Multiple Linear Regression Method Research Articles

Machine Learning for the Model Prediction of Final Semester Assessment (FSA) using the Multiple Linear Regression Method

Corona virus (COVID-19) is the reason behind the collapse of the National Assembly. The first is the Final Semester Assessment (FSA) , which is a component of the student's graduation. The aforementioned evaluation process is a crucial consideration for the teacher since it uses several intricate surveys and mark components. A prediction model is employed to assist teachers in providing suitable results for student learning. The method that is used is called the multiple linear regression. This multiple linear regression algorithm yields an accuracy level of approximately 92%. The analysis results using the method are used as a guide to understanding student’s index. This index is a rating that appears based on the Minimum Credit Count (MCC). Therefore, the goal of this study is to determine students' understanding of the FSA prediction value, which will be taken into consideration through the results of the MCC weights in the form of a range in the form of "Grade." Additionally, the research aims to determine the accuracy of the results from the model obtained using multiple linear regression algorithms in predicting students' FSA.

Experimental road safety study of the actual driver reaction to the street ads using eye tracking, multiple linear regression and decision trees methods

The article describes the results of a naturalistic driving study done in Kuwait performed by 34 participants wearing a mobile eye tracker to monitor the effect of roadside advertisements on user attention. Eye-tracking (fixations) are the main dependent variable and examined as a function of driving/roadside characteristics, particularly billboards, speed, and so forth. The results obtained were analyzed using traditional statistics (ANOVA test and multiple linear regression) and machine learning (decision tree estimation methods). From the results, it was found that road advertisements negatively affect driver attention and thus road safety. How the level of safety varies with the type and size of advertisement was also investigated. As a consequence, all of the estimates revealed that different aspects of advertising have a detrimental impact on drivers' behavior, and that the duration of fixation and the rate of acceleration before viewing an ad are impacted by advertising type and size, respectively.

The Effect of Work Motivation and Work Discipline on Employee Performance of PT Yangtze Optical Fibre Indonesia

This study aims to determine the effect of work motivation and work discipline on the performance of PT. Yangtze Optical Fiber Indonesia. Data were collected through observation and questionnaires with 52 final respondents. This study used multiple linear regression method to analyze the data. The results of the analysis prove that partially, work motivation does not affect employee performance, while partially work discipline affects employee performance. Similarly, simultaneously work motivation and work discipline have a significant effect on employee performance. This research can be useful for PT. Yangtze Optical Fiber Indonesia, where to improve employee performance, companies must pay attention to work discipline factors, especially, and work motivation.

The correlation between autumnal landscape colors and environmental factors and the analysis of ecological service functions in subtropical urban scenic forests

Background and objectivesUrban scenic forests are a main component of forest parks, and a quantitative study of the landscape color of urban scenic forests can provide a scientific reference for the planning of forest parks and the design of scenic forest management measures. The purpose of the study is to find the quantitative correlation between autumn landscape color and ecological service functions and to obtain the important influencing factors.Materials and methodsThis study focuses on Purple Mountain National Forest Park in Nanjing as a case study area and uses forest resource survey data from Purple Mountain National Forest Park in 2020, autumn landscape color photograph data from Purple Mountain National Forest Park in 2020, and digital elevation model data as the main information sources. The correlation between two ecological functions of above-ground biomass (AGB), tree species diversity (TSD), and influencing factors (including color factors, stand factors, and terrain factors) were both analyzed by Pearson correlation analysis. Then, multiple linear regression (MLR) and random forest (RF) methods were used to perform the quantitative relationship between the functions.ResultsThe results show that, in the established quantitative models of AGB, with TSD as the dependent variable, the correlation coefficients of the MLR model are both above 0.784, while the correlation coefficients of the RF model are all above 0.872. Moreover, the brightness value of the main color (BRI), the number of yellow-green blocks (NYG), and the number of yellow blocks (NY) have important effects on the two ecological service functions.ConclusionIn conclusion, there are complex non-linear relationships between the ecological service functions of AGB, TSD, and influencing factors, and the landscape color can reflect the ecological function of the scenic forest to some extent. In addition, stand factors and color factors have important effects on the ecological function of AGB. Color factors and terrain factors have important effects on the ecological function of TSD. BRI, NYG, and NY have important effects on the two ecological functions. Finally, this quantitative method has universal applicability in the temperate zone, warm temperate zone, and subtropical zone of China.

