scholarly journals Modeling Population Spatial-Temporal Distribution Using Taxis Origin and Destination Data

2021 ◽  
Vol 13 (7) ◽  
pp. 3727
Author(s):  
Fatema Rahimi ◽  
Abolghasem Sadeghi-Niaraki ◽  
Mostafa Ghodousi ◽  
Soo-Mi Choi
Keyword(s):  
Regression Analysis ◽  
Mean Squared Error ◽  
Population Distribution ◽  
Temporal Distribution ◽  
Coefficient Of Determination ◽  
Temporal Modeling ◽  
Location Data ◽  
Time Period ◽  
Proposed Model

During dangerous circumstances, knowledge about population distribution is essential for urban infrastructure architecture, policy-making, and urban planning with the best Spatial-temporal resolution. The spatial-temporal modeling of the population distribution of the case study was investigated in the present study. In this regard, the number of generated trips and absorbed trips using the taxis pick-up and drop-off location data was calculated first, and the census population was then allocated to each neighborhood. Finally, the Spatial-temporal distribution of the population was calculated using the developed model. In order to evaluate the model, a regression analysis between the census population and the predicted population for the time period between 21:00 to 23:00 was used. Based on the calculation of the number of generated and the absorbed trips, it showed a different spatial distribution for different hours in one day. The spatial pattern of the population distribution during the day was different from the population distribution during the night. The coefficient of determination of the regression analysis for the model (R2) was 0.9998, and the mean squared error was 10.78. The regression analysis showed that the model works well for the nighttime population at the neighborhood level, so the proposed model will be suitable for the day time population.

scholarly journals ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI PROFITABILITAS BANK UMUM SYARIAH DI INDONESIA

2020 ◽  
Vol 6 (8) ◽  
pp. 1607
Author(s):  
Dian Anggraini ◽  
Imron Mawardi
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Commercial Bank ◽  
Confidence Level ◽  
Linear Regression Analysis ◽  
Sampling Technique ◽  
Multiple Linear Regression Analysis ◽  
Coefficient Of Determination

The purpose of this study is to analyze the factors that affect the profitability of Sharia Commercial Bank in Indonesia. The sampling technique used is saturated sampling, so the population and sample is the Sharia Commercial Bank periode October 2014-March 2018 which amounted to 42 months. This study uses a quantitative approach with multiple linear regression analysis technique.The result showed that with 95% confidence level partially variable Financing to Deposit Ratio have significant effect to profitability, while variable Natural Uncertainty Contract Financing, Non Performing Financing, and Equity have no significant effect on profitability of Sharia Commercial Bank in Indonesia. Nevertheless, Natural Uncertainty Contract Financing, Non Performing Financing, Financing to Deposit Ratio and Equity simultaneously have significant effect to the profitability of Sharia Commercial Bank in Indonesia. With the coefficient of determination of 33,2%.Keywords: Natural Uncertainty Contract, Non Performing Financing, Financing to Deposit Ratio, Equity

scholarly journals PENGARUH PELATIHAN DAN MOTIVASI TERHADAP KINERJA KARYAWAN PADA HEAD OFFICE PADA PT PAM LYONNASE JAYA (PALYJA)

Epigram ◽  
2018 ◽  
Vol 14 (2) ◽  
Author(s):  
Anggi Fathya Anindita ◽  
Tuty Herawati ◽  
Wahyudi Utomo
Keyword(s):  
Regression Analysis ◽  
Strong Influence ◽  
Test Validity ◽  
Secondary Data ◽  
Primary Data ◽  
Coefficient Of Determination ◽  
Reliability Test ◽  
Head Office ◽  
Training Motivation

