Multiple Linear Regression Method Research Articles

Quantifying the effects of diffuse photosynthetically active radiation on water use efficiency in different ecosystems

Compared with direct radiation, diffuse radiation could be more efficiently used for photosynthesis because of the diffuse fertilization effect (DFE). Because carbon uptake and water loss are coupled through leaf stomata, DFE probably increases gross primary productivity (GPP) and evapotranspiration (ET) simultaneously. Multi-year eddy covariance flux observation data and simulated diffuse fraction of photosynthetically active radiation (PAR) for nine ecosystems across China (containing forest, grassland, wetland, and cropland) were used to quantify the impact of DFE on water use efficiency (WUE). The results showed that GPP firstly increased and then decreased with increasing diffuse fraction of PAR (kd-PAR = diffuse PAR/PAR) for each ecosystems. The kd-PAR values at which maximum GPP occurred varied between 0.34 and 0.76 across nine ecosystems. ET decreased with increasing kd-PAR in most ecosystems mainly because high kd-PAR (indicating low PAR) could reduce evaporation in most ecosystems. The relationships between WUE and kd-PAR were significantly linear with averaged slopes of forest, grassland, wetland, and cropland of 1.64, 0.96, 1.19, and 4.51 g C kg−1 H2O, respectively. A multiple linear regression method was used to analyze the effect of diffuse PAR (PARdif) and direct PAR (PARdir) on GPP and ET. The conversion efficiencies for PARdif were greater than for PARdir, and the relative differences were 178.35% and 23.77% for GPP and ET, respectively. The intensity of DFE for GPP and ET were greater for forest and cropland than for grassland and wetland. The intensity of DFE was 3.05 to 236.96 times higher for GPP than for ET. The mathematical analysis results demonstrated that the promoting effect of PARdif was greater for GPP than for ET, thereby inducing an increase in WUE with increasing kd-PAR. These results will be helpful for improving modeling accuracy of carbon and water cycles under the conditions accompanying global climate change.

Environmental aging influence on mechanical properties of additive manufactured polyamide parts: A statistical approach

AbstractThis study explores the influence of environmental factors and printing orientation on the aging of additive manufactured polyamide 12 (PA12). A multifactorial experimental design was employed to age specimens under controlled conditions. Analysis of variance revealed that temperature, irradiance, relative humidity, and time significantly impact the ultimate tensile strength (UTS) and Young's modulus (Y) of PA12. Applying multiple linear regression methods produced predictive models with R2 values of 0.9075 for the UTS and 0.5226 for the Y, indicating substantial explanatory power for the specimen's UTS. These models enhance understanding of PA12 aging, aiding in the design of more durable mechanical parts for applications exposed to environmental conditions, such as footwear, automotive components, and medical devices. As next steps, future research could empirically deploy these developed predictive models and explore longer time scales to further elucidate the long‐term aging behavior of additively manufactured PA12.

The Effect of Digital Marketing, Word of Mouth, Brand Trust and Image on the Purchase Decision

Social media has become a very important tool in the business world, especially in marketing activities. One strategy that is often used is Social Media Marketing, which aims to introduce products or services, provide and share information, and increase sales at a relatively low cost. With these benefits, this study aims to measure the role of digital marketing, word of mouth, product trust, and brand image on purchasing decisions, especially on the Es Teh Indonesia brand. This study was conducted using a purposive sampling approach, where data was collected boldly from people around the Surakarta area. The data obtained were then analyzed using multiple linear regression methods, with the help of SPSS software. The results of the analysis showed that each variable tested, namely digital marketing, word of mouth, product trust, and brand image, had a positive influence on the final customer purchasing decision. This finding emphasizes the importance of digital marketing strategies and word of mouth in shaping product trust and brand image, which ultimately encourages consumers to make purchases. This conclusion provides insight for companies to focus on developing effective marketing strategies to improve purchasing decisions

The Influence of Service Quality and Social Media on Blood Donation Interest in Indonesian Red Cross South Sulawesi Province

