scholarly journals Influence of social media advertising, e-marketing and product quality on the process of purchasing nature cosmetics

2019 ◽  
Vol 8 (5) ◽  
pp. 316-321
Author(s):  
Syawaluddin Syawaluddin ◽  
Joni Joni ◽  
Erwin Erwin
Keyword(s):  
Social Media ◽  
Linear Regression ◽  
Product Quality ◽  
Linear Regression Model ◽  
Multiple Linear Regression Model ◽  
Coefficient Of Determination ◽  
Environment Friendly ◽  
Social Media Advertising ◽  
North Sumatra

This study seeks to investigate the role of Social Media Advertising, E-Marketing, and Product Quality on Consumers’ Decision to Purchase Nature Cosmetics in North Sumatra-Indonesia partially and simultaneously. The data were analyzed using multiple Linear Regression model and coefficient of Determination. This research leads to the results that variables of Social Media Advertising, E-Marketing, and Product Quality simultaneously have a positive and significant impact on consumers’ decision in making purchases of Nature Cosmetics in North Sumatra-Indonesia and partially the variable of product quality is more dominant in consumers’ decision in purchasing Environment-friendly Cosmetics in North Sumatra-Indonesia. The coefficient of determination (R Square) shows that the variable of Social Media Advertising, E-Marketing, Product Quality is 0,593 or 59.3% while the remaining 40,7% is affected by other factors beyond the scope of this study.

Whole Facility Measurement for Quantifying Energy Saving in an Office Building, Malaysia

2015 ◽  
Vol 785 ◽  
pp. 676-681 ◽  
Author(s):  
Nor Shahida Razali ◽  
Nofri Yenita Dahlan
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Energy Saving ◽  
Linear Regression Model ◽  
Energy Use ◽  
Multiple Linear Regression Model ◽  
Office Building ◽  
Coefficient Of Determination ◽  
Independent Variable

This paper presents the concept of International Performance Measurement and Verification Protocol (IPMVP) for determining energy saving at whole facility level for an office building in Malaysia. Regression analysis is used to develop baseline model from a set of baseline data which correlates baseline energy with appropriate independents variables, i.e. Cooling Degree Days (CDD) and Number of Working Days (NWD) in this paper. In determining energy savings, the baseline energy is adjusted to the same set condition of reporting period using energy cost avoidance approach. Two types of energy saving analyses have been presented in the case study; 1) Single linear regression for each independent variable, 2) Multiple linear regression for each independent variable. Results show that NWD has coefficient of determination, R2 higher than CDD which indicates that NWD has stronger correlation with the energy use than CDD in the building. Finding also shows that the R2 for multiple linear regression model are higher than single linear regression model. This shows the fact that more than one component are affecting the energy use in the building.

scholarly journals Pengaruh pendapatan, kepercayaan dan religiusitas terhadap minat untuk membayar zakat penghasilan

2021 ◽  
Vol 1 (1) ◽  
pp. 12-24
Author(s):  
Sumadi Sumadi ◽  
Dini Priliastuti
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Linear Regression Model ◽  
Multiple Linear Regression Model ◽  
Sampling Technique ◽  
Quantitative Approach ◽  
Research Model ◽  
Probability Sampling

This study aims to determine the effect of income, belief, and religiosity on the interest in paying zakat income (study of residents of Makamhaji Kartasura). This study uses a quantitative approach to the population of Makamhaji Kartasura Village residents. The sampling technique uses probability sampling to analyze the data using a multiple linear regression model. The results showed that income had no significant effect on the interest in paying zakat income. In contrast, trust and religiosity have a significant effect on the interest in paying zakat income. Meanwhile, simultaneous income, belief, and religiosity have influenced the residents of Makamhaji Kartasura Village to pay zakat income. This research model contributes to explaining the role of trust and religiosity on increasing zakat income.

scholarly journals Performance of farming extension field during the COVID-19 pandemic in East Java

2021 ◽  
Vol 892 (1) ◽  
pp. 012030
Author(s):  
A Purwidyaningrum ◽  
M Rondhi ◽  
T D Hapsari
Keyword(s):  
Linear Regression ◽  
Linear Regression Model ◽  
Random Sampling ◽  
Descriptive Analysis ◽  
Multiple Linear Regression Model ◽  
Extension Field ◽  
Work Training ◽  
Good Environment ◽  
Cluster Random Sampling

