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All Journal Journal of Applied Science, Engineering, Technology, and Education Mattawang: Jurnal Pengabdian Masyarakat Quantitative Economics and Management Studies ARRUS Journal of Mathematics and Applied Science ARRUS Journal of Engineering and Technology VARIANSI: Journal of Statistics and Its Application on Teaching and Research Abdi Kimia : Jurnal Pengabdian Masyarakat
Rais, Zulkifli
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Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Mathematics Physics Public Health Social Sciences Other

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Journal : Quantitative Economics and Management Studies

 1 
Implementation of Binary Logistic Regression and Chi-Squared Automatic Interaction Detection (CHAID) to Recipients of the Prosper Family Card Program in Makassar City Rais, Zulkifli; Ruliana; Indrayasaro
Quantitative Economics and Management Studies Vol. 6 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems3981

Abstract

The binary logistic regression analysis method is a classification method that forms a relationship between a dichotomous dependent variable and an independent variable, while the chi-squared automatic interaction detection (CHAID) analysis method is a decision tree classification method for studying the relationship between independent variables and variables. bound by using the chi-square test statistic as the main tool. This research aims to determine the magnitude of the resulting accuracy value and what factors influence recipients of the Prosperous Family Card program in Makassar City based on National Socio-Economic Survey data in 2022 using the binary logistic regression method and the chi-squared automatic interaction detection method (CHAID). The results of this research using the binary logistic regression method show that the variables of the highest level of education of the head of the household (X4) and defecation facilities (X7) have a significant effect on recipients of the Prosperous Family Card program in Makassar City with an accuracy value of 75.78%, while the chi-squared automatic interaction detection (CHAID) method also shows that the variables of the highest level of education of the head of the household (X4) and defecation facilities (X7) have a significant effect on recipients of the Prosperous Family Card program in Makassar City with the resulting accuracy value of 75%. Based on the accuracy values of the two methods, the binary logistic regression method is the appropriate method for classifying recipients of the Prosperous Family Card program in Makassar City
Backpropagation Neural Network Method For The Classification of Districts/Cities Based On Macro Socio-Economic Indicators In The Province Of South Sulawesi Rais, Zulkifli; Sudarmin; Syahputra, Akbar
Quantitative Economics and Management Studies Vol. 6 No. 2 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems3982

Abstract

Classification is a way of grouping objects based on the characteristics possessed by the objects of classified. One of the developing classification methods is the backpropagation neural network. This study aims to look at the descriptive and classification results of the District/City Macro Socioeconomic Indicators in South Sulawesi Province. The data set comprises 24 observations with 9 variables, namely population density, poverty line, Gini ratio, open unemployment rate, life expectancy, average length of schooling, labor force participation rate, life growth rate, and GRDP at current prices. A model with a total of 9 hidden layers and a learning rate of 0.002 is obtained with an accuracy of 70%, precision of 70%, recall of 100%, and F1 score of 87%.
Co-Authors Ahmar, Ansari Saleh Aidid, Muhammad Kasim Amira, Husnul Asmar Asmar, Asmar Azrahwati Fahmuddin S, Muhammad Fahmuddin, Muh. Indrayasaro Mar’ah, Zakiyah Muhammad Refaldy Nusrang, Muhammad Purnamasari, A. Bida Rizal Bakri Ruliana Ruliana Ruliana, Ruliana Rusdianto Saida, Saida Sitti Masyitah Meliyana R. Sudarmin Sudarmin Sudarmin Suwardi Annas Syahputra, Akbar Triutomo, Agung Yuniar, Eka Citra Yusniar Rasjid, Yusniar