scholarly journals Exploring the Trend of New Zealand Housing Prices to Support Sustainable Development

2019 ◽  
Author(s):  
Linlin Zhao ◽  
Jasper Mbachu ◽  
Zhansheng Liu
Keyword(s):  
New Zealand ◽  
Regression Model ◽  
House Prices ◽  
Linear Regression Analysis ◽  
Arima Model ◽  
Housing Prices ◽  
Multiple Linear Regression Analysis ◽  
Housing Sector ◽  
Forecasting Performance ◽  
Sample Method

The New Zealand housing sector is experiencing rapid growth that boosts the national economy but also results in the loss of valuable resources. In line with the growth, the housing market for both residential and business purposes has been booming, as have house prices. To sustain the housing development, it is critical to accurately monitor and predict housing prices so as to support the decision-making process in housing sector. This study is devoted to applying a mathematical method to predict housing prices. The forecasting performance of two types of models: ARIMA and multiple linear regression analysis are compared. The ARIMA and regression models are developed based on a training-validation sample method. The results show that the ARIMA model generally performs better than the regression model. However, the regression model explores, to some extent, the significant correlations between house prices in New Zealand and the macro-economic conditions.

scholarly journals Exploring the Trend of New Zealand Housing Prices to Support Sustainable Development

2019 ◽  
Vol 11 (9) ◽  
pp. 2482
Author(s):  
Linlin Zhao ◽  
Jasper Mbachu ◽  
Zhansheng Liu
Keyword(s):  
New Zealand ◽  
Regression Model ◽  
House Prices ◽  
Moving Average ◽  
Arima Model ◽  
Housing Prices ◽  
Housing Sector ◽  
Autoregressive Integrated Moving Average ◽  
Forecasting Performance ◽  
Sample Method

The New Zealand housing sector is experiencing rapid growth that has a significant impact on society, the economy, and the environment. In line with the growth, the housing market for both residential and business purposes has been booming, as have house prices. To sustain the housing development, it is critical to accurately monitor and predict housing prices so as to support the decision-making process in the housing sector. This study is devoted to applying a mathematical method to predict housing prices. The forecasting performance of two types of models: autoregressive integrated moving average (ARIMA) and multiple linear regression (MLR) analysis are compared. The ARIMA and regression models are developed based on a training-validation sample method. The results show that the ARIMA model generally performs better than the regression model. However, the regression model explores, to some extent, the significant correlations between house prices in New Zealand and the macro-economic conditions.

scholarly journals PENGARUH RETRIBUSI DAERAH DAN PAJAK DAERAH TERHADAP PENDAPATAN ASLI DAERAH DI DINAS PENDAPATAN DAERAH

2020 ◽  
Vol 9 (4) ◽  
pp. 1338
Author(s):  
I Putu Agus Sudarmana ◽  
Gede Mertha Sudiartha
Keyword(s):  
Regression Analysis ◽  
Linear Regression Analysis ◽  
Sampling Technique ◽  
Multiple Linear Regression Analysis ◽  
Local Revenue ◽  
Local Taxes ◽  
Analysis Technique ◽  
Saturated Sample ◽  
The Government ◽  
Sample Method

The purpose of this study was to analyze the effect of regional levies and regional taxes simultaneously and partially on the value of local revenue in Badung Regency in the period 2008-2018. The sample of this research is Regional Retribution data, Local Tax and Local Revenue data in Badung Regency for the period 2008-2018. The sampling technique used is the saturated sample method, namely the method of determining the sample with the entire population used as research samples. The data analysis technique used in this study is multiple linear regression analysis. The results showed that regional levies, and regional taxes simultaneously or partially had a significant effect on the Original Local Revenues in Badung Regency. These results give the sense that, increasing revenue from taxes and levies will lead to an increase in local revenue that will be received by the government of Badung Regency. Keywords: regional levies, local taxes, PAD

scholarly journals Cluster and regression analysis for predicting salinity in groundwater

2018 ◽  
Vol 192 ◽  
pp. 02007
Author(s):  
Phiraphat Aphiphan ◽  
Uma Seeboonruang ◽  
Somyot Kaitwanidvilai
Keyword(s):  
Electrical Conductivity ◽  
Regression Analysis ◽  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Water Levels ◽  
Groundwater Salinity ◽  
Groundwater Levels

Groundwater salinity is a major problem particularly in the northeastern region of Thailand. Saline groundwater can cause widespread saline soil problem resulting in reducing agricultural productivity as in the Lower Nam Kam River Basin. In order to better manage the salinity problem, it is important to be able to predict the groundwater salinity. The objective of this research was to create a cluster-regression model for predicting the groundwater salinity. The indicator of groundwater salinity in this study was electrical conductivity because it was simple to measure in field. Ninety-eight parameters were measured including precipitation, surface water levels, groundwater levels and electrical conductivity. In this study, the highest groundwater salinity at 3 wells was predicted using the combined cluster and multiple linear regression analysis. Cross correlation and cluster analysis were applied in order to reduce the number of parameters to effectively predict the quality. After the parameter selection, multiple linear regression was applied and the modeling results obtained were R2 of 0.888, 0.918, and 0.692, respectively. This linear regression model technique can be applied elsewhere in the similar situation.

