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

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  • Sifriyani Sifriyani
  • Suyitno Suyitno
  • Rizki. N. A.

Abstract

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.

Suggested Citation

  • Sifriyani Sifriyani & Suyitno Suyitno & Rizki. N. A., 2019. "Identification of Factors Affecting Food Productivity Improvement in Kalimantan Using Nonparametric Spatial Regression Method," Modern Applied Science, Canadian Center of Science and Education, vol. 13(11), pages 103-103, November.
    • Handle: RePEc:ibn:masjnl:v:13:y:2019:i:11:p:103
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    References listed on IDEAS

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    1. Sifriyani Sifriyani, 2019. "Simultaneous Hypothesis Testing of Multivariable Nonparametric Spline Regression in the GWR Model," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 8(4), pages 32-46, July.
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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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