Abstract Influence of training and motivation on performance of employees at PT PAM Lyonnase Jaya (PALYJA). 2017. This research aims to find out how the influences between the training and motivation on performance of employees. Data collection using the questionnaire given to the respondents to obtain primary data and secondary data to obtain an libraries. While the method of data analysis using the test validity dan reliability, test the assumptionsof classical, test hypotheses, multiple linier regression analysis, analysis of the coefficient of determination of the significance of the T-test, and a test of the significance of f. Result of the research indicate that training has a strong influence on performance of employees and motivation have influence of 66,8% on performance of employees and the remaining 33,2% are influenced by other factors.Keywords: Training, Motivation, Employee Performance.AbstrakPengaruh Pelatihan dan Motivasi terhadap Kinerja Karyawan Pada head office PT PAM Lyonnase Jaya (PALYJA). 2017. Penelitian ini bertujuan untuk mengetahui seberapa pengaruh antara pelatihan dan motivasi terhadap kinerja karyawan. Pengumpulan data menggunakan kuesioner yang diberikan kepada responden untuk memperoleh data primer dan studi kepustakaan untuk memperolah data sekunder. Sedangkan metode analisis data menggunakan uji validitas dan reliabilitas, uji asumsi klasik, uji hipotesis, analisis regresi linier berganda, analisis koefisien determinasi, uji signifikansi T dan uji signifikansi F. Hasil penelitian menunjukan bahwa pelatihan memiliki pengaruh yang kuat terhadap kinerja karyawan dan motivasi memiliki pengaruh sebesar 66,8% terhadap kinerja karyawan dan sisanya 33,2% dipengaruhi oleh faktor lain.Kata Kunci: Pelatihan, Motivasi, Kinerja Karyawan

scholarly journals Applicability of CHIRPS-based satellite rainfall estimates for South Africa

2021 ◽  
Vol 63 (3) ◽  
pp. 1-12
Author(s):  
J A du Plessis ◽  
J K Kibii
Keyword(s):  
South Africa ◽  
Temporal Distribution ◽  
Pairwise Comparison ◽  
Monthly Rainfall ◽  
Rainfall Data ◽  
Coefficient Of Determination ◽  
Data Sets ◽  
Good Precision ◽  
Alternative Source

Long-term rainfall data with good spatial and temporal distribution is essential for all climate-related analyses. The availability of observed rainfall data has become increasingly problematic over the years due to a limited and deteriorating rainfall station network, occasioned by limited reporting and/or quality control of rainfall and, in some cases, closure of these stations. Remotely sensed satellite-based rainfall data sets offer an alternative source of information. In this study, daily and monthly rainfall data derived from Climate Hazards Group InfraRed Precipitation (CHIRPS) is compared with observed rainfall data from 46 stations evenly distributed across South Africa. Various metrics, based on a pairwise comparison between the observed and CHIRPS data, were applied to evaluate CHIRPS performance in the estimation of daily and monthly rainfall. The results show that CHIRPS data correlate well with observed monthly rainfall data for all stations used, having an average coefficient of determination of 0.6 and bias of 0.95. This study concludes that monthly CHIRPS data corresponds well, with good precision and relatively little bias when compared to observed monthly rainfall data, and can therefore be considered for use in conjunction with observed rainfall data where no or limited data is available in South Africa for hydrological analysis.

scholarly journals QSPR model for the forecast of dynamic viscosity of arenas by the topological characteristics of molecules

2020 ◽  
Vol 62 (6) ◽  
pp. 1-6
Author(s):  
Mikhail Yu. Dolomatov ◽  
◽  
Timur M. Aubekerov ◽  
Oleg S. Koledin ◽  
Ella A. Kovaleva ◽  
...  
Keyword(s):  
Dynamic Viscosity ◽  
Wiener Index ◽  
Test Sample ◽  
Coefficient Of Determination ◽  
Saturated Hydrocarbons ◽  
Qspr Model ◽  
Proposed Model ◽  
Chemical Factors ◽  
Topological Characteristics

Prediction of the dynamic viscosity of saturated hydrocarbons vapors is an important step in the calculation of various processes and apparatuses in chemical technology. In order to quickly determine the dynamic viscosity without resorting to the use of expensive equipment, methods of mathematical modeling are currently used. To predict the dynamic viscosity of saturated arenas vapors, a nonlinear multivariate regression model QSPR is proposed. The model associates with a dynamic viscosity a set of descriptors – the topological characteristics of molecular graphs: the Randic index, the Wiener index, and also the functions of the eigenvalues of the topological matrix of the molecule, which reflect the main structural and chemical factors, such as branching, length of the carbon skeleton and energy parameters of molecules, for example, Hückel’s perturbation spectrum of molecules, as well as affecting dynamic viscosity. The objects of research used arenas. The studied sample included 40 hydrocarbons of a number of arenas. The proposed model adequately describes the dynamic viscosity of saturated arenas vapors. The coefficient of determination of the model is 0.986. The average absolute and relative error for the test sample of HF is -2.46⋅10-7 cP and 1.83%, respectively. The model is applicable for engineering and scientific forecasts of the dynamic viscosity of various saturated arenas vapors.

