ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI PENDAPATAN PEDAGANG MUSLIM: Studi Pada Pedagang Sayuran di Pasar Jagasatru Cirebon

Anton Sudrajat

Abstract


Bagi sebagian muslim, berdagang merupakan salah satu alternative untuk bekerja di sector informal yang dapat menampung banyak tenaga kerja, tujuan berdagang tentu untuk menghasilkan keuntungan dan untuk menambah pendapatan demi untuk meningkatkan kualitas kehidupan keluarga. Tulisan ini bertujuan untuk menganalisis factor- faktor yang mempengaruhi pendapatan pedagang sayuran di pasar jagasatru Cirebon, seperti variable modal, jam dangang dan pengalaman dagang , system dagang dan kejujuran. Dengan menggunakan metode cross sectional terhadap 60 responden yang dipilih dengan teknik random sampling , dan menggunakan regresi linier berganda dengan metode OLS, hasil penelitian menunjukkan bahwa koefisien determinasi sebesar 73%, sedangkan uji F menunjukkan bahwa seluruh variable ber pengaruh signifikan terhadap pendapatan pedagang , sedangkan uji T menunjukkan bahwa variable modal, jam dagang dan pengalaman dagang ber pengaruh positif terhadap pendapatan pedagang adapun variable system penjualan dan kejujuran tidak menunjukkan pengaruh signifikan terhadap pendapan pedagang.

Kata kunci: Pedagang Islam, Pendapatan, Kapital, Pengalaman, kejujuran

THE ANALYSIS OF FACTORS AFFECTING THE INCOME OF MUSLIM TRADERS (Studies in Vegetables Traders In Jagasatru Market Cirebon). For some Muslims, business trade is an alternative employment in the informal sector that generates income for families and absorbs labors. The Pur pose of trading for Muslim traders is making profit and trying to increase their income to improve the quality of family life. The pur pose of this study is analyzing the factors affecting the income of Muslim traders who sell vegetables at the Jagasatru market, Cirebon, such as capital, trading hours, trading experience, sale system, and honesty of the merchant. This study uses cross sectional method. There are 60 respondents chosen by simple random sampling technique. This article applies multiple linear regressions by the method of OLS (Ordinary Least Square). Coefficient of determination R2 indicates that all independent variables in this study may explain the variation in income by 73% Muslim traders. F test indicates all independent variables have a significant effect on the level of income a significant Muslim traders ? = 10%. Based on t test results, it is known that the variable capital, trading hours and trading experience have positive effects on the income of Muslim traders with 90% confidence level. Because it is a major factor in high fluctuating vegetables business affected by harvesting season. On the other hand, the variables of sale systems and the honesty of merchants do not have significant effect on the income of Muslim traders.

Keywords: Muslim traders, Income, Capital, Experience, Honesty.


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DOI: http://dx.doi.org/10.21043/addin.v8i1.591

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