Factors Influencing Individual Income Level in Cikanyere Village Using Ordinal Logistic Regression Model
DOI:
https://doi.org/10.20956/j.v20i2.31964Keywords:
Tingkat Pendapatan, Regresi Logistik Ordinal, Tingkat Pendidikan, Usia, Jumlah TanggunganAbstract
Income is an element in the process of economic development that serves as an indicator of the standard of living for individuals, families, or the population. Cikanyere is a village located in, West Java, Cianjur, which still has low economic growth. Economic growth can be observed from the level of income obtained by the population. Based on the aforementioned issue, the original purpose of this research is to identify the factors that influence the level of individual income in Cikanyere Village. One type of regression analysis is ordinal logistic regression, which is used to test the correlation between independent variables and dependent variables that have multiple categories or polychotomous, meaning variables that have two or more categories and are in ordinal scale. Ordinal logistic regression is used because the dependent variable in this study is the income level, while the independent variables include education level, age, marital status, number of dependents, and gender. All these independent variables are measured on an ordinal scale. In this study, the influence of each component on the income level is measured partially using the Pearson Chi-Square test. The results show that age, education level, and the number of dependents to the components that affect the income level in Cikanyere Village. Gender and marital status do not affect the income level. The obtained ordinal logistic regression model provides the likelihood of individual income improvement based on changes in age, education level, and the number of dependents.Downloads
References
Sudjana, 2019. Hakikat Konsepsi Ketahanan Nasional di Bidang Ekonomi sebagai Geostrategi Indonesia melalui Pendekatan Kesejahteraan. Jurnal Pancasila Dan Kewarganegaraan, 4(2), 1–10. https://doi.org/10.24269/jpk.v4.n2.2019.pp1-10
Natalia, L., Sudhanshu, H., Petermana, A., Seidenfeldc, D., Tembod, G., On, & Team, behalf of the Z. C. T. E., 2019. Does money buy happiness? Evidence from an unconditional cash transfer in Zambia. SSM - Population Health, 4, 225–235. https://doi.org/https://doi.org/10.1016/j.ssmph.2018.02.002
Putri, N. D. K., & Wulandari, D. K. A., 202. Determinant Analysis of Income Inequality in Indonesia 2015-2020. Indonesian Journal of Human Resource Management, 1(1), 1–15.
Akbariandhini, M., & Prakoso, A. F., 2020. Analisis Faktor Tingkat Pendidikan, Jenis Kelamin, Dan Status Perkawinan Terhadap Pendapatan Di Indonesia Berdasarkan IFLS-5. Jurnal Pendidikan Ekonomi, Manajemen Dan Keuangan, 4(1 (1)), 13–22. https://doi.org/10.26740/jpeka.v4n1.p13-22
Peng, C., & She, P. W., 2020. Are women less likely to be managers in the UK labour market? Economic Modelling, 85, 317–324. https://doi.org/10.1016/j.econmod.2019.10.021
Luo, M. S., Chui, E. W. T., & Li, L. W., 2020. The Longitudinal Associations between Physical Health and Mental Health among Older Adults. Aging and Mental Health, 24(12), 1990–1998. https://doi.org/10.1080/13607863.2019.1655706
Susdarwono, E. T., 2022. Positive Predictions of International Institutions, Demographic Bonuses and Covid-19: Will Indonesia Really Enjoy the Demographic Bonus Amid the Raging Covid-19 Pandemic? Jurnal Ekonomi Dan Statistik Indonesia, 2(2), 134–141. https://doi.org/10.11594/jesi.02.02.01
Julianto, D., & Utari, A. P., 2019. Analisa Pengaruh Tingkat Pendidikan Terhadap Pendapatan Individu Di Sumatera Barat. Journal of Physics A: Mathematical and Theoretical, 44(8), 1689–1699.
Haryati, 2021. Pengaruh Jenjang Pendidikan Terhadap Pendapatan Rumah Tangga Di Desa Sebuduh Kabupaten Sanggau. Program Studi Pendidikan Ekonomi FKIP Untan Pontianak, 1, 42–48.
Budistiharah, A. U., Islamiyati, 2023. Pemodelan Regresi Logistik Ordinal dengan Dispersi Efek Lokasi. Journal of Statistics and Its Application. Vol. 4, No. 2, Juli, 2023, Hal. 144-152
Sesay, R. B., Kpangay, M., & Seppeh, S., 2021. An Ordinal Logistic Regression Model to Identify Factors Influencing Students Academic Performance at Njala University. April. https://doi.org/10.51244/IJRSI.2021.8104
Bustan, M. N., Tiro, M. A., Annas, S., & Adiatma, 2019. Analysis of Ordinal Logistic Regression Model on Breast Cancer Diagnosis by Birads Mammography. Indian Journal of Public Helalth Research & Development, 10(1), 1199–1203. https://doi.org/10.5958/0976-5506.2019.00218.3
Rifada, M., Chamidah, N., Nuraini, P., & Gunawan, F. D., 2021. Determinants of Stunting Among Under-Five Years Children Using the Ordinal Logistic Regression Model. 550(Icmmed 2020), 405–411.
