scholarly journals Pengaruh PAD, Dana Perimbangan dan PMA terhadap Tingkat Kemajuan Daerah Kabupaten dan Kota di Provinsi Sulavesi Selatan

2018 ◽  
Author(s):  
Muhammad Syukri
Keyword(s):  
Regression Model ◽  
Quantitative Data ◽  
Applied Research ◽  
Descriptive Analysis ◽  
Multiple Linear Regression Model ◽  
Multiple Regression Model ◽  
Simultaneous Test ◽  
South Sulawesi ◽  
Direct Benefits ◽  
Research Procedure

The purpose of this study is to determine the effect of locally-generated revenue (PAD), balancing funds and Foreign Direct Investment (FDI) to Progress Regions Level districts and cities in South Sulawesi Province either simultaneously or partially. Type of research used is applied research with quantitative data. The data used obtained from the Statistics Central Institution (BPS), which covers 24 districts and cities of South Sulawesi Province in 2016 in the form of thousands of rupiah. The research procedure is (1) Descriptive Analysis. (2) Establish multiple regression model. (3) Partial test and simultaneous test, and (4) determine the coefficient determination. Based on the simultaneous test of multiple linear regression model that PAD (X1), Balance Funds (X2) and FDI (X3) have significant effect to regional progress level (Y). And partial model testing, only PAD (X1) and fund balancing (X2) which significantly influence to regional progress level (Y). Meanwhile, FDI (X3) has no significant effect on regional progress level (Y). Therefore, the cultivation of FDI should be targeted and can provide direct benefits for the community in improving their welfare that will impact on improving regional progress. The suggestions needed in the development of further research that is required addition of other variables that can affect the level of regional progress.

scholarly journals Decrease in Serum Urate Level Is Associated With Loss of Visceral Fat in Male Gout Patients

2021 ◽  
Vol 12 ◽  
Author(s):  
Zijing Ran ◽  
Xiaomei Xue ◽  
Lin Han ◽  
Robert Terkeltaub ◽  
Tony R. Merriman ◽  
...  
Keyword(s):  
Regression Model ◽  
Visceral Fat ◽  
Multiple Linear Regression Model ◽  
Serum Urate ◽  
Multiple Regression Model ◽  
Final Visit ◽  
Visceral Fat Area ◽  
Serum Urate Level ◽  
Lowering Therapy ◽  
The Relationship

ObjectiveTo clarify the relationship between serum urate (SU) decrease and visceral fat area (VFA) reduction in patients with gout.MethodsWe retrospectively analyzed 237 male gout patients who had two sets of body composition and metabolic measurements within 6 months. Subjects included had all been treated with urate-lowering therapy (ULT) (febuxostat 20–80 mg/day or benzbromarone 25–50 mg/day, validated by the medical record). All patients were from the specialty gout clinic of The Affiliated Hospital of Qingdao University. The multiple linear regression model evaluated the relationship between change in SU [ΔSU, (baseline SU) – (final visit SU)] and change in VFA [ΔVFA, (baseline VFA) – (final visit VFA)].ResultsULT resulted in a mean (standard deviation) decrease in SU level (464.22 ± 110.21 μmol/L at baseline, 360.93 ± 91.66 μmol/L at the final visit, p <0.001) accompanied by a decrease in median (interquartile range) VFA [97.30 (81.15–118.55) at baseline, 90.90 (75.85–110.05) at the final visit, p < 0.001]. By multiple regression model, ΔSU was identified to be a significant determinant variable of decrease in VFA (beta, 0.302; p = 0.001).ConclusionsThe decrease in SU level is positively associated with reduced VFA. This finding provides a rationale for clinical trials to affirm whether ULT promotes loss of visceral fat in patients with gout.

scholarly journals A multiple regression model for prediction of optimal dose of Moringa Oleifera in faecal sludge dewatering

2021 ◽  
Author(s):  
Benjamin Doglas ◽  
Richard Kimwaga ◽  
Aloyce Mayo
Keyword(s):  
Regression Model ◽  
Moringa Oleifera ◽  
Multiple Linear Regression Model ◽  
Optimal Dose ◽  
Multiple Regression Model ◽  
Coefficient Of Determination ◽  
Septic Tank ◽  
Contributing Factors ◽  
Jar Test ◽  
The University