Neural critic learning with accelerated value iteration for nonlinear model predictive control

In practical industrial processes, the receding optimization solution of nonlinear model predictive control (NMPC) is always a very knotty problem. Based on adaptive dynamic programming, the accelerated value iteration predictive control (AVI-PC) algorithm is developed in this paper. Integrating iteration learning with the receding horizon mechanism of NMPC, a novel receding optimization solution pattern is exploited to resolve the optimal control law in each prediction horizon. Besides, the basic architecture and the specific form of the AVI-PC algorithm are demonstrated, including the relationship among the iterative learning process, the prediction process, and the control process. On this basis, the convergence and admissibility conditions are established, and the relevant properties are comprehensively analyzed when the accelerated factor satisfies the established conditions. Furthermore, the accelerated value iterative function is approximated through the single critic network constructed by utilizing the multiple linear regression method. Finally, the plentiful simulation experiments are conducted from various perspectives to verify the effectiveness and progressiveness of the AVI-PC algorithm.

Determinants of Customer Satisfaction in Chatbot Use

Chatbots are becoming increasingly popular in business due to their ability to deliver immediate responses to customers. However, there is limited empirical evidence focusing on customers’ perspectives. This study aims to investigate the determinants of customer satisfaction in chatbot use as well as provide an overview of chatbot users in Indonesia. The research uses quantitative methods and descriptive types of research, with the number of samples being 150 chatbot users. All data collected met the criteria for validity and reliability and were analyzed descriptively and quantitatively through multiple linear regression methods. The research showed that most of the respondents were male chatbot users, aged 18–29 years, had last used chatbots between 1–3 months ago, and used chatbots to convey their complaints/problems. It is also known that banking chatbots are the most frequently used chatbots. Additionally, perceived usefulness and perceived ease of use are the determinants of customer satisfaction in chatbot use. Of these two factors, perceived usefulness has a dominant influence on chatbot consumer (user) satisfaction in Indonesia.

Assessing microbial stability and predicting biogas production in full-scale thermophilic dry methane fermentation of municipal solid waste

Compared to typical anaerobic digestion processes, little is known about both sludge microbial compositions and biogas production models for full-scale dry methane fermentation treating municipal solid waste (MSW). The anaerobic sludge composed of one major hydrogenotrophic methanogen (Methanoculleus) and syntrophic acetate oxidizing bacteria (e.g., Caldicoprobacter), besides enrichment of MSW degraders such as Clostridia. The core population remained phylogenetically unchanged during the fermentation process, regardless of amounts of MSW supplied (∼35 ton/d) or biogas produced (∼12000 Nm3/d). Based on the correlations observed between feed amounts of MSW from 6 days in advance to the current day and biogas output (the strongest correlation: r = 0.77), the best multiple linear regression (MLR) model incorporating the temperature factor was developed with a good prediction for validation data (R2 = 0.975). The proposed simple MLR method with only data on the feedstock amounts will help decision-making processes to prevent low-efficient biogas production.

The Effect of Discipline and Work Motivation on Employee Performance at PT Yala Kharisma Shipping, Palembang

This study aims to explore the impact of work discipline and work motivation on employee performance at PT Yala Kharisma Shipping Palembang Branch. Data was collected through observation and distributing questionnaires to 40 respondents. Data analysis used multiple linear regression methods. The results of the analysis show that individually, both work discipline and work motivation have a significant influence on employee performance. In addition, together, the two factors also have a significant effect on employee performance. This research provides implications for PT Yala Kharisma Shipping Palembang Branch, that to improve employee performance, companies must pay attention to both work discipline and work motivation.

