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ANALISIS REGRESI LINIER BERGANDA PADA DATA SURVEY UNTUK PEMODELAN TOTAL PENGELUARAN DI JAWA TENGAH, INDONESIA

*Alan Prahutama  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Rita Rahmawati  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Open Access Copyright 2024 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract
Survey data is collected using a sampling design to capture Population phenomena. One of the sampling techniques used is complex design. Complex design is a sampling technique other than Simple Random Sampling (SRS). Sampling weight is used for the estimate from the complex design to result in unbiased estimation. Regression analysis using survey data needs to consider complex design. This study models total expenditure in Central Java province using March 2021 Susenas data, with a sample of 29,870 households, 3,005 primary sampling units, and 65 strata. The best model produced from this study is 25.51%. Based on the regression model, the characteristics of households with higher expenditure on categorical independent variables include households living in urban areas, heads of households that are male, married, graduates/postgraduates working in the service sector, and households not receiving Government assistance. Meanwhile, the positive coefficient of continuous variables include the age of the head of the household, hours worked during one week, and the number of households living in one house
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Keywords: Complex survey design data; regression analysis; total expenditure

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  1. BPS. (2021). Buku Pedoman 1: Survey Sosial Ekonomi Marret 2021. BPS
  2. Chambers, R. ., & Skinner, C. . (2003). Analysis of Survey Data. John Wiley and Sons
  3. Draper, N. R., & Smith, H. (1998). Applied Regression Analysis. John Wiley & Sons, Inc
  4. García, T., & Grande, I. (2010). Determinants of food expenditure patterns among older consumers. The Spanish case. Appetite, 54(1), 62–70
  5. Hahs-Vaughn, D. L., McWayne, C. M., Bulotsky-Shearer, R. J., Wen, X., & Faria, A. M. (2011). Methodological considerations in using complex survey data: An applied example with the head start family and child experiences survey. Evaluation Review, 35(3), 269–303
  6. Heeringa, S. G., West, B. T., & Berglund, P. A. (2010). Applied Survey Data Analysis. Chapman & Hall Taylor and Francis
  7. Jacobson, D., Mavrikiou, P. M., & Minas, C. (2010). Household size, income and expenditure on food: The case of Cyprus. Journal of Socio-Economics, 39(2), 319–328
  8. Lohr, S. L. (2010). Sampling: Design and Analysis (2nd ed.). Brooks/Cole Cengage Learning
  9. Sekhampu, T. J. (2012). Socio-economic determinants of household food expenditure in a low income township in South Africa. Mediterranean Journal of Social Sciences, 3(3), 449–453
  10. Smith, C., Parnell, W. R., Brown, R. C., & Gray, A. R. (2013). Providing additional money to food-insecure households and its effect on food expenditure: A randomized controlled trial. Public Health Nutrition, 16(8), 1507–1515
  11. Venn, D., Dixon, J., Banwell, C., & Strazdins, L. (2018). Social determinants of household food expenditure in Australia: The role of education, income, geography and time. Public Health Nutrition, 21(5), 902–911

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