rainfall index can provide protection to farmers due to too little rainfall or too much rainfall. Too much rainfall can cause damage to rice plants resulting in crop failure. The premium calculation method uses the Black-Scholes principle, while the exit value and trigger value are determined by the Historical Burn Analysis method. The result of this study is to obtain various trigger values and exit values as well as premiums that must be paid by farmers in each normal, high, and low (dry) rainfall condition. This value determines the premium price obtained for normal rainfall which is IDR 735,739.66 to IDR 871,698.64, for high rainfall the premium price obtained is IDR 1,404,184.75 to IDR 1,643,307.75, and for low rainfall (dry season) it is IDR 5,541,806.10 to IDR 6,689,629.88.

ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI PENDAPATAN PADI ORGANIK DI KECAMATAN HARAU

Excessive use of chemical fertilizers causes a decrease in soil quality so that rice production decreases, even though the production costs incurred by farmers continue to increase due to the increasing price of chemical fertilizers. The purpose of this study was to determine what factors affect the income of organic rice farmers. This study used a survey method, where the determination of the research area was carried out deliberately and selected Nagari Koto Tuo Harau District. Determination of research samples using proportional stratified random sampling method, where the number of samples is 25 farmers. Data collection is done by interview and direct observation. Data analysis method used is kunatitatif analysis using multiple linear regression analysis. The results showed that the factors that significantly affect the income of organic rice farmers are land area, production costs, the amount of rice production and the price of rice. While the factors that affect insignificantly are age, education and other jobs. Keywords: Analysis, rice, organic, Yield

Analysis of Factors Influencing Rice Production in Labuhan Batu District

This study aims to analyze the factors that influence rice production in Labuhan Batu District. The research was conducted in Labuhanbatu Regency, North Sumatra Province. The determination of the research area was carried out purposively (deliberately) with the consideration that the area of Labuhanbatu Regency was because according to BPS data for 2021, there was a deficit in dry milled rice production and corn production in Labuhanbatu which was not proportional to the population growth. The population in this study were all sub-districts that existed in Labuhanbatu Regency, which totaled 9 sub-districts the method used in sampling was a census, and the selection of samples was taken from 9 sub-districts in Labuhan Batu District. Data analysis in this study used Multiple Regression Analysis (multiple regression) through the Cobb-Dougla function, while the results of this study were that in the study the variable area of land had an effect on rice production because t count > t table (6,184 > 2,010) and a significant level 0.000 < 0.05. In the research, the agricultural sector variable has an effect on rice production because of t-count > t table (3,398 > 2,010) and a significant level of 0.002 <0.05. In the research, the variable fertilizer has an effect on rice production because t-count > t table (5.075 <2.010) and a significant level of 0.000 <0.05. In this study, the seed variable has an effect on rice production because of t-count > t-table (4,341 < 2,010) and a significant level of 0.000 < 0.05. The form of a linear regression model of the Cobb-Douglas production function for the study of factors influencing rice production. Shows the results of (bx1+bx2+bx3+bx4) = 4,761 meaning that in this study the area of land, the contribution of the agricultural sector, the use of fertilizers, and the use of seeds can be projected to see the amount of rice production in harbor stone of 47.61%.

Analisis Regresi Faktor-Faktor Yang Mempengaruhi Hasil Produksi Padi Di Indonesia Bagian Barat

This study aims to measure the influence of factors affecting rice production in the western part of Indonesia. Data analysis used multiple linear regression analysis, using the independent variable X1 = land area (Ha), X2 = rainfall (mm) and X3 = rainy days (days) on the dependent variable, namely the amount of rice production (Y). In this study, it was analyzed how much influence the land area (Ha), rainfall (mm), rainy days (days) had on the amount of rice production (tons). Data analysis using the help of RStudio software. The regression model obtained is Y=61.6+0.000007917X_1-0.1541X_2+0.0002555X_3 with a value of R2=0.9268.

Community Empowerment through Utilization of Rice Husk Waste in Cirebon Regency

The amount of rice production in Indonesia every year is always increasing. The results of the rice mill produce waste material, namely husks. Along with the increase in rice production, the amount of rice husk waste has also increased. The purpose of this service is to assist the community in utilizing husk waste to make a useful product. The approach used in implementing the KKN program for the people of Jagapura Kulon Village, Gegesik District, Cirebon Regency, is a Participatory Rural Appraisal (PRA) with five stages of design thinking. The dedication results show that the shoe rack and sandals that will be made use eco-friendly materials that use the waste from rice husks. The culture of reuse, reduce and recycle must also be applied to organic waste to reduce the use of new materials or materials. The manufacture of shoe and sandal racks is also expected to reduce the felling of trees used to make conventional shoe racks made of wood. Through RASENDAL products, we can reduce the use of new materials using unused waste.

