AGRICULTURAL STATISTICS: USING MULTIPLE MODES OF FOOD CROPS DATA COLLECTION IN INDONESIA DURING THE COVID-19 PANDEMIC

Ratna Rizki Amalia

Abstract


Government policy to limit the spread of COVID-19, such as lockdowns and social distancing, poses critical challenges to food crops data collection. The spread of COVID-19 has led to new challenges in collecting food crops data, which were previously collected using a conventional method, namely through measurements and direct interviews with respondents. To address this challenge, BPS-Statistics Indonesia finds alternatives to surveying by implemented multiple data collection modes, namely direct observation and measurement, physically distanced face-to-face interviews, and phone interviews. One of the most challenging aspects of implementing this combined method is the implementation of field activities. This issue arises due to an insufficient database of agricultural households' phone numbers and a questionnaire format that is complex enough to be used in this new method. This paper provides a comprehensive look at the technicalities that are implemented regarding this breakthrough. This paper's discussion focuses on the business process of data collection and strategic ways to overcome the challenges faced in implementing the method.


Keywords


Statistical Theory

Full Text:

PDF

References


BPS-Statistics Indonesia. (2018). Laporan Perekonomian Indonesia 2020 [Indonesian Economic Report, 2020]. Jakarta: BPS-Statistics Indonesia.

Kadir, K. & Amalia, R.R. (2016). Economic Growth and Poverty Reduction: The Role of the Agricultural Sector in Rural Indonesia. Proceeding on ICAS VII Seventh International Conference on Agricultural Statistics. DOI: 10.1481/icasVII.2016.03

Bresciani, F. & Vald├ęs, A. (2007). Beyond Food Production: The Role of Agriculture in Poverty Reduction. Rome: FAO Rome.

FAO. (1999). Guidelines for the Routine Collection of Capture Fishery Data. FAO fisheries technical paper 382.

ILO. (2020). COVID-19: Guidance for Labour Statistics Data Collection. Retrieved September 11,2020 from: https://www.ilo.org/wcmsp5/groups/public/---dgreports/---stat/documents/publication/wcms_741145.pdf

Welsch, W. (2020, May 5). The New Normal: Collecting Data Amidst A Global Pandemic. Retrieved September 14, 2020, from https://www.jips.org/uploads/2020/05/JIPS-TheNewNormal-CollectingDataAmidstPandemic-May2020-min.pdf

World Bank. (2020). High Frequency Mobile Phone Surveys of Households to Assess the Impacts of COVID-19: Overview (English). Washington, D.C.: World Bank Group. http://documents.worldbank.org/curated/en/703571588695361920/Overview

FAO. (2020). Risk analysis and guidance for the management and conduct of evaluations during international and national level COVID-19 crisis and restriction. OED Guidelines Series 05/2020. FAO Rome.

Kadir. (2019). Memperbaiki Data Pangan Indonesia lewat Metode Kerangka Sampel Area [Improving Indonesian Food Data through the Area Sampling Frame Method]. Jakarta: Center for Indonesian Policy Studies.

Kementrian Pertanian & Badan Pusat Statistik. (2015). Pedoman Pengumpulan Data Statistik Pertanian Tanaman Pangan [Guidelines for Collecting Data on Agricultural Statistics for Food Crops]. Jakarta: Badan Pusat Statistik.

Chen, H., Hailey, D., Wang, N., Ning & Yu, P. (2014). A Review of Data Quality Assessment Methods for Public Health Information Systems. International Journal of Environmental Research and Public Health. Int. J. Environ. Res. Public Health 2014, 11, 5170-5207; DOI: 10.3390/ijerph110505170

FAO. (2014). The FAO Statistics Quality Assurance Framework. FAO Rome. http://www.fao.org/3/i3664e/i3664e.pdf




DOI: https://doi.org/10.24252/msa.v8i2.16106

Refbacks

  • There are currently no refbacks.




Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Crossref Cited-by logo