The Indonesian Red Cross (PMI) is the only organization that has the authority to provide blood transfusion services. In 2021, the number of donors at the Indonesian Red Cross Blood Donation Unit, South Sulawesi Province, was 10,265 people, with 2,168 people taking blood from activities inside the building or around 21% and taking blood outside the building as many as 8,097 or around 79% (UDD PMI South Sulawesi Province, 2021) of the total population in South Sulawesi which reached 8,956,181 people, this proves that interest in blood donation is low (BPS, 2021). The demand for blood for blood transfusions is increasing. The minimum need for blood in Indonesia has reached around 5.1 million bags per year or 2% of the population, (WHO 2016). The Indonesian Red Cross Blood Donor Unit for South Sulawesi Province has not been able to meet the target of voluntary blood donations in accordance with the World Health Organization (WHO) requirement for voluntary donors of at least 2% of the population. This research aims to analyzing the influence of service quality and social media on interested in donating blood. The novelty of this research of Service Quality and Social Media on Interest in Blood Donation in the Indonesian Red Cross Blood Donation Unit, South Sulawesi Province in 2022. Using quantitative descriptive research using a questionnaire instrument with multiple linear regression method. The Service Quality and Social Media has a positive and significant effect on Interest in Blood Donation at UDD PMI South Sulawesi Province. Limitations of research is not measured from the many existing social media so it cannot be known which ones contributed the most of donors

Mediasi Trust Dalam Mempengaruhi Pemasaran Media Sosial Terhadap Niat Beli Konsumen (Studi Konsumen Muna Beauty Store)

This study aims to determine Trust mediation in influencing Social Media Marketing on consumer purchase intentions (study on Muna Beauty Store consumers). The method used in this research is purposive sampling, namely the technique of determining the sample by considering certain criteria with a total sample of 96 respondents. With multiple linear regression and analysis method. The results of this study indicate that 1) Social Media Marketing has a positive and significant direct effect on Trust at Muna Beauty Store. 2) Social Media Marketing has a direct significant positive effect on Consumer Purchase Intentions at Muna Beauty Store. 3) Trust has a significant positive direct effect on the Purchase Intention of Muna Beauty Store Consumers. 4) Social Media Marketing indirectly has a positive and significant effect on Consumer Purchase Intentions through Trust.

Pengaruh Profitabilitas, Kepemilikan Manajerial, Ukuran Perusahaan dan Leverage terhadap Nilai Perusahaan

This research aims to determine the effect of Profitability, Managerial Ownership, Company Size and Leverage on Company Value in the food and beverage sub-sector listed on the Indonesia Stock Exchange for the 2019–2023 period. The sample for this research is 24 companies in the food and beverage sub-sector listed on the Indonesia Stock Exchange for the 2019-2023 period. This research was carried out using the multiple linear regression method assisted by the SPSS version 22.0 program and Microsoft Excel 2010. The results of the research show that Profitability has an effect on Company Value, Managerial Ownership has no effect on Company Value, Company Size has a negative effect on Company Value, Leverage has an effect on Company Value.

Pengaruh Content Marketing dan Influencer Marketing terhadap Keputusan Pembelian Handphone Vivo: Studi Kasus Konsumen Handphone Vivo Kota Bengkulu

This research aims to determine the influence of content marketing and influencer marketing on Vivo cellphone purchasing decisions (case study of Vivo cellphone consumers in the city of Bengkulu). This research is quantitative research, the object of this research is Vivo cellphone consumers in the city of Bengkulu with a sample of 96 respondents, using a purposive sampling technique. Data was collected through questionnaires and analyzed using the multiple linear regression method. Based on the results of multiple linear regression, the regression equation Y = = 4.468 + 0.267 (X1) + 0.570 (X2) is obtained. The results of the hypothesis test show that content marketing has a significant influence on the decision to purchase a Vivo cellphone, with a significant level (0.007 < 0.050), and influencer marketing has a significant influence on the decision to purchase a Vivo cellphone, with a significant level (0.000 < 0.050), testing the hypothesis test f shows that content marketing and influencer marketing have a significant influence on Vivo cellphone purchasing decisions at a significant level (0.000 < 0.050). .This means that the results of the t test analysis state that the results are significant for all variables and the hypothesis is accepted. The results of multiple regression analysis also show a coefficient of determination of 0.432, which means that the content marketing and influencer marketing variables influence consumer purchasing decisions by 43.2%, while 56.8% is influenced by other variables not observed in this research.