Abstract Moringa Oleifera (MO) is a highly effective conditioner in the dewatering of Fecal sludge (FS). However, the model for the prediction of its optimal dose has not yet been documented. This article presents the results of the developed model for the prediction of MO optimal doses. The developed model was based on assessing the FS parameters and MO stock solution. The FS samples were obtained from a mixture of a pit latrine and septic tank and were analyzed at the water quality laboratory of the University of Dar es Salaam. The multiple linear regression model was used to establish a relationship between MO optimal dose as a function of FS characteristics (pH, Electrical Conductivity, Total Solids and Total Suspended Solids) and concentration of MO stock solution. The results indicated that the main contributing factors which determine the MO optimal dose were the concentration of MO stock solution, followed by pH of FS. The model results showed a good agreement between the predicted and observed MO optimal dose with a coefficient of determination of R2 = 0.72 and 0.9 for calibration and validation respectively. Therefore, the model can be adapted to determine the MO optimal dose without running the Jar-test experiment.

scholarly journals Impact of working capital on firm’s profitability

2015 ◽  
Vol 2 (3) ◽  
pp. 1-4
Author(s):  
Agha Ammad Nabi ◽  
Muhammad Matin
Keyword(s):  
Regression Model ◽  
Quantitative Data ◽  
Positive Relationship ◽  
Descriptive Analysis ◽  
Working Capital ◽  
The Impact ◽  
The Relationship

The purpose of this research is to find the relationship between working capital and firm’s profitability. Basically, to check the impact of working capital on firms profitability. The quantitative data is used in this research. The financials of the banks support me to check the impact whether it is positive or negative. I used certain test for this research i-e Regression model, Anova and descriptive analysis. These all test conclude that there is a positive relationship between working capital and firms profitability.  

scholarly journals Analysis of Competitiveness in the Field of Brackish Water Aquaculture in Indonesia

2021 ◽  
pp. 21-29
Author(s):  
Afifah Sabila ◽  
Asep Agus Handaka Suryana ◽  
. Iskandar
Keyword(s):  
Brackish Water ◽  
Descriptive Analysis ◽  
Secondary Data ◽  
Primary Data ◽  
Final Value ◽  
Expert Opinions ◽  
South Sulawesi ◽  
Research Procedure ◽  
Qualitative Descriptive ◽  
Brackish Water Aquaculture

This study was conducted from August 2020 to July 2021. Competitiveness can be interpreted as the ability of a region to make it excel in producing a commodity more than any other region. The competitiveness, especially in the field of brackish water aquaculture can be known through several indicators, i.e. human resources, infrastructure, production and science and technology. This study aims as an effort to realizing fisheries development in Indonesia by knowing the competitiveness profile of brackish water aquaculture in Indonesia through qualitative descriptive analysis method. The research procedure was conducted in several stages, the first of which was the collection of secondary data at the Ministry of Marine Affairs and Fisheries. The second stage is to analyze the primary data in the form of expert opinions or competent people in their fields. Then the last stage is to analyze the data that has been obtained during the research. Based on the results of the study, it was concluded that the competitiveness profile of brackish water aquaculture in Indonesia was outperformed by south Sulawesi province with a final value of 17.03, while the region with the lowest competitiveness value was Riau Islands Province with a final value of 0.05.

scholarly journals Extents of Predictors for Land Surface Temperature Using Multiple Regression Model

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
R. M. Yuvaraj
Keyword(s):  
Surface Temperature ◽  
Regression Model ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Climate Models ◽  
Multiple Linear Regression Model ◽  
Multiple Regression Model ◽  
Landsat 8 ◽  
Study Region

Land surface temperature (LST) is a key factor in numerous areas such as climate change, land use/land cover in the urban areas, and heat balance and is also a significant participant in the creation of climate models. Landsat data has given numerous possibilities to understand the land processes by means of remote sensing. The present study has been performed to identify the LST of the study region using Landsat 8 OLI/TIRS satellite images for two time periods in order to compare the data. The study also attempted to identify and predict the role and importance of NDVI, NDBI, and the slope of the region on LST. The study concludes that the maximum and minimum temperatures of 40.44 C and 20.78 C were recorded during the November month whereas the maximum and minimum LST for month March has increased to 42.44 C and 24.57 C respectively. The result indicates that LST is inversely proportional to NDVI (−6.369) and slope (−0.077) whereas LST is directly proportional to NDBI (+14.74). Multiple linear regression model has been applied to calculate the extents of NDVI, NDBI, and slope on the LST. It concludes that the increase in vegetation and slope would result in slight decrease in temperature whereas the increase in built-up will result in a huge increase in temperature.