Abstract The success of farming extension activities cannot be separated from the role of farming extension workers. In this pandemic, farming extension counseling must be continue to make good environment. Social and physical distancing can make limited access for farming extension workers in carry out their roles. The purpose of this study was to analyze the performance of farming extension field and the influenced factors of perfomance farming extension field during the pandemic in East Java. This research is located in East Java province, it was conducted from March 2020 to 2021. The sampling was carried out by cluster random sampling and it got 360 respondents. The data collected by using statistical descriptive analysis which is used a scale and multiple linear regression model. The result of this research during the pandemic was going well. Meanwhile, the was the factors that influence in performance of farming extension (age, work training, topography and availability of infrastructure) but distance, farmer group, and education did not have impact on it.

scholarly journals The Effects of Stressors on Academic Performance of International Students in Jiangsu University: The Moderating Role of Coping Strategies

2021 ◽  
Vol 9 (10) ◽  
pp. 1617-1632
Author(s):  
Michael Kobina Gyan
Keyword(s):  
Academic Performance ◽  
International Students ◽  
Linear Regression ◽  
Coping Strategies ◽  
Linear Regression Model ◽  
Multiple Linear Regression Model ◽  
Male And Female ◽  
The University ◽  
Moderating Role

Abstract: This paper examined the effects of stressors on academic performance of international students in Jiangsu University: the moderating role of coping strategies. The sample comprised randomly selected 228 international students from the university across all levels; bachelor, masters and PhD. We used multiple linear regression model to estimate the findings. Among our empirical results are: (1) stressors have adversative effects on students’ academic performance. (2) Male and female international students differ with regard to the effects of stressors on their academic performance. (3) The effect of stressors on students’ academic performance differ among bachelor, masters and PhD international students. (4) International students employed different strategies of coping throughout their study duration in order to minimize their stress levels and to attain higher levels of academic performance. The study found that, Problem-focused strategies were positively related to international students’ academic performance on the premise of its ability to minimize stress. Based on the empirical findings, we profess appropriate recommendations to stakeholders for action. Keywords: Stressors, International Students Academic Performance, Coping Strategies

scholarly journals Estimation of Health-Related Physical Fitness Using Multiple Linear Regression in Korean Adults: National Fitness Award 2015–2019

2021 ◽  
Vol 12 ◽  
Author(s):  
Sung-Woo Kim ◽  
Hun-Young Park ◽  
Hoeryong Jung ◽  
Jinkue Lee ◽  
Kiwon Lim
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Cardiorespiratory Fitness ◽  
Linear Regression Model ◽  
Multiple Linear Regression Model ◽  
Coefficient Of Determination ◽  
Muscular Endurance ◽  
Dependent Variables ◽  
Health Related

Continuous health care and the measurement of health-related physical fitness (HRPF) is necessary for prevention against chronic diseases; however, HRPF measurements including laboratory methods may not be practical for large populations owing to constraints such as time, cost, and the requirement for qualified technicians. This study aimed to develop a multiple linear regression model to estimate the HRPF of Korean adults, using easy-to-measure dependent variables, such as gender, age, body mass index, and percent body fat. The National Fitness Award datasets of South Korea were used in this analysis. The participants were aged 19–64 years, including 319,643 male and 147,600 females. HRPF included hand grip strength (HGS), flexibility (sit and reach), muscular endurance (sit-ups), and cardiorespiratory fitness (estimated VO2max). An estimation multiple linear regression model was developed using the stepwise technique. The outlier data in the multiple regression model was identified and removed when the absolute value of the studentized residual was ≥2. In the regression model, the coefficient of determination for HGS (adjusted R2: 0.870, P < 0.001), muscular endurance (adjusted R2: 0.751, P < 0.001), and cardiorespiratory fitness (adjusted R2: 0.885, P < 0.001) were significantly high. However, the coefficient of determination for flexibility was low (adjusted R2: 0.298, P < 0.001). Our findings suggest that easy-to-measure dependent variables can predict HGS, muscular endurance, and cardiorespiratory fitness in adults. The prediction equation will allow coaches, athletes, healthcare professionals, researchers, and the general public to better estimate the expected HRPF.

scholarly journals Faktor-Faktor Yang Mempengaruhi Kinerja Bank Devisa Yang Terdaftar Di Bursa Efek Indonesia (2013-2017)

2018 ◽  
Vol 1 (2) ◽  
pp. 69-76
Author(s):  
Hartanti Hartanti
Keyword(s):  
Quantitative Analysis ◽  
Linear Regression ◽  
Foreign Exchange ◽  
Linear Regression Model ◽  
Stock Exchange ◽  
Multiple Linear Regression Model ◽  
Coefficient Of Determination ◽  
Performance Factors ◽  
Exchange Performance ◽  
Simultaneous Influence