Pengaruh leverage, intensitas modal, dan intensitas persediaan terhadap tarif pajak efektif pada perusahaan manufaktur yang terdaftar di Bursa Efek Indonesia Tahun 2019-2022

This research study investigates the effective tax rates. It aims to provide empirical evidence of the impact of leverage, capital, and inventory intensity on the effective tax rate. The study uses specific selection criteria to focus on manufacturing companies listed on the Indonesia Stock Exchange from 2019 to 2022. A total of sixty-eight companies were chosen as samples through purposive sampling. The samples were then analyzed and tested using the multiple linear regression method. The study results indicate that the leverage variable affects the effective tax rate. At the same time, capital intensity does not affect the effective tax rate. On the other hand, inventory intensity has also been proven to affect the company's effective tax rate. Public interest statements Investors should consider various financial ratios to maximize profits. This study's findings can provide guidance for making informed decisions. Companies should prioritize factors that attract investor interest and ensure accurate completion of financial reports. The study's results can help them better understand these factors. Future researchers should consider adjusting variables to improve the effectiveness of the tax rate. The study's findings can serve as a starting point for their research.

Mechanical mechanism analysis of rockburst in deep-buried tunnel with high in-situ stress

The Qinling water conveyance tunnel has a large buried depth and high in-situ stress level, and rockburst disasters frequently occurred during excavation. In order to find out the mechanical mechanism of rockburst, the research work in this paper is as follows: (1) In-situ three-dimensional hydraulic fracturing method was used to measure the in-situ stress of the deep buried tunnel crossing the ridge. (2) Based on the measured in-situ stress results, the stress distribution characteristics of the tunnel crossing the ridge were obtained by the multiple linear regression method, and the rockburst tendency during construction was predicted. (3) A three-dimensional numerical model of tunnel excavation was established to analyze the dynamic adjustment characteristics of the surrounding rock stress and elastic strain energy during TBM excavation, and to clarify the mechanical mechanism of rockburst. The research results show that the maximum principal stress of the deep-buried tunnel crossing the ridge of Qinling is 40–66 MPa, which belongs to extremely high in-situ stress level, and medium-strong rockburst may occur during excavation. In the process of TBM excavation, the stress of the surrounding rock in the range of 2.6 times the diameter of the tunnel before and after the working face is adjusted violently, and the concentrated zones after the stress redistribution are mainly distributed in the arch roof and arch bottom, and the stress concentration coefficient can reach 2.06. The arch roof, arch waist, and arch bottom are susceptible to immediate rockburst due to stress transient unloading at the moment of excavation. After the elastic strain energy of the surrounding rock at the arch roof and the arch bottom is released and accumulated, it is easy to cause time delayed rockburst, and the depth of the rockburst pit can reach 3.5 m, which is consistent with the rockburst phenomenon in the field.

Pengaruh Current Ratio, Debt to Asset Ratio, dan Total Asset Turn Over terhadap Net Profit Margin

This study aims to determine the effect of Current Ratio, Debt to Asset Ratio and Total Asset Turn Over on Net Profit Margin. The data used in this study is secondary data with a population of retail sub-sector companies listed on the Indonesia Stock Exchange with the observation year 2019 - 2022, totaling 31 companies. The sampling technique used in this study was purposive sampling method with data analysis using multiple linear regression methods and using the Statistical Package for the Social Sciences (SPSS) version 22 program and Microsoft Excel for Windows 2019. The results of this study indicate that Current Ratio, Debt to Asset Ratio and Total Asset Turn Over affected Net Profit Margin with a coefficient of determination (R2) of 83.3% and the rest is influenced by other variables not studied in this study.