The Impact of Climate Change, Economic Growth, and Population Growth on Food Security in Central Java Indonesia

As climate change continues to cause more frequent weather shocks such as droughts and floods and increasingly erratic rainfall, people in developing regions are threatened by crop failures and hunger. In this study, the researchers describe how climate change influences food security in Central Java, seen from the frequency of floods, rainfall, and rainy days. This study also added another variable, i.e., economic growth, reviewed through GRDP and the amount of rice production. Using the Common effect model, the study results revealed that rainy days and population were the variables significantly influencing food security in cities/regencies in Central Java Province. Meanwhile, two other variables, i.e., rainfall and GRDP, had no significant effect on food security in cities/regencies in Central Java Province.

Rice Plant Health Spatial Study with Sentinel and SPOT Imagery in Parakansalak District

The Rice plant is a food plant cultivated through lowland, one of the world community’s basic needs and source of livelihood for most Indonesian people. However, the amount of rice production in Indonesia is still relatively low compared to the consumption rate of the people, so it needs to get more attention in supporting the realization of food self-sufficiency. One of the efforts to achieve this is made by monitoring, such as health conditions. The purpose of this research is to identify the health condition of rice plants in Parakansalak District, Sukabumi Regency, West Java, by applying high-resolution satellite imagery, Sentinel-2 and SPOT-6 processed with NDVI (Normalized Difference Vegetation Index) algorithm to the monitoring plants health. The result concluded that rice plants have good health with an area of 197 hectares or 52 % of the existing paddy field area by Sentinel-2, and the distribution of NDVI values in higher resolution images SPOT-6 has a similar spatial pattern. This percentage shows that the distribution of NDVI values is relatively high and indicates that the plants have a high density.

Teknologi Kecerdasan Buatan dalam Sistem Identifikasi Benih: A Review

Revolution made various advances in various fields, including agriculture. Agricultural technology is very influential in supporting the increase in agricultural production. Inspection of rice seeds is an important process in plant nurseries because it will have an impact on the amount of rice production. The majority of inspection processes are currently carried out conventionally, namely by expert inspectors who manually screen rice seed samples to identify species and quality of rice seeds. The conventional rice seed inspection process has several obstacles, namely the role of humans in carrying out inspections is still very large and it requires quite a lot of time in determining the results of rice seed inspections. The use of technology is expected to increase productivity in agricultural production, speed, and accuracy in the rice seed inspection process. Intelligence Technology. Artificial provides an alternative to the inspection process automatically, accurately and quickly. We present a design study of technology related to seed identification systems using Machine Learning and Machine Vision methods to classify the quality of rice seed varieties. This technology is designed to identify superior and non-superior seeds based on digital image data training. So that the inspection process is helped because the machine can help identify the characteristics of superior seeds and are not based on digital image data processing.

Analysis of Rice Production Forecast in Maros District Using the Box-Jenkins Method with the ARIMA Model

The Box-Jenkins method is a statistical method used for forecasting time series data. This method uses data in the past as the dependent variable. The data used in this study is data on the amount of rice production in Maros Regency which was taken from 2001 to 2018 which was taken from the Central Statistics Agency of Maros Regency and the Department of Food Security, Food Crops, and Horticulture of South Sulawesi Province. The results obtained show that the ARIMA(0,2,1) model is a suitable model to predict the amount of rice production in Maros Regency. Forecasting results show that the amount of rice production in Maros Regency has increased every year with an average increase of 3807.1 tons.

