BibTex Citation Data :
@article{DJOE29047, author = {Daniel Victory P and Banatul Hayati}, title = {ANALISIS PENGARUH JUMLAH WISATAWAN, JUMLAH KAMAR TERJUAL, PDRB PERKAPITA, DAN INFLASI TERHADAP REALISASI PENERIMAAN PAJAK HOTEL KOTA SEMARANG TAHUN 2010-2017}, journal = {Diponegoro Journal of Economics}, volume = {9}, number = {4}, year = {2020}, keywords = {Hotel Tax, Tourist Numbers, Numbers of Sold Rooms, GDRP per capita}, abstract = { Fiscal decentralization involves shifting some responsibilities for expenditures and/or revenues to lower levels of government. One important factor in determining revenues is tax. The most potential tax revenues for Semarang City is Hotel Tax. This research aims to analyze the influence of tourist numbers, numbers of sold rooms, GDRP per capita, and inflation towards Hotel Tax revenue realization in Semarang City. The analytical tool used is multiple linear regression analysis with OLS (Ordinary Least Square). The data used is quartely data from year 2010-2017 obtained from the Badan Pusat Statistik (BPS) of Central Java Province and Semarang City , Dinas Kebudayaan dan Pariwisata Semarang City, and Badan Pendapatan Daerah (BAPENDA) Semarang City. The analysis result showed that tourist numbers, numbers of sold rooms, and GDRP per capita has a significant positive effect on hotel tax revenue realization. Whereas inflation does significant negative influence the hotel tax revenue realization }, issn = {2337-3814}, doi = {10.14710/djoe.29047}, url = {https://ejournal3.undip.ac.id/index.php/jme/article/view/29047} }
Refworks Citation Data :
Fiscal decentralization involves shifting some responsibilities for expenditures and/or revenues to lower levels of government. One important factor in determining revenues is tax. The most potential tax revenues for Semarang City is Hotel Tax.
This research aims to analyze the influence of tourist numbers, numbers of sold rooms, GDRP per capita, and inflation towards Hotel Tax revenue realization in Semarang City. The analytical tool used is multiple linear regression analysis with OLS (Ordinary Least Square). The data used is quartely data from year 2010-2017 obtained from the Badan Pusat Statistik (BPS) of Central Java Province and Semarang City, Dinas Kebudayaan dan Pariwisata Semarang City, and Badan Pendapatan Daerah (BAPENDA) Semarang City.
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