Countries population determination to test rice crisis indicator at national level using <i>k</i>-means cluster analysis

Hidayat, Yuyun; Purwandari, Titi; Ariska, Yuliana

doi:10.1088/1757-899x/166/1/012023

Cited by 1 publication

(2 citation statements)

References 4 publications

(10 reference statements)

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“…The procedure used to establish the right, valid, and reliable model is the main problem in modeling [21]. The mathematical model is a reliable and efficient tool [35].…”

Section: Research Objectivementioning

confidence: 99%

“…Based on previous research [35], it was found that 43 countries have similarities with Indonesia based on the democratic atmosphere, rice consumption, and rice purchasing power. Eleven of these countries implemented recovery policies in response to a rice crisis, meaning that crisis recovery cost (CRC) or riot recovery cost were budgeted, while the remaining 32 countries implemented policies of prevention, or a crisis anticipation cost (CAC), in response to the threat of rice crises, as reflected in the budget for anticipation costs.…”

Section: Data Collectionmentioning

confidence: 99%

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Objective Method for Determining the Importance of Unprecedented Restlessness as a Rice Crisis Indicator at the National Level

et al. 2021

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In this study, we use restlessness as an input for a rice crisis indicator, since restlessness rather than rice price provides a comparable year-to year context. We outline the significant increase in the use of unprecedented restlessness (UR) as an indicator for rice crises. The UR approach involves a precedence analysis, in contrast with the existing approach, the price shock analysis. We test UR as a new indicator for rice crises at the national level, which can be applied in Asia and other countries around the world where rice is the staple food. Strong indicators point out the effectiveness of strategic government programs and are able to assess solutions and detect rice crises, while weak indicators are only reliable in detecting whether or not there has been a crisis. UR is tested across 43 countries using two new statistics: success probability (SP) and constraint probability (CP). As a consequence of SP and CP calculations, a large number of IMR control charts for UR analysis are constructed to provide evidence that UR is a strong indicator. The optimum validity measurement result is achieved with SP = 8/26 = 0.31 and CP = 8/14 = 0.57. This means that the UR detects and is followed by only 31% of riot events. Since the value of SP is less than 0.6, we can conclude that the UR indicator is not considered valid as an indicator of rice crises at the national level. The values of CP and SP are determined subjectively as equal to 0.6. This is the main cause of the emergence of new problems in the calibration of UR as an indicator of rice crises. The subjective success criteria trigger a question regarding why the value is 0.6, for which there is no scientific justification. Based on this background, we continue to objectively establish success criteria for UR validity. After conducting a risk analysis involving a crisis recovery cost (CRC) to crisis anticipation cost (CAC) ratio, it is found that the probability of the CRC-to-CAC ratio having values greater than 7 is 0.76, which means the CRC-to-CAC ratio tends to be higher than 7. Objectively, it is concluded that UR, which has been defined as rice crisis indicator at the national level, is an important indicator.

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“…The procedure used to establish the right, valid, and reliable model is the main problem in modeling [21]. The mathematical model is a reliable and efficient tool [35].…”

Section: Research Objectivementioning

confidence: 99%

Section: Data Collectionmentioning

confidence: 99%