HUBUNGAN VARIABEL PENDAPATAN PETANI ALIH GUNA LAHAN SAWAH KE KARET (Studi Kasus di Desa Nusaraya Kecamatan Belitang III) KABUPATEN OKU TIMUR

<p><em>Analysis of the Correlation between Factors Influencing Farmers' Income to Change the Function of Rice Fields to Rubber in Nusaraya Village, Belitang III District, OKU Timur Regency. The purpose of this study is (1) to identify the process of land conversion to rubber plants. (2) Calculate how much farmers' income after the conversion of rice fields to rubber plants. (3) Analyzing the level of closeness of the income relationship of farmers after transferring the function of paddy fields to rubber trees on factors that affect income. The method used in this research is the case study method, with data analysis using the Spearman Rank Correlation. Based on the results of research that has been done, the following conclusions can be drawn: (1) Identification of the process of changing the function of paddy fields to rubber plants in Nusaraya Village, Belitang III District, Ogan Komering Ulu Timur Regency is determined by the rubber price factor which is higher than the price of rice . (2) The average income of farmers who convert rice fields to rubber is higher because of the two commodities being cultivated, namely rice and rubber. (3) Factors that are highly correlated in influencing the income of the conversion of paddy fields to rubber plants, namely factors of income and amount of rubber production, income and area of rubber land, income and expenditure of farmers, amount of rice production and area of paddy land, amount of rubber production and rubber land area, the amount of rubber production and farmer expenditure, rubber land area and farmer expenditure, while the age of farmers and farmer education are very small correlated with farmers' income to change the function of rice fields to rubber plant.</em></p>

PERAMALAN PRODUKSI PADI DI KABUPATEN BADUNG, GIANYAR, DAN TABANAN DENGAN METODE VECTOR AUTOREGRESSION (VAR)

Rice is one of the staple foodstuffs whose availability is very important for public consumption in Indonesia, especially Bali Province. The three regencies that produce the most rice in Bali they are Badung, Gianyar and Tabanan. This study aims to model, predict, and analyze the relationship between rice production in Badung, Gianyar, and Tabanan Regency from January 2018 to December 2019 using vector autoregression (VAR) method. VAR method is a time series method that can be used to model and predict time series with more than one variable simultaneously. The results of this study, namely the VAR model obtained to predict the amount of rice production in Badung, Gianyar, and Tabanan Regencies is third order VAR (VAR (3)). Based on the forecasting criteria for the mean absolute percentage error (MAPE) in this model, a reasonable forecast is obtained for the rice production variables in Badung and Gianyar regencies, and good forecasting for the rice production variables in Tabanan Regency is obtained. Then, based on the granger causality analysis, it is found that the amount of rice production in Gianyar Regency affects the amount of rice production in Badung and Tabanan Regencies, and the amount of rice production in Badung Regency affects the amount of rice production in Gianyar Regency.

UPAYA MEMPERBAIKI EKONOMI BERAS DI PROVINSI NUSA TENGGARA TIMUR ANALISIS DATA SEKUNDER TAHUN 2003-2017)

The aim of this research were to review the state of rice industry over the past 15 years (2003-2017) based on the demand and supply situation in East Nusa Tenggara. The development of the price of rice, the factors that influence the demand and supply, and determine the policy impact of rice demand and supply in East Nusa Tenggara Province. This research uses the econometric model, that is a simultant structural equation,which was indentified by the order condition and it was approaches using Two Stage Least Square (2SLS). The data used in this research was the time series of secondary data during 15 years period from 2003-2017 that was provided by Central Startics Office, the National Logistics Authority, the NTT Agricultural Bureau and other publications related to this investigation.
 The analysis showed that the amount of rice production was really depended on harvest area, rice consumption, rice supply and rice production in the previous year. The retail price of rice was responded to the price of corn and the demand for rice in the long term, while in the short term it only responded to the price of corn. The amount of rice consumption responded to rice production, rice prices and rice demand. Rice imports reacted to rice production, rice prices, corn prices and rice consumption in the long run. 
 Based on the results of the research, it was suggested that the area of irrigation needs to be extended,in each region of East Nusa tenggara Province, particularly technical irrigation in order to increase the rice production, and it es neededto do diversification programs in order to reduce dependency rice. The weakness of this research was it used the inpure simultan model.