scholarly journals PENGARUH TRUSTWORTHINESS, EXPERTISE DAN ATTRACTIVENESS CELEBRITY ENDORSER DI INSTAGRAM TERHADAP PURCHASE INTENTION PRODUK HIJAB (Studi Kasus pada Akun Instagram @gitasav)

JEMBATAN ◽  
2019 ◽  
Vol 16 (1) ◽  
pp. 13-30
Author(s):  
Syarifah Fatimah Dina Najib H.A ◽  
Islahuddin Daud ◽  
Aslamia Rosa
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Regression Model ◽  
Purchase Intention ◽  
Sampling Method ◽  
Linear Regression Analysis ◽  
Sampling Technique ◽  
Multiple Linear Regression Analysis ◽  
Analysis Technique ◽  
Celebrity Endorser

This study was aimed to examine the effects of trustworthiness, expertise, and attractiveness of celebrity endorser on Instagram to purchase intention of hijab products. The sampling technique was done by purposive sampling method. The population in this study was followers of the @gitasav Instagram account. Data was collected through distributing questionnaires to 100 respondents. The analysis technique used in this study is multiple linear regression analysis. The results showed that simultaneously the variables of trustworthiness, expertise, and attractiveness had a significant effect on purchase intention. However, partially the purchase intention variable is only influenced by the trustworthiness variable which is equal to 3,878. In this study a regression model was obtained, which is Y = 10,021 + 0,655X1 + 0,038X2 - 0,122X3. 

scholarly journals COVID 19: THE IMPACT OF DEMAND, SUPPLY, AND LABOR

2020 ◽  
Vol 4 (5) ◽  
pp. 60-73
Author(s):  
Hantono
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Data Collection ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Sampling Method ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Independent Variables ◽  
The Impact

This study aims to determine the effect of 1) demand, 2) supply, 3) labor, 4) covid 19. The sampling in this research was conducted by using a incidental sampling method. Methods of data collection through questionnaires that have been distributed to 100 respondents who have met criteria. With multiple linear regression analysis, it shows that the demand, supply, labor both partial and simultaneous have significant effect on covid 19. It can be concluded that mitigation of demand, supply, labor towards covid 19. The results of t test showed that demand is approved and indicates demand has great impact on affecting the covid 19, supply is not approved and indicates supply has less impact on affecting the covid 19, labor is approved and indicates labor has great impact on affecting the covid 19. The results of f test showed that both of the independent variables are simultaneously affecting the covid 19. The result of R Square of the regression model is 0.216 which shows that 21,6 % of mitigation of covid 19 can be explained by demand, supply, labor. Whereas, the 78,4% of covid 19 variable can be explained by other factors or variables which are not examined in this research.

Effect of Work Discipline and Competency on Employee Performance at Goddes Bakery Bali-Indonesia

2021 ◽  
Vol 8 (12) ◽  
pp. 488-496
Author(s):  
Ida Ayu Sri Meitri ◽  
I Made Setena ◽  
Ni Putu Sri Mariyatni
Keyword(s):  
Regression Analysis ◽  
Raw Materials ◽  
Employee Performance ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Knowledge And Skills ◽  
Before And After ◽  
Saturated Sample ◽  
Sample Method ◽  
The Impact

The purpose of this study was to examine the impact of the skills and abilities of Goddes Bakery Bali employees and their compliance with all applicable regulations in the company. There are some employees who work in the production department often experience errors with the lack of knowledge and skills of employees, so many breads are rejected which results in a lack of efficiency in raw materials, employees are often absent for no reason even though the company has carried out daily briefings before and after doing work. This will clearly affect the performance of employees and also the performance of the company. Based on this, it is deemed necessary to examine the effect of competence and discipline on employee performance. Data was collected by distributing questionnaires which were used as research instruments. Sampling was carried out using the saturated sample method or the census method, with 34 respondents. Respondents. Data analysis used multiple linear regression analysis. The results show that Work discipline has a positive and significant effect on employee performance at Goodes Bakery Bali. Which means, the higher the employee's work discipline, the employee's performance will increase. Competence has a positive and significant effect on employee performance at Goodes Bakery Bali. Which means, the higher the competence of employees, the performance of employees will increase. Keywords: Performance, Discipline, Competence.