Professional attractiveness among long-term care workers in nursing homes in China: a cross-sectional study

BackgroundThe population aging trend and the shortage of elderly care workers require the long-term care profession to become more attractive. However, the professional attractiveness among long-term care workers has yet to be extensively studied. This study aims to identify the factors that influence the attractiveness of the long-term care profession for nursing home (NH) care workers..MethodsA cross-sectional study was conducted in more than 50 NHs. Perception of professional attractiveness among long-term care workers and potential associated factors were measured using the Attractive Work Questionnaire (AWQ) and structural instruments including the Fraboni Scale of Ageism (FSA) and the Maslach Burnout Inventory (MBI). A multiple linear regression method was employed to explore the influence of potential independent variables on professional attractiveness.ResultsThe overall response rate was 99%. The results showed the score of professional attractiveness (185.37 ± 20.034), as well as the scores of each component (99.26 ± 11.258 for work condition, 30.13 ± 3.583 for work content, and 55.99 ± 7.074 for job satisfaction). Findings of multiple linear regression analysis indicated that age(β = 0.129, p<.05), years of work(β = 0.156, p<.05), 12-hour shifts(β = 0.185, p<.05), and training times per year(β = 0.148, p<.05) positively associated with long-term care workers perceived professional attractiveness. Whereas only ageism(β=-0.267, p<.05) significantly and negatively influenced professional attractiveness.ConclusionsThe perceived professional attractiveness of long-term care workers in NHs was acceptable. Age, years of work, shifts, training opportunities, and ageism contributed to the professional attractiveness of nursing home care workers in China. Target intervention measures should be taken to enhance the attractiveness of long-term care careers so as to avoid the shortage of long-term care workers.

Dynamics Power Quality Cost Assessment Based on a Gradient Descent Method

The escalating demand for power load is increasingly prone to triggering power quality (PQ) issues, leading to severe economic losses. Aiming at reducing the economic losses, this paper focuses on the coordinated relationship between PQ and economic costs. Firstly, a multilayer multiple linear stepwise regression method is employed to screen PQ indicators, identifying harmonic and voltage deviation as the primary influencing factors of PQ. Secondly, a gradient descent optimization algorithm based on the Least Absolute Shrinkage and Selection Operator (LASSO) is proposed, enabling rapid computation of the minimum PQ cost. Finally, through validations of two case studies, the results confirm that the proposed method can rapidly calculate the minimum PQ cost based on real-time load demands, enabling the dynamic adjustment of PQ cost to meet the evolving needs of power system development.

Analysis of the Correlation between Corporate Dividend Policy and Stock Price

Based on the basic premise and assumption of building a multiple linear regression model and the correlation theory between corporate dividend policy and stock price, this paper adopts the multiple linear regression method of cross-section data to analyze the correlation between corporate dividend policy and stock price of 1458 enterprises from Choice financial terminal after strictly eliminating outliers. It is concluded that the significant positive correlation between dividend per share and stock price is stronger than that between fundamental indicators such as company total market value, return on equity, turnover rate of trading indicators and dividend distribution ratio and stock price, respectively. It is concluded that dividend distribution ratio is helpful to stabilize stock price fluctuations and improve investor return mechanism is beneficial to the healthy development of A-share market.

FS-WOA-stacking: A novel ensemble model for early diagnosis of breast cancer

In this paper, a new integrated scheme is proposed to accurately predict breast cancer, help doctors make early diagnosis and treatment plans, and improve the prognosis of patients. We selects five mainstream machine learning models: support vector machine (SVM), artificial neural network (ANN), random forest (RF), extreme gradient boosting (XGBoost) and adaptive boosting (AdaBoost). The Wisconsin Breast Cancer Database (WBCD) and Wisconsin Diagnostic Breast Cancer (WDBC) are used as datasets to investigate the predictive performance of these single and ensemble models. Then, we use multiple linear regression method for feature selection (FS), the experimental results show that the change of feature subset will significantly affect the performance of the model. The recall and f1-score of the five models are improved by 1.19% and 0.84% on average. After that, we apply whale optimization algorithm (WOA) to optimize the hyperparameters of the model to improve their prediction performance. In the best-case scenario, the model demonstrated improvements of 1.02% in accuracy and 1.82% in precision. In addition, we ensemble these models by stacking, investigate the performance changes of the ensemble model when different models are used as meta learners. Finally, the FS-WOA-Stacking model achieves 99.56% accuracy on WBCD and 99.65% accuracy on WDBC. Compared with the existing breast cancer prediction models, the performance of the proposed model is at an excellent level.