Daoud, J. I., 2018. Multicollinearity and Regression Analysis. Journal of Physics: Conference Series, 949(1). https://doi.org/10.1088/1742-6596/949/1/012009
Negara, I. C., & Prabowo, A., 2018. Penggunaan Uji Chi–Square untuk Mengetahui Pengaruh Tingkat Pendidikan dan Umur terhadap Pengetahuan Penasun Mengenai HIV–AIDS di Provinsi DKI Jakarta. Prosiding Seminar Nasional Matematika Dan Terapannya 2018, 1(1), 1–8.
Guzman, F., Paswan, A., & Tripathy, N., 2019. Consumer centric antecedents to personal financial planning. Journal of Consumer Marketing, 36(6), 858–868. https://doi.org/10.1108/JCM-01-2018-2514
Rizkiawati, N. L., & Asandimitra, N., 2018. The Influence of Demography, Financial Knowledge, Financial Attitude, Locus of Control and Financial Self-Efficacy on the Financial Management Behavior of the Surabaya Community. Jurnal Ilmu Manajemen (JIM), 6(3), 93–107.
Hakim, L. N., 2020. Urgensi Revisi Undang-Undang tentang Kesejahteraan Lanjut Usia. Aspirasi: Jurnal Masalah-Masalah Sosial, 11(1), 43–55. https://doi.org/10.46807/aspirasi.v11i1.1589
Colineaux, H., Neufcourt, L., Delpierre, C., Kelly-Irving, M., & Lepage, B., 2023. Explaining biological differences between men and women by gendered mechanisms. Emerging Themes in Epidemiology, 20(1), 1–17. https://doi.org/10.1186/s12982-023-00121-6
Lamichhane, C. D., 2018. Understanding the Education Philosophy and Its Implications. NCC Journal, 3(1), 24–29. https://doi.org/10.3126/nccj.v3i1.20245
Pristiwanti, D., Badariah, B., Hidayat, S., & Dewi, R. S., 2022. Pengertian Pendidikan. Jurnal Pendidikan Dan Konseling (JPDK), 4(6), 1707–1715.
Amir, Akhmad, Romadhoni, B., & Abidin, Z., 2022. Factors Affecting Household Income of Traditional Fishermen in Galesong District, Takalar Regency, Indonesia. European Journal of Business and Management Research, 7(6), 22–25. https://doi.org/10.24018/ejbmr.2022.7.6.1597
Setyawati, D. U., Korida, B. D., & Febrilia, B. R. A., 2020. Analisis Regresi Logistik Ordinal Faktor-Faktor yang Mempengaruhi IPK Mahasiswa. Jurnal Varian, 3(2), 65–72. https://doi.org/10.30812/varian.v3i2.615
Amelia, R., Indahwati, & Erfiani., 2022. the Ordinal Logistic Regression Model With Socio-Economic Survey. 16(4), 1355–1364.
Ananda, B. D. K., Insani, Z., Febrilia, B. R. A., & Setyawati, D. U., 2020. Analisis Regresi Logistik Ordinal Mengenai Faktor-Faktor Yang Mempengaruhi Tingkat Pendikan Anak Di Desa Sayang-Sayang. Journal of Fundamental Mathematics and Applications (JFMA), 3(2), 124–132. https://doi.org/10.14710/jfma.v3i2.7811
Lelisho, M. E., Wogi, A. A., & Tareke, S. A., 2022. Ordinal Logistic Regression Analysis in Determining Factors Associated with Socioeconomic Status of Household in Tepi Town, Southwest Ethiopia. Scientific World Journal, 2022. https://doi.org/10.1155/2022/2415692
Atinafu, B. T., Tarekegn, F. N., & Kebede, W. M., 2023. Assessment of the level of social support and associated factors among cancer patients in the comprehensive cancer center at Ethiopia: Ordinal logistic regression analysis level of social support and associated factors among cancer patients. Heliyon, 9(5), e15688. https://doi.org/10.1016/j.heliyon.2023.e15688
Susanti, A., Soemitro, R. A. A., Suprayitno, H., & Ratnasari, V., 2019. Searching the Appropriate Minimum Sample Size Calculation Method for Commuter Train Passenger Travel Behavior Survey. Journal of Infrastructure & Facility Asset Management, 1(1), 47–60. https://doi.org/10.12962/jifam.v1i1.5232
Desanti, G., & Ariusni, 2022. Pengaruh Umur, Jenis Kelamin, Jam Kerja, Status Pekerjaan Dan Pendidikan Terhadap Pendapatan Tenaga Kerja Di Kota Padang. 3, 17–26.
Bhaskara, A. A. Y., Wardana, I. G., & Marhaeni, A. A. I. N., 2019. Pengaruh Pendidikan, Jenis Kelamin, Dan Status Pekerjaan Terhadap Pendapatan Pekerja Di Bali. 8(9), 1947–1976.
Ichsan, M. W., & Suharto, R. B., 2021. Pengaruh pendapatan dan jumlah tanggungan keluarga terhadap konsumsi buruh ( studi terhadap buruh angkut di pasar segiri Samarinda ) The effect of income and the number of family dependents on labor consumption ( study of transport workers in the segiri market in Samarinda ). 6(3), 7–14.
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