Pengaruh Green Accounting, Intellectual Capital terhadap Kinerja Keuangan Perusahaan Sektor Kesehatan di Indonesia

This study's primary goal is to examine how intellectual capital and green accounting affect the financial performance of health sector businesses. The value added intellectual coefficient (VAIC) is used to quantify intellectual capital, and environmental expenses and eco-friendly products are used to measure green accounting. The analyzed data consists of secondary data from the annual reports of healthcare companies listed on the Indonesia Stock Exchange (IDX) for the period from 2019 to 2022. Multiple linear regression method was employed in the data analysis. The study's conclusions suggest that while green products and environmental cost have no effect on a company's financial performance, intellectual capital has a favorable effect on the financial performance of businesses in the health sector. These results underscore the importance of effective management of intellectual capital to enhance financial success in the healthcare sector.

Correlation analysis of occupational stress and metabolic syndrome among employees of a power grid enterprise in China.

Being in a state of high occupational stress may disrupt the metabolic balance of the body, thus increasing the risk of metabolic diseases. However, the evidence about the relationship between occupational stress and metabolic syndrome was limited. To explore the association between occupational stress and metabolic syndrome (MetS) in employees of a power grid enterprise. A total of 1091 employees were recruited from a power grid enterprise in China. Excluding those who failed to complete the questionnaire and those who had incomplete health check-ups, 945 subjects were included in the study. Assessment of occupational stress was used by job demand-control (JDC) and effort-reward imbalance (ERI) questionnaires, respectively. The information on body mass index (BMI), systolic blood pressure (SBP), and diastolic blood pressure (DBP) were collected. The levels of high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), and fasting blood glucose (FBG) in the fasting venous blood samples were measured. Logistic regression analysis and multiple linear regression methods were used to analyze the correlation between JDC and ERI models of occupational stress, metabolic syndrome, and its components, respectively. The prevalence of MetS was 8.4% and 9.9% in JDC and ERI model high occupational stress employees, respectively. ERI model occupational stress and smoking are significantly associated with the risk of MetS. ERI ratio was significantly associated with lower HDL-C levels. Gender, age, marital status, smoking, high-temperature and high-altitude work were significantly associated with metabolic component levels. Our study revealed a high detection rate of occupational stress in both JDC and ERI models among employees of a power grid enterprise. ERI model occupational stress, demanding more attention, was associated with the risk of MetS as well as its components such as HDL-C.

Structure and microwave dielectric characteristics of (Ba,Sr,Ca)HfO3 ceramics

In the present work, the structure and microwave dielectric properties of (Ba,Sr,Ca)HfO3 ceramics were systematically investigated to understand the general mechanism of tuning the temperature coefficient of resonant frequency, τf in perovskite ceramics. Ba1–xSrxHfO3 and Sr1–yCayHfO3 could form continuous solid solutions while the solid solubility of Ca in Ba1–yCayHfO3 was about 20% (in mole). τf changed nonlinearly with increasing tolerance factor as the result of competition between the increase in the restoring force on the ions and the increase in polarizability. Under the guidance of three microscopic mechanisms affecting τf, a preliminary attempt was made to explore the suitable parameters to predict the variation trend of τf. Normalized ionic radii and the τf values of the end members were selected as independent variables, and τf was calculated by using multiple linear regression method. For Ba1–xSrxHfO3 and Sr1–yCayHfO3 with orthorhombic structures, the root mean square error between the calculated and measured τf was only 6.8×10–6 °C–1. The good agreement between the calculated τf values and the measured ones in Ba1–x–ySrxCayHfO3 ceramics confirmed its validity where three elements jointly occupy A-site, but it only works when there is no structural phase transition. Progresses in this research field would not only deepen our understanding of mechanism of regulating properties in multi-ion solid solutions, but also boost the developments of closely related fields such as machine learning-assisted design and high-entropy ceramics. Finally, a good combination of microwave dielectric properties was achieved in Sr0.15Ca0.85Hf0.96Ti0.040O3: εr = 27.8, Qf = 36,470 GHz, τf = +5×10–6 °C–1.