Pengaruh Modal Sendiri, Total Aset, Volume Usaha, Jumlah Anggota dan Modal Luar terhadap Sisa Hasil Usaha Koperasi Simpan Pinjam

This research aims to determine the influence of own capital, total assets, business volume, members and outside capital on the remaining business results in Savings and Loans Cooperatives. Sampling in this research used a purposive sampling method by analyzing 32 cooperatives from 83 Savings and Loans Cooperatives in Banyumas Regency from 2019-2022. Data analysis was carried out using the multiple linear regression method. The results of this research show that the variables of own capital, business volume, have a positive and significant effect on the remaining business results, while the variables total assets, members, external capital do not have a significant effect on the remaining business results. The research results showethat own capital is a variable that has a relatively large influence on the remaining business results, so it is best for savings and loan cooperatives to maintain the condition of their own capital structure, and try to develop their members so that members increase the amount of principal savings and mandatory savings, so that they can increase their own capital.

COST ANALYSIS OF SUSPENSION BRIDGE CONSTRUCTION IN KALIMANTAN BARAT PROVINCE

The successful implementation of a job begins with the determination of a reliable estimation value. One of the models used in determining the estimated value of a job, using data from the cost budget plan (RAB) on work that has been carried out, is the Cost Significant Model. In this study, the data used were five suspension bridge construction jobs starting from 2018 to 2022. the data obtained from the RAB is processed into independent variables and dependent variables, which are then tested using multiple linear regression methods using the SPSS application. Based on the results of the analysis, the influential variables are X2, namely Bridge Oprit Work; X4, namely Upper Building Work (Transportation and Installation of Truss Bridges); and X5, namely Lower Building Work (Angkur Block Work, Pyilon Foundations, Wind Ties) with a total weight of 85.30%. By using the equation Y = -21,640,343,680,000 + (1,856,843,372 x X2) + (453,953,095 x X4) + (41,965,201,370 x X5), the maximum value of 62.21% and minimum value of -98.05% are obtained, so it falls into the Class 5 category. Class 5 has an accuracy value ranging from +30% to +100%, so it is estimated that it is feasible to use it to carry out the initial concept screening estimation.

Ultrasonic non-destructive inspection method for glass fibre reinforcement polymer (GFRP) hull plates considering design and construction characteristics

The design and construction characteristics, including glass fibre weight fraction ( Gc), number of single-ply layers, fabric combination, and fabrication quality, of glass fibre reinforcement polymer (GFRP) hull plates affect ultrasound propagation characteristics, such as ultrasonic velocity and attenuation, thereby influencing the accuracy of ultrasonic non-destructive test results. Therefore, this study is to propose a method to decrease the ultrasonic test errors of GFRP hull plate by using statistical method. The GFRP specimens with Gc of approximately 30–50 wt%, thicknesses of approximately 5–20 mm, and different fabric combinations were prepared using the hand lay-up method, considering the general design–construction characteristics. Further, an ultrasonic velocity decision method for ultrasonic inspection was proposed considering the GFRP hull design-construction characteristics, such as Gc and number of single-ply layers of hull plate by multiple linear regression method. The results show that the proposed method can reduce the thickness measurement error from approximately 20%–30% to 1%–2%, compared to an existing ultrasonic inspection method, only considering the Gc effect on ultrasonic velocity, which indicates that the proposed test method is suitable for practical applications.

Pengaruh Beban Kerja, Disiplin Kerja Dan Kepuasan Kerja Terhadap Kinerja Karyawan Pada PT Volex

This study aims to analyze the effect of workload, work discipline, and job satisfaction on employee performance at PT Volex. The type of research used is descriptive with a quantitative approach. The population used is all employees who work as production operators in the ICA department at PT Volex in 2023 with a total of 112 employees with sampling based on saturated sampling, using a questionnaire distributed to PT Volex employees. The collected data were analyzed using multiple linear regression methods which were tested involving data quality tests, classic assumption tests, influence tests and hypothesis tests, to determine the effect of workload, work discipline, and job satisfaction variables on employee performance. Findings in multiple linear regression analysis can show that workload has a positive relationship with a magnitude of 26.2% on employee performance. Work discipline has a positive relationship with a magnitude of 21.2% on employee performance. Job satisfaction has a positive relationship with a magnitude of 34.1% on employee performance. The findings of the analysis of the coefficient of determination (R2) that the level of employee performance can be explained by workload, work discipline and job satisfaction of 72.5%. The research results in the hypothesis testing carried out can show that workload, work discipline and job satisfaction partially or simultaneously can provide a positive and significant relationship to employee performance.

