GPH-International Journal of Agriculture and Research

DECISION-MAKING OF FARM HOUSEHOLDS IN PREVENTING STUNTING IN LEMPAKE VILLAGE, NORTH SAMARINDA DISTRICT, SAMARINDA CITY

2024-06-08T07:21:40+00:00

Stunting was a serious public health problem, especially in rural areas in Indonesia. Decision-making was the process of selecting an alternative course of action to achieve a predetermined goal or goal. Household decision-making had a significant impact on stunting prevention, especially in terms of food supply, health, and sanitation. The purpose of the study was to find out how decision-making was carried out and who was the most dominant in decision-making in farming households in the prevention of stunting in Kelurahan Lempake, Kecamatan Samarinda Utara. The study was conducted in Lempake Village, North Samarinda District, from November 2023 to February 2024, with data collected in the form of primary data through questionnaires and secondary data (library studies and related agencies). The sample was taken using random sampling purposive and the sample used was a group of prosperous farm women and a group of 34 respondents of night-time farmers. The methods of data analysis used were qualitative descriptive analysis and tabulation. The results of the study showed that the decision-making process began with the identification of stunting problems and the collection of information on stunting prevention. The husband and wife then jointly chose an alternative action, evaluated the alternative, and finally made a joint decision. This reflected a high awareness of the importance of having accurate information and adequate knowledge in quality decision-making. The decision-making of farming households in the prevention of stunting in Lempake Village showed that the wife's role in food-related decision-making was very dominant in farming households. However, the role of the husband was also involved, even to a lesser extent.

IMPLEMENTATION OF THE AGRARIAN REFORM OBJECT LAND PROGRAM IN FOREST AREA IN 2023 CASE STUDY IN JEMBAYAN VILLAGE, LOA KULU SUBDISTRICT

2024-06-09T07:41:18+00:00

The research aims to determine the implementation of the Agrarian Reform Object Land Program and the role and support of stakeholders in the Implementation of the Agrarian Reform Object Land (TORA) Program in Jembayan Village, Loa Kulu sub-District, Kutai Kartanegara Regency, East Kalimantan Province, Indonesia. The research was carried out from September to November 2022 in Jembayan Village, Loa Kulu sub-District, Kutai Kartanegara Regency, East Kalimantan Province, Indonesia as the center for implementing administrative and technical activities of the TORA Program for East Kalimantan Province. The community population at the research location was 134 people and using the Slovin method a sample of 21 people was taken as respondents. The data collected consists of primary data obtained from observations and interviews with respondents and resource persons, and secondary data obtained from documentation in the form of archives and documents relevant to the research. This research uses qualitative research methods, the data analysis process is carried out through several stages, namely: data collection, data reduction, data presentation and analysis, and conclusion. The research results show that (1) TORA implementation is already underway, starting from the Inventory and Verification of Settlement of Land Tenure in Forest Areas (PPTKH) activities and Definitive Boundary Arrangement Activities, but to date, the final stage of distributing certificates from ATR/BPN has not been realized. The forest area allocation for providing TORA resources implemented by PPTKH is 30.05 hektare and is a function of the Permanent Production (HP) forest area. The implementation route for Definitive Boundary Arrangement activities in part of the Jembayan Village Permanent Production Forest Area was realized as long as 5,084.19 meters; and (2) the TORA program in Jembayan Village in terms of the benefits and support provided by stakeholders and the community is in the good category, namely 43.75% and 66.67%.

THE EFFECT OF Mg(CO3)2 COMPOUND FERTILIZER AND N,P,K FERTILIZER ON THE Mg-EC, PLANT Mg-UPTAKE, AND YIELD OF TOMATO (Solanum lycopersicum L.) ON INCEPTISOLS OF JATINANGOR

2024-06-26T06:17:08+00:00

Inceptisols is a soil order that has an area of about 70.5 million hectares in Indonesia. The commodity that can be cultivated on Inceptisols is tomatoes. The nutrient content of Inceptisols is classified as low, resulting in decreasing in tomato yield. One of the efforts that can be made to increase the yield of tomatoes is by applying Mg(NO₃)₂ compound fertilizer. The experiment was conducted to determine the effect of Mg(NO₃)₂ compound fertilizer on soil exchangeable Mg (Mg-EC), plant Mg-Uptake, and yield of tomato. The experiment was conducted at the Experimental Field of the Laboratory of Soil Chemistry and Plant Nutrition, Faculty of Agriculture, Universitas Padjadjaran, Jatinanor, from October to December 2023. The experimental design used was a Completely Randomized Block Design (RCBD) with six treatments: one treatment without fertilizer, one treatment of the recommended dose of N, P, K fertilizer, four treatments of various doses of Mg(NO₃)₂ compound fertilizer combined with N, P, K fertilizer with four replications each. The results of the experiment showed that Mg(NO₃)₂ compound fertilizer had the effect of increasing soil exchangeable Mg (Mg-EC), plant Mg-Uptake, and yield of tomato. The treatment of 1 dose of Mg(NO₃)₂ compound fertilizer and dose of N, P, K fertilizer showed the best results on soil Mg-EC(3,82 plant Mg-Uptake content (1.23%), number of fruits (268 fruits), fruit diameter (38.15 cm, weight per fruit (36.75 g), and fruit weight per plot (6.13 kg) on Inceptisols Jatinangor.

Forecasting the Contribution Agricultural Sector on the Gross Domestic Product, Sudan

2024-06-26T15:50:01+00:00

The objective of this study was to forecast the contribution of the Sudanese agricultural sector on the country GDP for the period (2023- 2038). Auto-Regressive Integrated Moving Average (ARIMA) Model with statistical time series modeling technique was used in the analysis. The research depended mainly on secondary data which was collected from different relevant sources. Results showed that ARIMA (1,0,0) was the best model because there is a noticeable agreement between the observed and expected forecasted values and the Mean Absolute Percentage Error (MAPE) was found to be 18.8. Result also revealed that, the forecasted value for the year 203.