Enhancing Nursing Competence in China: The Interplay of Resilience, Mindfulness and Social Support

ObjectivesTo address the nursing crisis, it is imperative to comprehend the factors that influence nursing competencies, which are crucial for the delivery of quality patient care. BackgroundFacing demographic shifts and increasingly complex healthcare demands, China's nursing sector struggles with workforce shortages and the need to enhance core competencies. This research explores the interplay of social support, psychological resilience, mindfulness and nursing competencies in various hospital environments in China. MethodsThrough a cross-sectional survey, 941 nurses across tertiary, secondary and private healthcare settings completed self-assessment questionnaires. The analysis included multiple linear regression and comparative methods to assess how psychological resilience, mindfulness and social support have an impact on nursing competencies. ResultsFindings revealed a strong relationship between psychological resilience and nursing competencies, with resilience being a key predictor. Mindfulness and social support also significantly contributed to competency levels. Nurses in tertiary hospitals showed greater competencies than those in secondary or private facilities. ConclusionEnhancing nursing competencies requires targeted interventions focusing on professional development and supportive workplace cultures. Incorporating psychological resilience, social support and mindfulness into nurse training is crucial for improving practice and policy.

Combining Bourgoyne and Young Equations by Bagging Tree Regression to Predict Rate of Penetration in a Southern Iraqi Field, Case Study

Abstract Achieving an accurate and optimal rate of penetration (ROP) is critical for a cost-effective and safe drilling operation. While different techniques have been used to achieve this goal, each approach has limitations, prompting researchers to seek solutions. This study’s objective is to conduct the strategy of combining the Bourgoyne and Young (BYM) ROP equations with Bagging Tree regression in a southern Iraqi field. Although BYM equations are commonly used and widespread to estimate drilling rates, they need more specific drilling parameters to capture different ROP complexities. The Bagging Tree algorithm, a random forest variant, addresses these limitations by blending domain knowledge and capturing non-linear relationships. Its ensemble nature also mitigates the impact of outliers. This approach combines physics-based equations with machine learning to enable more accurate ROP predictions in drilling operations. It enhances drilling efficiency, reduces expenses, and improves decision-making in the oil and gas sector. Extensive testing on actual drilling datasets has demonstrated outstanding performance compared to the multiple linear regression (MLR) method. With the increased R2 and zero P-value. positive findings show that this tool can benefit precise future ROP prediction in southern Iraqi oil well drilling.

Prediction of the level of crime cases using multiple linear regression in the city of Pontianak

This study aims to develop a predictive model for the crime rate in the Police Resort Area of Kota (POLRESTA) Pontianak using the Multiple Linear Regression method based on secondary data obtained from the Criminal Investigation Unit of POLRESTA Pontianak. The utilization of descriptive statistical techniques and data visualization aids in identifying relevant features that enrich the information within the model. The evaluation results indicate that this model performs well in both modeling and predicting crime rates in Kota Pontianak. Despite the variations in error rates between training and testing data, the model still demonstrates its proficiency in predicting known data. The testing results also reveal that the Mean Absolute Percentage Error (MAPE) values for each crime category exhibit variations in the testing dataset, with MAPE for "Berat" increasing to 12.91%, MAPE for "Sedang" increasing to 30.11%, and MAPE for "Ringan" increasing to 26.59%. Consequently, this study concludes that the Multiple Linear Regression method holds potential as an effective tool for decision-making and the development of strategies to combat criminal activities in Kota Pontianak

