An Analysis of Elderly Drivers' Traffic Accidents Influential Factors using Multiple Linear Regression

2021 ◽  
Author(s):  
Ahhyeon Hong ◽  
Donghee Noh ◽  
Ju-Hwan Choi
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Traffic Accidents ◽  
Influential Factors ◽  
Elderly Drivers

scholarly journals Production Analysis of Green Mussel (Perna viridis) in Lampung Province

2020 ◽  
Vol 8 (2) ◽  
pp. 975
Author(s):  
Sulvina Sulvina ◽  
Zainal Abidin ◽  
Supono Supono
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Influential Factors ◽  
Perna Viridis ◽  
Factors Affecting ◽  
Cultivation Process ◽  
Quantitative Descriptive

This study was conducted to find out factors affecting and level of mussel production, level of efficiency of using the tools and materials in cultivation process and whether the cultivation of mussels in Pasaran. This study was analyzed using Cobb-Douglass. The study were analyzed in quantitative descriptive, multiple linear regression analysis, and analysis of efficiency. The dependent variable (Y) is the result of production of green mussels cultivation and free variables are the number of bamboos (X 1), the amount of strap (X2), grouper (X3) and labor (X4). Mussel fisherman in Pasaran NPM with Px calculated to obtain the level of efficiency of each factors of production in messels cultivation. Studies show that the most influential factors production are variable bamboo, rope and labor. While the results of analysis the level of efficiency of using tools and materials is not efficient. The number of bamboo and labor should be reduced, because it tends to be a waste and not profitable either technically or economically. The value of the return to scale of 1.22 showed cultivation mussels are on increasing return to scale.

scholarly journals The association between meteorological variables and road traffic injuries: a study from Macao

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6438 ◽  
Author(s):  
Chon-Fu Lio ◽  
Hou-Hon Cheong ◽  
Chon-Hou Un ◽  
Iek-Long Lo ◽  
Shin-Yi Tsai
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Meteorological Factors ◽  
Linear Regression Analysis ◽  
World Health ◽  
Road Traffic Accidents ◽  
Road Traffic Injuries ◽  
Windy Weather

Objective Correlation analysis and multiple linear regression analysis were conducted to estimate the influence of meteorological factors on road traffic injuries stratified by severity. Crash rate was defined as mean monthly road traffic accidents per 1,000 vectors. Design Ecological time-series study. Setting Macao traffic accident registry database between January 1st, 2001 and November 31st, 2016. Participants In total, 393,176 traffic accidents and 72,501 cases of road traffic injuries (RTIs) were enrolled; patients’ severity was divided into mild injury, required hospitalisation, and death. Exposure Variation of monthly meteorological factors. Main outcome measure Weather-condition-related road traffic accidents, injuries, and deaths. Results Windy weather significantly correlated with increased number of traffic accidents among all transport vectors (r = .375 to .637; p < 0.001). Multiple linear regression showed temperature (B = 0.704; p < 0.05) and humidity (B =  − 0.537; p < 0.001) were independent factors for mild injury. The role of windy weather was relatively more obvious among patients with severe injuries (B = 0.304; p < 0.001) or those who died (B = 0.015; p < 0.001). A longer duration of sunshine was also associated to RTI-related deaths (B = 0.015; p < 0.001). In total, 13.4% of RTIs were attributable to meteorological factors and may be preventable. Conclusion The World Health Organization stated that RTIs are a major but neglected public health challenge. This study demonstrates meteorological factors have significant effects on any degree of RTIs. The results may not be generalized to other climates or populations while the findings may have implications in both preventing injuries and to announce safety precautions regarding trauma and motor vehicle collisions to the general public by public agencies.

scholarly journals Pengaruh Pendapatan Pegadaian, Tingkat NPL, Tingkat Inflasi dan Harga Emas Tehadap Penyaluran Pembiayaan Gadai Rahn Pada Pegadaian Syariah

2020 ◽  
Vol 1 (1) ◽  
pp. 246-257
Author(s):  
Mochamad Iqbal Aulia ◽  
Iwan Setiawan
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Research Method ◽  
Inflation Rate ◽  
Regression Method ◽  
Influential Factors ◽  
Gold Price ◽  
Linear Regression Method ◽  
External Influences ◽  
Multiple Linear Regression Method

There are internal and external influences that affect the distribution of financing in sharia pawnshops and in this study there is a phenomenon that is an increase in the distribution of rahn mortgage financing followed by a decrease in income, an increase in the level of NPL, an increase in the inflation rate, and a decline in gold prices. This study aims to analyze factors that are thought to have an influence on rahn financing, namely mortgage income, NPL level, inflation rate, and gold price. This research method is a multiple linear regression method and a classic assumption test. The results of this study are not the influence of pawnshop income on the distribution of rahn pawn financing and significantly influence the level of NPL, inflation rate, and the price of gold on the distribution of mortgage financing rahn. So that in the future can be a reference consideration in the distribution of rahn financing on sharia pawnshops based on these influential factors.