scholarly journals Kelayakan Operasional Hotel Nonbintang di Sulawesi Selatan

2020 ◽  
Vol 2 (1) ◽  
pp. 44-51
Author(s):  
Daniel Adolf Ohyver ◽  
Nursjam Nursjam ◽  
Kurnia Yusniar Rahman
Keyword(s):  
Applied Research ◽  
Descriptive Analysis ◽  
Qualitative Approach ◽  
South Sulawesi ◽  
Regional Tourism ◽  
Analysis Technique ◽  
Product Service ◽  
Assessment Guidelines

This research aims to know the condition of non-star hotels in relation to product, service and management aspects. In addition, this research was also carried out with the intention of evaluating the feasibility of operating non-star hotels in South Sulawesi. This type of research is applied research with a qualitative approach. Information is obtained through observation using check lists, interviews, and documentation in the form of assessment guidelines. Determination of informants was taken in 10 regions with a total of 56 hotels, each hotel has one informant, plus 10 informants from the Regional Tourism Office, so the number of informants became 66 people. The analysis technique used is descriptive analysis. The results showed that, of the 56 non-starred hotels studied there were 23 that were less feasible, 19 were feasible and 14 were very feasible.

scholarly journals Parameter Estimation of Bayesian Multiple Regression Model with Informative Inverse Gamma Prior Distribution: Application to Malaria Symptom Dataset

2020 ◽  
pp. 71-86
Author(s):  
Drinold Aluda Mbete
Keyword(s):  
Parameter Estimation ◽  
Regression Model ◽  
Multiple Regression ◽  
Prior Distribution ◽  
Least Squares Method ◽  
Average Distance ◽  
Multiple Linear Regression Model ◽  
Multiple Regression Model ◽  
Inverse Gamma ◽  
Highest Posterior Density

Objectives: The study aims to develop a Bayesian multiple regression model with informative inverse gamma prior and t the model to malaria symptom dataset.Place and Duration of Study: The study was carried out in Masinde Muliro University of Science and Technology (MMUST). The study used 300 malaria related symptom dataset obtained from Health service records of different patients (students) between the time period of 1st January, 2015 to 20th December, 2015.Methodology: Multiple linear regression model with Bayesian parameter estimation is used. The Normal prior distribution for θ parameter and inverse gamma prior distribution for the σ2 parameter is derived. Gibbs sampler and Metropolis Hasting algorithm is used with Markov Chain Monte Carlo (MCMC) method to produce an iteration of about 102,491 with Burn-in of 2500 and thinning of 10 that resulting to eective sample size of 90000.Results: The results shows that all the estimated posterior predictive p-values are between 0.05 and 0.95 indicating an adequate t for the individual observation of the data in the model. The results also reveals that the data values and the average distance between the data values and the mean tend to be close to each other and the estimated coeffcient of θ′s approximately 95%draws fall within each of the corresponding highest posterior density intervals. Conclusion: Though the Least Squares method is sucient for estimating the coeffcients of the regression parameters, the Bayesian estimates recorded comparatively very small standard errors making the Bayesian method more robust in analysing symptom dataset.

scholarly journals Recent Changes in Downward Longwave Radiation at King Sejong Station, Antarctica

2008 ◽  
Vol 21 (22) ◽  
pp. 5764-5776 ◽  
Author(s):  
Hi Ku Cho ◽  
Jhoon Kim ◽  
Yeonjin Jung ◽  
Yun Gon Lee ◽  
Bang Yong Lee
Keyword(s):  
Time Series ◽  
Regression Model ◽  
Air Temperature ◽  
Multiple Linear Regression Model ◽  
Longwave Radiation ◽  
Multiple Regression Model ◽  
Specific Humidity ◽  
Annual Data ◽  
Mean Values ◽  
Downward Longwave Radiation

Abstract Effects of cloud, air temperature, and specific humidity on downward longwave irradiance and their long-term variabilities are examined by analyzing the measurements made at the King Sejong Station in the Antarctic Peninsula during the period of 1996–2006. It has been shown that the downward longwave irradiance (DLR) is significantly correlated with three variables: air temperature, specific humidity, and cloudiness. Based on the relationship of the three variables with DLR, a multiple linear regression model has been developed in order to evaluate the relative contribution of each of the variables to the variation of DLR. The three variables together explained 75% of all the variance in daily mean DLR. The respective contribution from specific humidity and cloudiness to the variation of DLR was 46% and 23%; thus most of the DLR variability can be explained by the variations in the two variables. The annual mean of longwave cloud forcing shows 52 W m−2 with no remarkable seasonal cycle. It is also noted that the overcast cloud effect gives an increase by 65 W m−2 with respect to clear-sky flux throughout the year. It is suggested that the multiple regression model can be used to estimate the radiative forcings of variables influencing the DLR variability. A highly significant decrease in DLR with an average of −1.52 W m−2 yr−1 (−0.54% yr−1) is found in an analysis from the time series of the deseasonalized monthly mean values. Accordingly, the atmospheric flux emissivity, air temperature, and specific humidity have also decreased in their time series, while the cloudiness has increased insignificantly. Consequently, it may be concluded that the recent decrease in DLR is mainly attributed to the net cooling effect due to the decrease in air temperature and specific humidity, which overwhelm the slight warming effect in cloudiness. Analysis of mean monthly trends for individual months shows that, as for the annual data, the variations in DLR are mostly associated with those of air temperature, specific humidity, and cloudiness.