Influence of a Meandering Channel on the Threshold of Sediment

River meanders and channel curvatures play a significant role in sediment motion, making it crucial to predict incipient sediment motion for effective river restoration projects. This study utilized an artificial intelligence method, multiple linear regression (MLR), to investigate the impact of channel curvature on sediment incipient motion at a 180-degree bend. We analyzed 42 velocity profiles for flow depths of 13, 15, and 17 cm in a laboratory flume. The results indicate that the velocity distribution was influenced by the sediment movement threshold conditions due to channel curvature, creating a distinct convex shape based on the bend’s position and flow characteristics. Reynolds stress distribution was concave in the upstream bend and convex in the downstream bend, underscoring the bend’s impact on incipient motion. Bed Reynolds stress was highest in the first half of the bend (0 to 90 degrees) and lowest in the second half (90 to 180 degrees). The critical Shields parameter at the bend was approximately 8–61% lower than the values suggested by the Shields diagram, decreasing from 0.042 at the beginning to 0.016 at the end of the bend. Furthermore, our findings suggest that the MLR method does not significantly enhance the understanding of sediment movement, highlighting the need for a more comprehensive physical rationale and an expanded dataset for studying sediment dynamics in curved channels.

The Influence of Technology Literacy and the Use of Artificial Intelligence (AI) By Hasanuddin University Students on the Change of Habits in Completing Academic Tasks

With the rapid advancement of technology and the integration of artificial intelligence in various aspects of life, students' approach to academic tasks is evolving. This study aims to analyze the effect of using AI on changes in habits in completing academic assignments. The type of research used is descriptive quantitative with multiple Linear Regression method. In this study, the sample was drawn with cluster random sampling of 400 people who had used AI which was divided into 16 faculties at Hasanuddin University. The data collection method in this study uses a questionnaire distributed online via kuesio.id which contains statements, interviews and documentation by searching the internet. In testing data analysis techniques, namely validity and reliability tests calculated using the SPSS (Statistical Product and Service Solutions) program with Cronbach Alpha (α) above 0.60, so the overall statement is declared reliable. The results of this study indicate that the literacy level of Hasanuddin University students is categorized as good with a respondent achievement rate (TCR) of 78.3% and the use of AI that is often used from the 15 applications listed by researchers, namely ChatGPT by 26.7%, Perplexity 12.7%, and Grammarly 12.6%. The results of data analysis show that there is a positive correlation between technological literacy and the ability to use AI with changes in habits in completing academic tasks. Students who have high literacy and are skilled in utilizing AI tend to be more efficient and effective in completing their tasks.

Pengaruh Kompetensi dan Lingkungan Kerja terhadap Kinerja Pegawai

The study of employee performance continues to be a major focus of human resource experts and practitioners. Various influential factors have been analyzed in relation to efforts to improve performance. Various aspects have been explored, both from the organizational and individual side, with various perspectives resulting in diverse findings. The focus of the study aimed to understand the impact of competencies and working conditions on employee outcomes. The approach in the study uses quantitative correlation which examines cause-and-effect relationships. The study population consisted of 96 employees of the Maluku Province Bawaslu, which was also used as the research sample (saturated sample). The instrument used has gone through validity and reliability testing, which then the data is analyzed using multiple linear regression methods. The study findings show that competence and work environment have a positive and significant impact on employee performance. This suggests that employees who are more competent and work in better working conditions tend to have better performance. The path analysis and discussion conducted in the study also supported these findings, concluding that competence working conditions have a positive and meaningful impact on employee performance, thus reinforcing the conclusion that these two factors are important in improving employee performance.

Estimasi Laju Pertumbuhan Penduduk menggunakan Metode Regresi Linier Berganda di Kabupaten Batang

Population growth in an area is very important for development and as a benchmark for development and progress. One way to estimate/estimate population growth is to use Data Mining techniques. Data mining is able to analyze data into information. This research will discuss the population growth of Batang Regency, Central Java in 2024. The estimation technique that will be used is Multiple Linear Regression. This method was chosen because it can make estimates/predictions by utilizing past data regarding population growth so that it can produce a relationship pattern. This Multiple Linear Regression method aims to produce the best predictions. The research data used is population data in Batang Regency in 2019-2023. Based on research that has been carried out, the results show a population growth of 853,800 people in 2024. This figure shows a population increase of 24,917 people compared to 2023 of 828,883 people with an increase percentage of 3%. The benefits of this research can be conveyed to the Batang Regency Government as material for decision and policy making in the year.