scholarly journals Deep Learning-Based Optimal Smart Shoes Sensor Selection for Energy Expenditure and Heart Rate Estimation

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7058
Author(s):  
Heesang Eom ◽  
Jongryun Roh ◽  
Yuli Sun Hariyani ◽  
Suwhan Baek ◽  
Sukho Lee ◽  
...  
Keyword(s):  
Heart Rate ◽  
Deep Learning ◽  
Energy Expenditure ◽  
Mean Squared Error ◽  
Pressure Sensors ◽  
Absolute Error ◽  
Coefficient Of Determination ◽  
Proposed Model ◽  
Point Pressure

Wearable technologies are known to improve our quality of life. Among the various wearable devices, shoes are non-intrusive, lightweight, and can be used for outdoor activities. In this study, we estimated the energy consumption and heart rate in an environment (i.e., running on a treadmill) using smart shoes equipped with triaxial acceleration, triaxial gyroscope, and four-point pressure sensors. The proposed model uses the latest deep learning architecture which does not require any separate preprocessing. Moreover, it is possible to select the optimal sensor using a channel-wise attention mechanism to weigh the sensors depending on their contributions to the estimation of energy expenditure (EE) and heart rate (HR). The performance of the proposed model was evaluated using the root mean squared error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). Moreover, the RMSE was 1.05 ± 0.15, MAE 0.83 ± 0.12 and R2 0.922 ± 0.005 in EE estimation. On the other hand, and RMSE was 7.87 ± 1.12, MAE 6.21 ± 0.86, and R2 0.897 ± 0.017 in HR estimation. In both estimations, the most effective sensor was the z axis of the accelerometer and gyroscope sensors. Through these results, it is demonstrated that the proposed model could contribute to the improvement of the performance of both EE and HR estimations by effectively selecting the optimal sensors during the active movements of participants.

scholarly journals Analisis Faktor-faktor yang Mempengaruhi Produktivitas Kerja Karyawan di PT. Multi Terminal Indonesia

2021 ◽  
Vol 23 (2) ◽  
pp. 167-178
Author(s):  
Retno Ayu Hastuti ◽  
Tri Bodroastuti ◽  
Tantri Widiastuti
Keyword(s):  
Regression Analysis ◽  
Linear Regression Analysis ◽  
Work Productivity ◽  
Multiple Linear Regression Analysis ◽  
Analytical Tool ◽  
Coefficient Of Determination ◽  
Research Model ◽  
And Behavior ◽  
Attitudes And Behavior

Work productivity is the ability to carry out activities that produce an output or work in accordance with the quality set, but often there are obstacles that cause the company's goals to be less achieved. Every company has a different policy on efficient sourcing. The purpose of this study was to determine and analyze how the effect of knowledge, skills, abilities, attitudes and behavior on work productivity of PT. Multi Terminal Indonesia. The population in this study were 30 employees and the entire population was sampled. The analytical tool used in this research was Multiple Linear Regression Analysis. The results showed that knowledge (X1), skills (X2), abilities (X3), behaviors (X5) had no effect on work productivity. The attitude (X4) had an effect on work productivity. The results of simultaneous hypothesis testing explained that knowledge (X1), skills (X2), abilities (X3), attitudes (X4) and behavior (X5) haved an effect on work productivity. The coefficient of determination of 0.636 means that knowledge, skills, abilities, attitudes and behavior are able to explain work productivity by 63.6%. The remaining 36.4% is explained by other variables not included in this research model.

scholarly journals An Interpretable Extreme Gradient Boosting Model to Predict Ash Fusion Temperatures

Minerals ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 487
Author(s):  
Maciej Rzychoń ◽  
Alina Żogała ◽  
Leokadia Róg
Keyword(s):  
Coefficient Of Determination ◽  
Gradient Boosting ◽  
Important Indicator ◽  
Upper Silesian Coal Basin ◽  
Proposed Model ◽  
Extreme Gradient Boosting ◽  
The Impact ◽  
Partial Dependence ◽  
Individual Input