scholarly journals The Effect of Distance Teaching on Academic Achievement in the Online Course of Introduction to Computers Science

2020 ◽  
Vol 1 (2) ◽  
pp. p23
Author(s):  
Ying-Sheng Kuo
Keyword(s):  
Regression Model ◽  
Student Performance ◽  
Online Teaching ◽  
Multiple Linear Regression Model ◽  
Multiple Regression Model ◽  
Distance Teaching ◽  
Final Test ◽  
Final Exam ◽  
Model Combining ◽  
On Line

For distance teaching, if the teacher can obtain the predicted scores that students may obtain in the final exam at this time, the students whose predicted scores do not meet the standard can be found. Teachers can strengthen the teaching of this type of students in the teaching process, which will greatly improve the overall teaching efficiency of teachers. The target of this research is the students of the course of the “Introduction to Computers Science” at Open University of Kaohsiung. This course is a distance teaching based on online teaching, and the questionnaire and final test are also completed on line. A total of 95 students filled out the questionnaire online, accounting for 77.24% of the electives. This study aims to assess the measurement of students’ pre-learning computer experience, software operation ability, learning motivation, and computer attitude, and analyze their relationship with the performance of subsequent distance teaching on the course of the “Introduction to Computers Science”, and find a multiple regression model to predict student performance. It was found that a multiple linear regression model combining 7 independent variables was statistically significantly related to the final test scores.

scholarly journals Variations in the Distribution of Chl-a and Simulation Using a Multiple Regression Model

2019 ◽  
Vol 16 (22) ◽  
pp. 4553
Author(s):  
Jiancai Deng ◽  
Fang Chen ◽  
Weiping Hu ◽  
Xin Lu ◽  
Bin Xu ◽  
...  
Keyword(s):  
Regression Model ◽  
Lake Taihu ◽  
Sampling Site ◽  
Secchi Depth ◽  
Multiple Linear Regression Model ◽  
Multiple Regression Model ◽  
Interactive Effects ◽  
Important Indicator ◽  
Chl A ◽  
Meiliang Bay

Chlorophyll a (Chl-a) is an important indicator of algal biomass in aquatic ecosystems. In this study, monthly monitoring data for Chl-a concentration were collected between 2005 and 2015 at four stations in Meiliang Bay, a eutrophic bay in Lake Taihu, China. The spatiotemporal distribution of Chl-a in the bay was investigated, and a statistical model to relate the Chl-a concentration to key driving variables was also developed. The monthly Chl-a concentration in Meiliang Bay changed from 2.6 to 330.0 μg/L, and the monthly mean Chl-a concentration over 11 years was found to be higher at sampling site 1, the northernmost site near Liangxihe River, than at the three other sampling sites. The annual mean Chl-a concentration fluctuated greatly over time and exhibited an upward trend at all sites except sampling site 3 in the middle of Meiliang Bay. The Chl-a concentration was positively correlated with total phosphorus (TP; r = 0.57, p < 0.01), dissolved organic matter (DOM; r = 0.73, p < 0.01), pH (r = 0.44, p < 0.01), and water temperature (WT; r = 0.37, p < 0.01), and negatively correlated with nitrate (NO3−-N; r = −0.28, p < 0.01), dissolved oxygen (DO; r = −0.12, p < 0.01), and Secchi depth (ln(SD); r = −0.11, p < 0.05). A multiple linear regression model integrating the interactive effects of TP, DOM, WT, and pH on Chl-a concentrations was established (R = 0.80, F = 230.7, p < 0.01) and was found to adequately simulate the spatiotemporal dynamics of the Chl-a concentrations in other regions of Lake Taihu. This model provides lake managers with an alternative for the control of eutrophication and the suppression of aggregations of phytoplankton biomass at the water surface.

Sign in / Sign up

Export Citation Format

Share Document