PENGARUH DIGITALISASI DAN KEPEMIMPINAN TRANSFORMASIONAL TERHADAP KINERJA KARYAWAN BAGIAN OPERASIONAL PADA PT BANK CAPITAL INDONESIA

The Influence of Digitalization and Transformational Leadership on the Performance of Operational Employees at PT Bank Capital Indonesia. The purpose of this study is to determine the influence of Digitalization and Transformational Leadership on the performance of operational employees at PT Bank Capital Indonesia. The respondents in this study amounted to 50. The data analysis in this research is quantitative, using simple linear regression and multiple linear regression methods. The data were analyzed using SPSS version 25. Based on the results of this study, it is shown that Digitalization affects the performance of operational employees at PT Bank Capital Indonesia. Transformational Leadership influences the performance of operational employees at PT Bank Capital Indonesia. Simultaneously, the variables of Digitalization and Transformational Leadership significantly influence the variable of operational employee performance at PT Bank Capital Indonesia. The R Square value is 0.609 or 60.9%, meaning that the variable of employee performance is influenced by digitalization and transformational leadership, while the remaining 39.1% is influenced by other factors not used in this study.

Factors Predicting Singers’ Work Efficiency and Singers’ Singing Peak

Abstract The research focusses on understanding the controls and predicting singers’ work efficiency, which is measured by rework times (RwT) in the recording studios. We conducted a comprehensive literature synthesis to identify a set of nine critical factors combining advancements in both acoustic field and recording practice. We measured each of these potential variables while 10 individual singers performed the same original song independently. The pieces of music sentences (n = 380) were analyzed by the multiple linear regression method. We found that: In the recording process, the RwT of a singer are predicted mainly by intensity, singing duration (SinD) and rhythm consistency. SinD mediates the connection between intensity and RwT. A singing peak exists in the performance.

The Effect of Capital Structure, Profitability, and Liquidity on Company Value with Company Size as A Moderation Variable

This research aims to test whether the structure of capital, profitability, and liquidity affects the value of the company and whether by adding moderation variables the size of the company can strengthen or weaken independent variables against dependent variables. It is known that the impact of the COVID-19 virus made some banks suffer losses, and others experienced a decrease in profits that lowered the value of the company, one of which is the banking sector. The population used in this study is financial industry companies, namely banking and components which amounted to 34 companies in the period 2020. The analysis method used in this study uses a multiple linear regression method consisting of independent variables of capital structure, profitability, company size, and moderation variables namely company size, as well as dependent variables i.e. company values. Based on the results of the F test it was obtained that all independent variables significantly affect dependent variables. Partially, the results that profitability variables have a significant effect on the value of the company, the size of the company strengthens the influence of profitability on the value of the company, and partially also obtained the result that the variables of capital structure, and liquidity do not significantly affect the value of the company, the size of the company weakens the influence of the capital structure, and liquidity on the value of the company. The purpose of the study is to identify and analyze the effect of three main factors, namely capital structure, profitability, and liquidity, on the value of the company.

Pengaruh Good Corporate Governance Dan Kompetensi Sumber Daya Manusia Terhadap Kualitas Laporan Keuangan

This study aims to test and re-analyze previous researchers between independent variables, namely the variables of transparency, accountability, responsibility, independence, fairness and competence of human resources on the quality of financial reports of Private hospitals in the city of Balnjalrmalsin. The type of data in this study is primarily dental, namely questionnaires distributed to employees of private hospitals in the city of Balnjalrmalsin. The subjects in this study were the director, deputy director, head of finance, and employees of the finance department, totaling 62 people. The method of data analysis was carried out using the multiple linear regression method with the calculation process using the SPSS 22 application program. The results of the study show that transparency, accountability, and human resource competence have significant effects on the quality of financial reports. Responsibility and independence have no effect on the quality of financial reports. Fairness has a negative effect on the quality of financial reports.