Performance is a tool to evaluate the success of the company in running its business. This study aims to examine the performance factors of Foreign Exchange Banks Listed on the Indonesia Stock Exchange. Performance factors in this study were measured by the ratio of CAR, NPL, LDR, BOPO, GWM while Performance measured by ROA. This study uses quantitative analysis with multiple linear regression model to test the influence of these factors on the performance of foreign exchange banks simultaneously or partially. The results showed that there was a significant and simultaneous influence between CAR, NPL, LDR, BOPO, GWM on Foreign Exchange Bank ROA. Coefficient of determination simultaneously CAR, NPL, LDR, BOPO, GWM affect ROA of 85,6% and the rest influenced by other factors. Partially CAR, NPL and GWM have no significant effect on ROA of Foreign Exchange Bank. while the LDR and BOPO have a negative and significant effect on the ROA of Foreign Exchange Bank.

An Enhanced Multiple Linear Regression Model for Seasonal Rainfall Prediction

2020 ◽  
Vol 10 (4) ◽  
pp. 473-483
Author(s):  
Pundra Chandra Shaker Reddy ◽  
Alladi Sureshbabu
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Linear Regression Model ◽  
Weather Prediction ◽  
Big Data Analytics ◽  
Multiple Linear Regression Model ◽  
Seasonal Rainfall ◽  
Climate Data ◽  
Rainfall Forecasting

Aims & Background: India is a country which has exemplary climate circumstances comprising of different seasons and topographical conditions like high temperatures, cold atmosphere, and drought, heavy rainfall seasonal wise. These utmost varieties in climate make us exact weather prediction is a challenging task. Majority people of the country depend on agriculture. Farmers require climate information to decide the planting. Weather prediction turns into an orientation in farming sector to deciding the start of the planting season and furthermore quality and amount of their harvesting. One of the variables are influencing agriculture is rainfall. Objectives & Methods: The main goal of this project is early and proper rainfall forecasting, that helpful to people who live in regions which are inclined natural calamities such as floods and it helps agriculturists for decision making in their crop and water management using big data analytics which produces high in terms of profit and production for farmers. In this project, we proposed an advanced automated framework called Enhanced Multiple Linear Regression Model (EMLRM) with MapReduce algorithm and Hadoop file system. We used climate data from IMD (Indian Metrological Department, Hyderabad) in 1901 to 2002 period. Results: Our experimental outcomes demonstrate that the proposed model forecasting the rainfall with better accuracy compared with other existing models. Conclusion: The results of the analysis will help the farmers to adopt effective modeling approach by anticipating long-term seasonal rainfall.

scholarly journals Magnetization Transfer Ratio of Peripheral Nerve and Skeletal Muscle

2021 ◽  
Author(s):  
Olivia Fösleitner ◽  
Véronique Schwehr ◽  
Tim Godel ◽  
Fabian Preisner ◽  
Philipp Bäumer ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Body Weight ◽  
Sciatic Nerve ◽  
Linear Regression ◽  
Peripheral Nerve ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Linear Regression Model ◽  
Magnetization Transfer ◽  
Multiple Linear Regression Model

Abstract Purpose To assess the correlation of peripheral nerve and skeletal muscle magnetization transfer ratio (MTR) with demographic variables. Methods In this study 59 healthy adults evenly distributed across 6 decades (mean age 50.5 years ±17.1, 29 women) underwent magnetization transfer imaging and high-resolution T2-weighted imaging of the sciatic nerve at 3 T. Mean sciatic nerve MTR as well as MTR of biceps femoris and vastus lateralis muscles were calculated based on manual segmentation on six representative slices. Correlations of MTR with age, body height, body weight, and body mass index (BMI) were expressed by Pearson coefficients. Best predictors for nerve and muscle MTR were determined using a multiple linear regression model with forward variable selection and fivefold cross-validation. Results Sciatic nerve MTR showed significant negative correlations with age (r = −0.47, p < 0.001), BMI (r = −0.44, p < 0.001), and body weight (r = −0.36, p = 0.006) but not with body height (p = 0.55). The multiple linear regression model determined age and BMI as best predictors for nerve MTR (R2 = 0.40). The MTR values were different between nerve and muscle tissue (p < 0.0001), but similar between muscles. Muscle MTR was associated with BMI (r = −0.46, p < 0.001 and r = −0.40, p = 0.002) and body weight (r = −0.36, p = 0.005 and r = −0.28, p = 0.035). The BMI was selected as best predictor for mean muscle MTR in the multiple linear regression model (R2 = 0.26). Conclusion Peripheral nerve MTR decreases with higher age and BMI. Studies that assess peripheral nerve MTR should consider age and BMI effects. Skeletal muscle MTR is primarily associated with BMI but overall less dependent on demographic variables.

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