The hemispherical temperature (HT) is the most important indicator representing ash fusion temperatures (AFTs) in the Polish industry to assess the suitability of coal for combustion as well as gasification purposes. It is important, for safe operation and energy saving, to know or to be able to predict value of this parameter. In this study a non-linear model predicting the HT value, based on ash oxides content for 360 coal samples from the Upper Silesian Coal Basin, was developed. The proposed model was established using the machine learning method—extreme gradient boosting (XGBoost) regressor. An important feature of models based on the XGBoost algorithm is the ability to determine the impact of individual input parameters on the predicted value using the feature importance (FI) technique. This method allowed the determination of ash oxides having the greatest impact on the projected HT. Then, the partial dependence plots (PDP) technique was used to visualize the effect of individual oxides on the predicted value. The results indicate that proposed model could estimate value of HT with high accuracy. The coefficient of determination (R2) of the prediction has reached satisfactory value of 0.88.

scholarly journals Determination of the Super-Elliptic Shape of Tire-Soil Contact Area Using Image Processing Method

2015 ◽  
Vol 48 (2) ◽  
pp. 5-14
Author(s):  
R. Farrokhi Teimourlou ◽  
H. Taghavifar
Keyword(s):  
Image Processing ◽  
Contact Area ◽  
Block Design ◽  
Processing Method ◽  
Coefficient Of Determination ◽  
Inflation Pressure ◽  
Wheel Load ◽  
Image Processing Method ◽  
Proposed Model

Abstract The present study is aimed at determination of the super-elliptic shape of tire-soil contact area using image processing method. Contact area has a substantial role on determination of soil compaction and tractive parameters of agricultural tractors. A very well-known model in this realm is to describe the contact area with superellipse geometry. A soil bin testing facility equipped with a single-wheel tester was utilized to conduct the needed experiments. The experiments were carried out at three levels of wheel load, three levels of tire inflation pressure with three replicates in a completely randomized block design. Corresponding images were taken for each of the experiments and the images were processed accordingly. The contact length and width were determined using imdistline command in MATLAB commercial software. This experiment was conducted at three levels of wheel load (2, 3, and 4 kN), and three levels of tire inflation pressure (100, 200, and 300 kPa) with three replications. The aforementioned parameters were applied consequently in the superellipse model and the contact area was computed. The obtained results disclosed that increase of wheel load increases the contact area. Contradictory, increment of tire inflation pressure reduces the formed contact area. Additionally, the potential of contact area determination with the proposed model was compared with that of actual values, which denoted coefficient of determination equal to 0.96, which shows the promising ability of the proposed model and the appropriateness of describing contact area with superellipse geometry

scholarly journals PENGARUH IKLAN MEDIA SOSIAL INSTAGRAM DAN CELEBRITY ENDORSER ( SELEBGRAM ) TERHADAP MINAT BELI (studi kasus pada toko online shop Keripik pisang coklat Krispbo.id ).

2020 ◽  
Vol 6 (1) ◽  
pp. 81-97
Author(s):  
Heny Herawati
Keyword(s):  
Social Media ◽  
Regression Analysis ◽  
Purchase Intention ◽  
Coefficient Of Determination ◽  
The Social ◽  
Celebrity Endorser ◽  
Positive Effect ◽  
Celebrity Endorsers

ABSTRAK             Tujuan penelitian ini untuk mendapatkan bukti empiris mengenai “Pengaruh Iklan Media Sosial Instagram, dan celebrity endorser terhadap minat beli konsumen (studi kasus pada toko online shop Keripik pisang coklat Krispbo.id ). Pengujian hipotesis menggunakan analisis regresi berganda . Berdasarkan hasil analisis data dan pembahasan, secara parsial variabel Iklan Media Sosial Instagram (X1) berpengaruh positif teradap minat beli (Y). Variabel celebrity endorser (X2) secara parsial berpengaruh positif terhadap minat beli (Y). Secara simultan iklan media sosial instagram dan celebrity endorser berpengaruh signifikan terhadap minat beli. Koefisien determinasi sebesar 65,2% yang dijelaskan oleh iklan media sosial instagram dan celebrity endorser sedangkan sisanya 34,8%  yang tidak diteliti, seperti harga, kualitas, distribusi dan lain sebagainya.   Kata kunci : Iklan media sosial instagram, celebrity endorser, dan minat beli.   ABSTRACT             The purpose of this study was to obtain empirical "Effect of Instagram Social Media Ads, and celebrity endorser on buying interest online shop consumers (case study on the online shop of Keripik pisang coklat Krispbo.id). Hypothesis testing uses multiple regression analysis. Based on the results of the data analysis and discussion, partially the Social Media Ads variable Instagram (X1) has a positive effect on buying interest (Y). The celebrity endorser (X2) variable partially has a positive effect on buying interest (Y). Simultaneously Instagram social media ads and celebrity endorsers have a significant effect on buying interest. The coefficient of determination of 65.2% is explained by Instagram social media advertisements and celebrity endorsers while the remaining 34.8% is not examined, such as price, quality, distribution etc.   Key words : Instagram Social Media , celebrity endorser and purchase intention.