The Analysis of Fuzzy Logic Method and Multiple Linear Regression in Determining National Rice Production to Improve Food Self-Sufficiency in Indonesia

Indonesia in 2023 targets rice self-sufficiency. To be included in the category of rice self-sufficiency, Indonesia’s total rice production should be 82 million tons in accordance with Government Regulation No.2 of 2015. The amount of rice production is uncertain. One way to calculate uncertainty in forecasting is by using the Fuzzy Logic of the Mamdani method and the Linear Regression of the Least Squares method. In the Fuzzy Logic Mamdani method there are 4 steps namely; 1) Fuzzy set formation; 2) Application of Implication functions; 3) Composition of Rules; and 4) Defuzzification. Rice Harvested Area, Rice Production and National Rice Consumption are the input variables and National Rice Production is the output variable. The data used are secondary data from the Central Statistics Agency (BPS) and the Ministry of Agriculture Annual Report 2006 - 2017. The data analysis process also uses matlab and minitab software. From the research results obtained that the Fuzzy Logic of the Mamdani method and the Linear Regression of the Smallest Square method can be used to predict the amount of national rice production. For the results of predictions of Fuzzy Logic the Mamdani method has a relatively large error compared to the Linear Regression of the Smallest Squares method. Furthermore it is also known that there is a significant relationship between harvested area and consumption. These two variables will be the determining factors for realizing rice self-sufficiency in Indonesia.

Detection of Rice Plants Diseases Using Convolutional Neural Network (CNN)

As a rice-producing plant, rice plant (Oryza sativa L.) is one of the most important crops in Indonesia. Rice production is increasing every year along with an increase in rice demand and population.The amount of rice production is affected by the condition of the rice plants. The worse the condition of rice plants, the rice production will also lower. Rice plant is very susceptible to diseases or pests that can reduce its productivity, including brown spot disease, leaf smut and bacterial leaf blight. As the development of science and technology, currently known as Artificial Intelligence. Artificial intelligence is a combination of several scientific disciplines such as mathematics, statistics, computer science, and even social science. Using artificial intelligence, the system now have the ability to interpret external data correctly to learn from the data and then use the learning to achieve certain goals through flexible adaptation. The artificial intelligence fields consists of several branches, such as machine learning and deep learning. Neural Network (NN) is one of the methods used in the deep learning.NN has many types, one of which is the Convolutional Neural Network (CNN). CNN is the best-knownmethod used for processingimages data compared to other types of NN. Therefore, in this study the identification of rice plants diseases was carriedout using CNN method. From this study,better results were obtained compared to other methods, obtaining 100% accuracy for training data and 86,67% for testing data. The model obtained by the CNN method can be used for detecting 3 different types of rice plants diseases, there are brown spots, leaf smuts, or bacterial leaf blight disease based on the physical images of rice plant leaves.

IMPACT OF IMPORT TARIFF POLICIES ON RICE DEMAND AND SUPPLY IN INDONESIA

Indonesia’s economic policies cannot be separated to its rice policies since rice is the staple food for Indonesian people. The paper aims to find out the impact of rice import tariff policies on rice demand and supply in Indonesia. The research uses time series data in 1981-2018. Data obtained are analyzed using econometric model with simultaneous equation system. Estimation results show that rice supply was positively and significantly influenced by grain rice price in farmer level, amount of rice production, and rice supply of the previous year. Meantime, domestic rice demand was negatively and significantly influenced by domestic rice price and positively and significantly influenced by domestic rice demand of the previous year. The result of policy simulation indicates that scenario of policy combination through an increase in rice import tariff and government purchase price brings a sizeable impact on the increase in domestic rice production and rice demand and supply. Therefore, Indonesia needs to conduct protection to farmers in the form of rice import tariff imposition as well as government purchase price.

Constructing County-Level Data for Agricultural Inputs and Analyzing Agricultural Productivity, 1951-1980

Constructing County-Level Data for Agricultural Inputs and Analyzing Agricultural Productivity, 1951-1980

Identification of Factors Affecting Food Productivity Improvement in Kalimantan Using Nonparametric Spatial Regression Method

Problems of Food Productivity in Kalimantan is experiencing instability. Every year, various problems and inhibiting factors that cause the independence of food production in Kalimantan are suffering a setback. The food problems in Kalimantan requires a solution, therefore this study aims to analyze the factors that influence the increase of productivity and production of food crops in Kalimantan using Spatial Statistics Analysis. The method used is Nonparametric Spatial Regression with Geographic Weighting. Sources of research data used are secondary data and primary data obtained from the Ministry of Agriculture and the Central Statistics Agency. The total area used is 56 regencies/cities in Kalimantan. The results show that there are 13 factors affect food productivity in Kalimantan. These factors are the number of agricultural business households, the number of workers in agriculture, the amount of rice production, rice field area, rice field harvest area, irrigation network area, area of each region, total area based on altitude class, area based on slope/slope class, economic growth rate, Gross Regional Domestic Product, Regional Development Index and Population Density. The best model is obtained using the geographical weighting of the Gaussian kernel function with the cross-validation value 5,65. The criteria for the goodness of the model with the number of knots 3 and order m = 1 have R2 value of 97,19% and the value of AIC is 2,43.