scholarly journals Pengaruh Pendapatan Pegadaian, Tingkat NPL, Tingkat Inflasi dan Harga Emas Tehadap Penyaluran Pembiayaan Gadai Rahn Pada Pegadaian Syariah

2020 ◽  
Vol 1 (1) ◽  
pp. 246-257
Author(s):  
Mochamad Iqbal Aulia ◽  
Iwan Setiawan
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Research Method ◽  
Inflation Rate ◽  
Regression Method ◽  
Influential Factors ◽  
Gold Price ◽  
Linear Regression Method ◽  
External Influences ◽  
Multiple Linear Regression Method

There are internal and external influences that affect the distribution of financing in sharia pawnshops and in this study there is a phenomenon that is an increase in the distribution of rahn mortgage financing followed by a decrease in income, an increase in the level of NPL, an increase in the inflation rate, and a decline in gold prices. This study aims to analyze factors that are thought to have an influence on rahn financing, namely mortgage income, NPL level, inflation rate, and gold price. This research method is a multiple linear regression method and a classic assumption test. The results of this study are not the influence of pawnshop income on the distribution of rahn pawn financing and significantly influence the level of NPL, inflation rate, and the price of gold on the distribution of mortgage financing rahn. So that in the future can be a reference consideration in the distribution of rahn financing on sharia pawnshops based on these influential factors.

scholarly journals Model Hubungan antara Angka Korban Kecelakaan Lalu Lintas dan Faktor Penyebab Kecelakaan pada Jalan Tol Purbaleunyi. (Hal. 124-132)

2019 ◽  
Vol 5 (2) ◽  
pp. 124
Author(s):  
Virlia Dian Fridayanti ◽  
Dwi Prasetyanto
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Traffic Accidents ◽  
Linear Regression Analysis ◽  
Secondary Data ◽  
Correlation Test ◽  
Independent Variables ◽  
Linearity Test ◽  
The Relationship

ABSTRAKKecelakaan lalu lintas merupakan hasil dari kombinasi faktor-faktor penyebab  yang yang terdiri dari faktor manusia, kendaraan, jalan, dan lingkungan. Penelitian ini bertujuan untuk mengetahui variabel dominan dari beberapa faktor penyebab kecelakaan dengan memodelkan hubungan antara angka korban kecelakaan lalu lintas dengan variabel faktor penyebab kecelakaan di Jalan Tol Purbaleunyi pada tahun 2015–2017. Data yang digunakan pada penelitian ini berupa data sekunder yang terdiri dari data jumlah korban dan jumlah kecelakaan yang diakibatkan oleh faktor-faktor penyebab kecelakaan. Metode penelitian yang digunakan dalam penelitian ini adalah metode analisis regresi linear berganda dengan melakukan uji linearitas dan uji korelasi terlebih dahulu. Uji linearitas digunakan untuk memastikan apakah data yang akan dianalisis dapat menggunakan analisis regresi linear atau tidak, sedangkan uji korelasi digunakan untuk menentukan hubungan antara variabel baik antara sesama variabel bebas maupun antara variabel peubah bebas dengan variabel peubah tidak bebas. Berdasarkan hasil penelitian yang dilakukan pada tahun 2015–2017, variabel utama faktor kecelakaan diakibatkan oleh faktor manusia dan faktor kendaraan yaitu variabel mengantuk ( ) dan rem blong ( ).Kata kunci: Kecelakaan lalu lintas, faktor penyebab kecelakaan lalu lintas, regresi linear berganda. ABSTRACTTraffic accidents are the result of a combination of factors causes which consists of the human factor, vehicle, road, and environment. This study aims to determine the majority of the accidents variable of several factors that cause accidents by modeling the relationship between the numbers of traffic accident victims with variable factors causing the accident on Highway Purbaleunyi in 2015–2017. The data used in this study of secondary data consists of data on the number of victims and the number of accidents caused by factors that cause accidents. The method used in this research is multiple linear regression analysis to test the linearity and correlation test beforehand. Linearity test used to determine whether the data will be analyzed using linear regression analysis or not, whereas the correlation test was used to determine the relationship between both variables among the independent variables and the independent variables with the variable variable variable is not free. Based on the results of research conducted in 2015–2017, the main variable of the accident factor is caused by human factors and vehicle factors, which are variable drowsiness ( ) and brake failure ( ).Keywords: Traffic accidents, the causes of traffic accidents, multiple linear regression.