scholarly journals Pengaruh Motivasi dan Stres Kerja Terhadap Kinerja Karyawan CV. Muslim Galeri Indonesia

2020 ◽  
Vol 3 (2) ◽  
pp. 164-173
Author(s):  
Nina Shabrina ◽  
Darmadi Darmadi ◽  
Ratna Sari
Keyword(s):  
Regression Analysis ◽  
Data Analysis ◽  
Data Collection ◽  
Hypothesis Testing ◽  
Work Environment ◽  
Multiple Regression Analysis ◽  
Employee Performance ◽  
Coefficient Of Determination ◽  
Analysis Techniques

This study aims to determine the effect of the work environment and work discipline both partially and simultaneously on employee performance at PT. Caturkarda Depo Serpong Tangerang Building. The method used in this study uses associative quantitative approach while the sample used in this study were 85 respondents. Data collection techniques by means of questionnaires, data analysis techniques with validity, reliability, classic assumption tests, multiple regression analysis, hypothesis testing, Ftest, Ftest, and coefficient of determination. The results showed that the work environment had a positive and significant effect on employee performance, this can be proven by the regression value of 0.091X1 . Tcount value of 3.086> ttable 1.989 with a significance of 0.003 <0.05. And the coefficient of determination of 28.5%. Work discipline has a positive and significant effect on employee performance, this can be proven by the regression value of 0.173X2 . Tvalue 4.612> ttable 1.989 with a significant 0.000 <0.05. And the coefficient of determination 36.6%. Simultaneously the work environment and work discipline have a positive and significant effect on employee performance. This can be proven by the value of Fcount 31.222> Ftable 3.11 with a significance of 0.000 <0.05 and the Rvalue of the coefficient of determination of 43.2% Abstrak Penelitian ini bertujuan untuk mengetahui pengaruh lingkungan kerja dan disiplin kerja baik secara parsial maupun secara simultan terhadap kinerja karyawan pada PT. Caturkarda Depo Bangunan Serpong Tangerang. Metode yang dipakai dalam penelitian ini menggunakan Asosiatif dengan pendekatan kuantitatif adapun sampel yang digunakan dalam penelitian ini sebanyak 85 responden. Tehnik pengumpulan data dengan cara kuesioner, tehnik analisis data dengan uji validitas, reliabilitas, uji asumsi klasik, analisis regresi berganda, uji hipotesis uji thitung uji F, dan koefisien determinasi. Hasil penelitian menunjukan bahwa lingkungan kerja berpengaruh positif dan signifikan terhadap kinerja karyawan hal ini dapat dibuktikan oleh nilai regresi 0,091X1. Nilai thitung 3,086 > ttabel 1,989 dengan signifikan 0,003 < 0,05. Serta nilai koefisien determinasi sebesar 28,5%. Disiplin kerja berpengaruh positif dan signifikan terhadap kinerja karyawan hal ini dapat dibuktikan oleh nilai regresi 0,173X2. Nilai thitung 4,612 > ttabel 1,989 dengan signifikan 0,000 < 0,05. Serta nilai koefisien determinasi 36,6%. Secara simultan lingkungan kerja dan disiplin kerja berpengaruh positif dan signifikan terhadap kinerja karyawan hal ini dapat dibuktikan oleh nilai Fhitung 31,222 > Ftabel 3,11 dengan siginifikan 0,000 < 0,05 dan nilai R nilai koefisien determinasi sebesar 43,2%. Kata Kunci : Lingkungan Kerja, Disiplin Kerja, Kinerja Karyawan

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