PREDIKSI HASIL PANEN PADI KABUPATEN & KOTA DI PROPINSI NUSA TENGGARA TIMUR DENGAN FUZZY INFERENCE SYSTEM (FIS)

Rice (Oryza sativa) is a staple food source for the people of Indonesia. Most of the rice consumed is the result of national rice productivity. Often the government has difficulty in estimating the adequacy of basic food items that can be provided by domestic agriculture. Therefore a method is needed to predict rice yields accurately and precisely. The agricultural sector in East Nusa Tenggara is not a flagship of the community's economic activities. This is due to the geographical conditions of NTT which are less supportive for business activities in the agricultural sector. Even so, the prediction of agricultural products, especially rice yields, is needed to be predicted so that a forecast can be obtained in determining rice yields in 2017. Fuzzy logic method in this case Fuzzy Inference System (FIS) is widely applied for forecasting or prediction. Fuzzy logic has a slowness in predicting crop yields for the following year based on crop yields in the previous year and information taken from the fuzzy information provided. Fuzzyinformation can be made a rule or rule as a consideration in predicting yields. By using the formula of Mean Absolute Percentage Error (MAPE) or Average Absolute Error, from the Fuzzy Mamdani model The Fuzzy Inference System (FIS) with the Mamdani model that has been built can be used to estimate the amount of rice production in the City District in NTT with the truth value reaching 97.8%. To determine the amount of rice production in 2017, the data is processed by using the help of the Matlab 2012 fuzzy toolbox software using the centroid method for defuzzification.

Efisiensi Penggunaan Jumlah Bibit Terhadap Pertumbuhan dan Produksi Padi Sawah

The number of seedlings per hill of rice plants affects the level of productivity , the use of seeds per hill with the right amount of rice production. This research aims to determine the effect of the number of seeds/clump on the growth and production of rice. Research using randomized block design (RBD) consists of five treatments with four replications. The treatments tested were: A (1 seedling/hill), B (3 seedling/hill), C (5 seedling/hill), D (7 seedling/hill), and E (9 seedling/hill). The seeds used are Batang Piaman variety, 25x25 cm spacing. The experiment sites in lowland farmers Lubuk Minturun Sungai Lareh village, Koto Tangah district, Padang city, West Sumatra province on wed season 2009/2010. Fertilizer is given as 150 kg Urea, 100 kg SP36 and 75 kg KCl per hectare. Urea and KCl are given three times, with brocasting system at 7, 28, and 45 Days After Planting (DAP), while the SP36 is given at 7 DAP combined with Urea and KCl. The results showed the treatment number of seedlings provide significant effect (P<0.05) on the number of grains per panicle and grain yield. However, no significantly effect (P<0.05) on plant height, maximum number of tillers, number of productive tillers, panicle length, percentage of empty grains, and weight of 1000 grains. The use number of seedlings less than five seedling per hill produces the high number of seeds per panicle and grain yield per hectare. Based on these results it can be concluded that the number of seed on the rice crops are not more than five seedling per hill. Keywords: efficiency , number of seeds , production, lowland rice.

SEVERAL FACTORS THAT INFLUENCE HOUSEHOLD ECONOMIC DECISIONS OF RICE FARMERS IN INDONESIA

The objective of this study is to point out the factors that influence household economic decisions in the use of labor, production, and consumption. This study was undertaken in Kupang regency, East Nusa Tenggara with 114 samples of agricultural household. A specification of household economic model used a simultaneous equations system. Parameter estimation uses two-stage least squares (2SLS) method. The results showed that the act of using labor in a household for rice farming was significant influenced by agricultural wage rate, rice product price, household income, farming area, and the number of household member. While the use of wage-labor was significant influenced by wage rate, farming area, and the use of household (domestic) labor. The use of urea and SP-36 was affected by ratio of rice price to fertilizer, and farming area. Rice production was influenced by farming area, total number of labor used, and amount of fertilizer used. Rice consumption from farming was positively significant influenced by an amount of rice production produced and the number of household member. Rice consumption from purchase was negatively influenced by the number of rice production but positively influenced by the number of household member.