Research on Influential Factors of Visual Website Aesthetics Basing on Multiple Linear Regression Method

2014 ◽  
Vol 666 ◽  
pp. 379-382
Author(s):  
Yang Li ◽  
Yan Qun Huang
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Linear Regression Model ◽  
Multiple Linear Regression Model ◽  
Regression Method ◽  
Influential Factors ◽  
Linear Regression Method ◽  
Mathematical Algorithm ◽  
Visual Aesthetics ◽  
Multiple Linear Regression Method

Visual aesthetics has showed a reliable association with user experience and how to measure the whole visual aesthetic feeling of a web is a challenge. This research aims to provide a regression equation between visual aesthetics and influential factors by constructing a multiple linear regression model. The final result includes six factors, and those are color, style, novelty, font, figure and movement. The model also gives the ranking of the influence power. In a word, ­­this article not only gives a mathematical algorithm to solve the aesthetics problems, but also provides a new way to help designers access to a better visual effect.

scholarly journals Assessment of predictive models for the estimation of heat consumption in kindergartens

2021 ◽  
pp. 84-84
Author(s):  
Nebojsa Jurisevic ◽  
Dusan Gordic ◽  
Arso Vukicevic
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Linear Regression ◽  
Decision Tree ◽  
Multiple Linear Regression ◽  
Predictive Models ◽  
Influential Factors ◽  
Data Availability ◽  
Heat Consumption ◽  
Artificial Neural

The service sector remains the only economic sector that has recorded an increase (3.8%) in energy consumption during the last decade, and it is projected to grow more than 50% in the following decades. Among the public buildings, educational are especially important since they have high abundance, great retrofit potential in terms of energy savings and impact in promoting a culture of energy efficiency. Since predictive models have shown high potential in optimizing usage of energy in buildings, this study aimed to assess their application for both finding the most influential factors on heat consumption in public kindergarten and heat consumption prediction. Two linear (Simple and Multiple Linear Regression) and two non-linear (Decision Tree and Artificial Neural Network) predictive models were utilized to estimate monthly heat consumption in 11 public kindergartens in the city of Kragujevac, Serbia. Top-performing and most complex to develop was the Artificial Neural Network predictive model. Contrary to that, Simple Linear Regression was the least precise but the most simple to develop. It was found that Multiple Linear Regression and Decision Tree were relatively simple to develop and interpret, where in particular the Multiple Linear Regression provided relatively satisfying results with a good balance of precision and usability. It was concluded that the selection of proper predictive methods depends on data availability, and technical abilities of those who utilize and create them, often offering the choice between simplicity and precision.

Pengaruh Motivasi Kerja Terhadap Kinerja Pegawai Kantor Sekretariat Daerah Kabupaten Gunungkidul

2017 ◽  
Vol 23 (2) ◽  
pp. 121-137
Author(s):  
Ary Sutrischastini ◽  
Agus Riyanto
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Sampling Method ◽  
Work Motivation ◽  
Probability Sampling ◽  
Random Probability

This paper will discuss the effect of work motivation (incentives, motives and expectations) on the performance of the staff of the Regional Secretariat Gunungkidul. The purpose of this paper is: 1) Determine the effect of incentives on the performance of the staff of the Regional Secretariat Gunungkidul, 2) Determine the effect of motive on the performance of the staff of the Regional Secretariat Gunungkidul, 3) To know the effect of expectations on the performance of the staff of the Regional Secretariat Gunungkidul, 4)To know the effect of incentives, motives and expectations on the performance of the staff of the Regional Secretariat Gunungkidul.Research sites in the Regional Secretariat Gunungkidul and the population is 162entire employee in the Regional Secretariat Gunungkidul. Samples amounted to 116 respondents taken with simple random probability sampling method. Data were analyzed using multiple linear regression. Results obtained: (1) incentives positive and significant effect on the performance of, (2) motif positive and significant effect on the performance of, (3) expectations positive and significant impact on the performance of , and (4) incentives, motives and expectations of positive and significant impact on the performance of the staff of the Regional Secretariat Gunungkidul.

PENGARUH FAKTOR-FAKTOR INTERNAL PERBANKAN TERHADAP NON PERFORMING FINANCING PADA BANK UMUM SYARIAH

2019 ◽  
Vol 6 (2) ◽  
pp. 115-130
Author(s):  
Eka Ambara Harci Putranta ◽  
Lilik Ambarwati
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Capital Adequacy ◽  
Annual Reports ◽  
Regression Methods ◽  
Capital Adequacy Ratio ◽  
Negative Effect ◽  
Independent Variable

The study aims to analyze the influence of internal banking factors in the form of: Capital Adequency Ratio (CAR), Financing to Deposit Ratio (FDR) and Total Assets (TA) to Non Performing Financing at Sharia Banks. This research method used multiple linear regression analysis with the help of SPSS 16.00 software which is used to see the influence between the independent variables in the form of Capital Adequacy Ratio (CAR), Financing to Deposit Ratio (FDR) and Total Assets (TA) to Non Performing Financing. The sample of this study was 3 Islamic Commercial Banks, so there were 36 annual reports obtained through purposive sampling, then analyzed using multiple linear regression methods. The results showed that based on the F Test, the independent variable had an effect on the NPF, indicated by the F value of 17,016 and significance of 0,000, overall the independent variable was able to explain the effect of 69.60%. While based on the partial t test, showed that CAR has a significant negative effect, Total assets have a significant positive effect with a significance value below 0.05 (5%). Meanwhile FDR does not affect NPF.

Sign in / Sign up

Export Citation Format

Share Document