Analysis of Volumetric Shrinkage and Optimization of Process Parameters in Injection Molding

2012 ◽  
Vol 217-219 ◽  
pp. 2065-2069 ◽  
Author(s):  
Ji Ping Chen ◽  
Zhi Ping Ding
Keyword(s):  
Injection Molding ◽  
Regression Model ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Processing Parameters ◽  
Volumetric Shrinkage ◽  
Plastic Part ◽  
Melt Temperature ◽  
Optimization Of Process Parameters ◽  
Design Variables

Based on experimental method of factorial design, numerical simulation of injection molding using Moldflow software has been done. The effects of the gate number-distribution, melt temperature, packing pressure, packing time, injection time, etc. on volumetric shrinkage and the two-way interactions among factors in injection molding of plastic part have been researched. The regression model for volumetric shrinkage of plastic part has been obtained through multiple linear regression analysis of the experimental data. The optimization model has been established to optimize processing parameters setting leading factors which effect volumetric shrinkage as design variables and regression model of volumetric shrinkage as objective function. The volumetric shrinkage value of plastic part is less than the minimum volumetric shrinkage value of the main experiment, which indicates that the method has a good practical value in engineering.

scholarly journals Pengaruh Penerapan Akuntabilitas Keuangan, Pemanfaatan Teknologi Informasi, Kompetensi Aparatur Pemerintah Dan Ketaatan Peraturan Perundangan Terhadap Kinerja Instansi Pemerintah (Good Governance) Pada Organisasi Perangkat Daerah Kabupaten Bengkalis

2020 ◽  
Vol 4 (1) ◽  
pp. 124-139
Author(s):  
Dariana Dariana ◽  
Annisa Meidyaroza Harrie
Keyword(s):  
Information Technology ◽  
Good Governance ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Government Agencies ◽  
Government Officials ◽  
Financial Accountability ◽  
Saturated Sample ◽  
Sample Method ◽  
Laws And Regulations

This research aims to examine the effect of the application of financial accountability, utilization of information technology, the competence of government officials and compliance with laws and regulations on the performance of government agencies (good governance) partially and simultaneously in the organization of Bengkalis Regency. This research is a survey research with 160 respondents using a saturated sample method. The number of questionnaires returned was able to be processed as many as 130 respondents. This research uses multiple linear regression analysis models. The results of this research indicate that partially and simultaneously financial accountability, utilization of information technology, the competence of local government officials and obedience of laws and regulations have a significant effect on the performance of government agencies (good governance) in Bengkalis Regency regional apparatus organizations.

scholarly journals Short Communication: Prediction of body weight based on body measurements in female Saburai goat

2021 ◽  
Vol 22 (3) ◽  
Author(s):  
AKHMAD DAKHLAN ◽  
MUHAMMAD DIMA IQBAL HAMDANI ◽  
DELSI RUSITAIMI PUTRI ◽  
SULASTRI SULASTRI ◽  
ARIF QISTHON
Keyword(s):  
Body Weight ◽  
Regression Analysis ◽  
Regression Model ◽  
Short Communication ◽  
Linear Regression Analysis ◽  
Information Criterion ◽  
Multiple Linear Regression Analysis ◽  
Regression Equation ◽  
Body Measurements ◽  
Chest Girth

Abstract. Dakhlan A, Hamdani MDI, Putri DR, Sulastri, Qisthon A. 2021. Short Communication: Prediction of body weight based on body measurements in female Saburai goats. Biodiversitas 22: 1391-1396. Saburai goat is a new composite breed in Lampung Province with little information on its performance. This research aimed to predict body weight based on body measurements, namely body length (BL), chest girth (CG), and shoulder height (SH) in female Saburai goats. This study used 42 female Saburai goats aged 3-4 years. The method used in this study was a survey, namely all-female Saburai goats aged 3-4 years were used for this research. The data obtained were analyzed using correlation and simple and multiple linear regression analysis using R program. Coefficient determination (R2), adjusted R2, residual standard error (RSE), Akaike information criterion (AIC), Bayesian information criterion (BIC), and stepwise regression analysis were used to find the best and most parsimonious regression model to predict BW based on body measurements. The results showed that BL, CG, and SH were positively and significantly correlated with BW of female Saburai goats with correlation coefficients of 0.858, 0.956 and 0.862, respectively. Chest girth was the best predictor for BW if using single predictor with regression equation of Ŷ = -31.17 + 0.93X2. However, combination of BL and CG was the best and most parsimonious regression model in predicting BW of female Saburai goat with regression equation of Ŷ = -36.09 + 0.31X1 + 0.72X2 with R2 = 0.941, adjusted R2 = 0.938, RSE = 2.842, AIC = 216.73 and BIC = 223.78. In conclusion, all body measurements in this study (particularly combination of BL and CG) could be used as predictor for BW with high accuracy of prediction. The result of this study suggested that CG and BL could be as indirect criteria to improve BW of female Saburai goats.

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