The Analysis of Quality of Paddy Harvest Yield to Support Food Security: A System Thinking Approach (Case Study: East Java)

Abstract Rice (Oryza Sativa) is a staple food for the people in Indonesia. East Java Province is a province with potential agricultural in Indonesia. East Java has advantages in agriculture and has a role in the national food sector. Population in Indonesia is projected to reach 271.1 million by 2020. East Java’s population growth rate from 2010 to 2017 was 0.64% with consumption of 213,783 tons of rice in 2018. Raw materials such as paddy, are perishable materials that require fast and precise handling. When handling is not right it will cause a loss of the results of high quality and quantity, this can be harmful to farmers because it will affect their income. This study uses a system dynamic to build the conceptual model (Causal Loop Diagram) to improving the quality of paddy yields to support food security. The results of study are a model that has some useful information regarding factors that affect the quality paddy. This can be used as decision support by the government for decision making about policies that will be applied to improve the quality of paddy harvest yields for support food security. Further research can be carried out by simulating several scenarios to predict the state of the rice farming system in the future.

[1]  S. Haefele,et al.  On-farm assessment of site-specific nutrient management for rainfed lowland rice in the Philippines , 2017 .

[2]  B. K. Bala,et al.  Modelling of food security in Malaysia , 2014, Simul. Model. Pract. Theory.

[3]  E. Suryani,et al.  System Dynamics Model to Support Rice Production and Distribution for Food Security , 2014 .

[4]  S. Applanaidu,et al.  An Econometric Analysis of Food Security and Related Macroeconomic Variables in Malaysia: A Vector Autoregressive Approach (VAR) , 2014 .

[5]  Stephen Darby,et al.  Evaluating sustainable adaptation strategies for vulnerable mega-deltas using system dynamics modelling: Rice agriculture in the Mekong Delta's An Giang Province, Vietnam. , 2016, The Science of the total environment.

[6]  K. Cassman,et al.  Assessment of rice self-sufficiency in 2025 in eight African countries , 2015 .

[7]  G. Singleton,et al.  On-farm assessment of different rice crop management practices in the Mekong Delta, Vietnam, using sustainability performance indicators , 2018, Field Crops Research.

[8]  D. R. Panuju,et al.  The dynamics of rice production in Indonesia 1961–2009 , 2013 .

[9]  Agus Supriatna Soemantri.  STRATEGI PENINGKATAN PRODUKSI BERAS MELALUI PENEKANAN SUSUT PANEN DAN PASCAPANEN DENGAN PENDEKATAN SISTEM MODELING: STUDI KASUS KABUPATEN INDRAMAYU, JAWA BARAT , 2017 .

[10]  Akhmad Mahbubi,et al.  MODEL DINAMIS SUPPLY CHAIN BERAS BERKELANJUTAN DALAM UPAYA KETAHANAN PANGAN NASIONAL , 2013 .

[11]  R. Yusuff,et al.  A decision support system for evaluating effects of Feed-in Tariff mechanism: Dynamic modeling of Malaysia’s electricity generation mix , 2015 .

[12]  D. Glover,et al.  On-farm impact of the System of Rice Intensification (SRI): Evidence and knowledge gaps , 2015 .

[13]  Hye-jung Kang,et al.  An Analysis on the Factors Affecting Rice Production Efficiency in Myanmar , 2015 .

[14]  D. Debnath,et al.  The impact of India’s food security policy on domestic and international rice market , 2017 .

[15]  Kazuki Saito,et al.  Variability and determinants of yields in rice production systems of West Africa , 2017 .

[16]  Fatimah Mohamed Arshad,et al.  Modelling boom and bust of cocoa production systems in Malaysia , 2015 .

[17]  Isaac K. Tetteh,et al.  Differential impacts of rainfall and irrigation on agricultural production in Nigeria: Any lessons for climate-smart agriculture? , 2016 .

[18]  William H. Meyers,et al.  Price stabilization and impacts of trade liberalization in the Southeast Asian rice market , 2015 .

[19]  L. Smutka,et al.  Cooperative rice farming within rural Bangladesh , 2018, Journal of Co-operative Organization and Management.