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All Journal Integral : Jurnal Penelitian Pendidikan Matematika Narra X
Fahmi, Iqbal
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Biochemistry, Genetics & Molecular Biology Chemistry Education Immunology & microbiology Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Physics Public Health

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Willingness-to-pay for urban green space: A meta-analysis of surveys across China Wikurendra, Edza A.; Aulia, Aulia; Fauzi, Muhammad L.; Fahmi, Iqbal; Amri, Ikhwan
Narra X Vol. 1 No. 3 (2023): December 2023
Publisher : Narra Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52225/narrax.v1i3.105

Abstract

Sustainable ecosystem services are increasingly recognized amid rapid regional transformation. While the rate of urbanization in China continues to rise, there is an urgent need to evaluate public preferences and their associated economic values concerning urban green space (UGS). The aim of this study was to calculate the overall willingness-to-pay (WTP) for UGS across China. Literature search was performed systematically on Scopus, Scilit, PubMed, and Google Scholar databases on 11 November 2023. Studies reporting the WTP in China were included in the analysis. Quality of the included studies were appraised by using Q-SSP tool consisting of 20-item quality of survey studies in psychology. To calculate the overall willing to pay rate and WTP, a meta-analysis was performed using restricted maximum-likelihood model on raw proportions. A total of nine studies were included comprised of 9381 valid responses with high quality according to Q-SSP (score: 70–90%). Findings from the meta-analysis indicated that the rate of willing to pay for UGS was 70.8% (95%CI: 60%, 82%; p-Het<0.001, I2= 99.37%). The rate was not affected by sample size, age, gender, and education (p>0.05). Among mainland Chinese population alone, the average minimum WTP was 2.97 USD/month, and increased to 3.36 USD/month if combined with Hong Kong population. A majority of over 70% Chinese population were willing to pay for UGS. Nevertheless, high heterogeneity in the pooled estimates suggest the importance of addressing contextual variables and presence of regional disparities.
Optimization Of Support Vector Machine (Svm) Based Forward Selection For Prediction Of Incoming Students Continue To Private College Fahmi, IQBAL
Integral (Jurnal Penelitian Pendidikan Matematika) Vol. 6 No. 1 (2023): November 2023
Publisher : Program Studi Pendidikan Matematika, Universitas Pancasakti Tegal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24905/jppm.v6i1.121

Abstract

Abstract. The large volume of society can cause problems if it is not commensurate with improving the quality of human resources. A factor that can support human resource capacity is improving the quality of education. High school student data has quite diverse data. With a case study at a high school in Brebes Regency, this experiment is used as a basis for predicting the distribution of high school graduates in the following year. The data mining process is assisted by the WEKA application. The classification used is a support vector machine classification based on forward selection to determine the attributes that are most influential in prediction. The highest results from the SVM experiment were obtained by kernel anova with an accuracy value of 96.17%. Then the FS-SVM algorithm with anova kernel parameter C of 0.5 with an accuracy level of 99.71%. Keywords: High School, Course, Data, Classification
Willingness-to-pay for urban green space: A meta-analysis of surveys across China Wikurendra, Edza A.; Aulia, Aulia; Fauzi, Muhammad L.; Fahmi, Iqbal; Amri, Ikhwan
Narra X Vol. 1 No. 3 (2023): December 2023
Publisher : Narra Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52225/narrax.v1i3.105

Abstract

Sustainable ecosystem services are increasingly recognized amid rapid regional transformation. While the rate of urbanization in China continues to rise, there is an urgent need to evaluate public preferences and their associated economic values concerning urban green space (UGS). The aim of this study was to calculate the overall willingness-to-pay (WTP) for UGS across China. Literature search was performed systematically on Scopus, Scilit, PubMed, and Google Scholar databases on 11 November 2023. Studies reporting the WTP in China were included in the analysis. Quality of the included studies were appraised by using Q-SSP tool consisting of 20-item quality of survey studies in psychology. To calculate the overall willing to pay rate and WTP, a meta-analysis was performed using restricted maximum-likelihood model on raw proportions. A total of nine studies were included comprised of 9381 valid responses with high quality according to Q-SSP (score: 70–90%). Findings from the meta-analysis indicated that the rate of willing to pay for UGS was 70.8% (95%CI: 60%, 82%; p-Het<0.001, I2= 99.37%). The rate was not affected by sample size, age, gender, and education (p>0.05). Among mainland Chinese population alone, the average minimum WTP was 2.97 USD/month, and increased to 3.36 USD/month if combined with Hong Kong population. A majority of over 70% Chinese population were willing to pay for UGS. Nevertheless, high heterogeneity in the pooled estimates suggest the importance of addressing contextual variables and presence of regional disparities.
Co-Authors Amri, Ikhwan Aulia Aulia Fauzi, Muhammad L. Wikurendra, Edza A.