Multiple Linear Regression Techniques Research Articles

The Influence of Advertising, Sales Promotion and Personal Selling Toward Purchasing Decision to Hotel Stay in East Java

This study aims to identify the effect of advertising, sales promotion and personal selling on the decision of guests to stay at a hotel in East Java. Data was collected through questionnaires, observation, documentation and literature review from March to July 2022. Data were analyzed quantitatively using multiple and simple linear regression techniques. The results showed that simultaneously, advertising, sales promotion and personal selling have a significant effect on purchasing decisions. However, partially, the Sales promotion variable has no significant effect, while Advertising and Personal Selling have a significant effect on the guest's decision to stay at Hotel Ilona.

The Effect of Income on Capital Expenditure with Budget Surplus as a Moderating Variable

The realization of capital expenditure of regencies/cities in North Sumatra Province during the 2019-2020 period decreased by more than 25%. Similarly, the realization of local indigenous income (PAD) in the province decreased in 2019-2020 by 4.75%. This decrease is thought to be caused by poor budget planning at the beginning of the budgeting year. This study aims to determine the effect of local income and general allocation funds on capital expenditure moderated by budget surplus in districts/cities in north Sumatra province in 2016-2020. This study uses descriptive quantitative method. The population of this study is all regencies/cities in North Sumatra Province which amounts to 33 regencies/cities. This study used multiple linear regression techniques to determine the influence between research variables. The results showed that local original income had a positive effect on capital expenditure, the general allocation fund had a positive effect on capital expenditure, the budget surplus moderated the effect of local original income on capital expenditure, and the surplus budget moderated the effect of the general allocation fund on district/city capital expenditure in North Sumatra Province 2016-2020. The increase in PAD and DAU will have a positive impact on Capital Expenditure of Regencies/Cities in North Sumatra Province. The increase in PAD and DAU will provide sufficient budget for local governments to finance the necessary development projects. This can have a positive impact, including the availability of sufficient budgets, improving community welfare, increasing economic growth, and increasing regional competitiveness.

Liquidity on Banks Performance with Corporate Governance as a Moderating Variable (Indonesia Pandemic Covid-19 Evidence)

The Covid-19 pandemic requires prudence, especially in the ratio of credit or liquidity in the banking sector and the role and supervision through the implementation of good corporate governance is required intensively to go through dynamic policy changes. This study aims to examine the effect of liquidity on bank performance and examine the effect of liquidity on bank performance after being moderated by good corporate governance. The research methodology uses multiple linear regression techniques using SPSS 25 software, with the research sample being the conventional banking sector listed on the Indonesia Stock Exchange in 2019-2021 totaling 111 research samples. The results showed that liquidity had no effect on bank performance with the significant value 0.491>0.05. Corporate governance moderated the negative effect of liquidity on bank performance with the significant value 0.028< 0,05 and coefficient -0.786.

Aboveground biomass estimation in dry forest in northeastern Brazil using metrics extracted from sentinel-2 data: Comparing parametric and non-parametric estimation methods

Caatinga is a dry forest, which occupies almost one million square kilometers in the Brazilian territory, representing more than 11% of the territory. However because of the extensive areas to be inventoried and the difficulties in collecting data from this natural vegetation using traditional techniques, the operation becomes very costly, often resulting in low sampling intensity owing to cost and time constraints. Therefore, remote sensing tools have become very useful for minimizing the difficulties caused by traditional methods. Given this context, our study aims to evaluate the performance of spectral and texture variables extracted from an MSI/Sentinel-2 image in the estimation and mapping of AGB in a fragment (natural vegetation area) of Caatinga vegetation in northeastern Brazil. The original reflectance values, the ratio between spectral bands, vegetation indices, texture metrics (extracted from the 3 × 3, 5 × 5, 7 × 7, and 9 × 9-pixel windows), and fraction images (proportion of the vegetation, soil, and shadow/water components) were associated with AGB. These variables were derived from a forest inventory with systematic sampling composed of 40 plots of 900 m2 each. We evaluated the estimates using a parametric model of multiple linear regression (MLR) and a non-parametric model of an artificial neural network (ANN). The texture metrics (angular second moment, correlation, entropy, and contrast), extracted in a 7 × 7-pixel window, were the best predictors. The parametric model was the most accurate for AGB estimation. The MLR and ANN techniques showed bias validation of 2.58% and 2.79%, and relative root mean square errors of 12.02% and 16.60%, respectively. AGB estimates ranged from 1.49 Mg ha−1 to approximately 73 Mg ha−1 on the MLR and ANN maps. The textural metrics showed the potential to accurately predict AGB, providing valuable information for the use of open access data. Such information is very useful in the management of natural resources in large areas, such as the Caatinga vegetation. The use of optical data for AGB estimation in the region is relatively unexplored and this study contributes to filling that gap or better understand their application for deriving AGB in a dry forest in the semiarid region of Sergipe.

Pengaruh Keamanan, Kualitas Informasi dan Kemudahan terhadap Keputusan Pembelian Online pada Konsumen Tiktok Shop

This study is entitled the effect of security, information quality and convenience on online purchasing decisions for tiktok shop consumers which aims to determine how security, information quality and convenience affect online purchasing decisions partially or simultaneously. The data collection method used is the simple random sampling method, namely people who have shopped at tiktokshop. Data collection using a questionnaire, namely by distributing a list of questions using Google Form to respondents randomly to tiktok users. The number of samples taken based on the responses to the incoming questionnaire responses was 148 respondents. Furthermore, the results of the respondents' responses were tabulated and tested for feasibility. The research model that will be used in this study is a regression analysis model to test the proposed hypothesis using Multiple Linear Regression techniques using the SPSS 25.0 programme. The results showed that online purchasing decisions were simultaneously and partially influenced by the variables of security, information quality and ease of tiktok shop consumers in shopping. Keywords: purchase, online, tiktok shop

Analisis Faktor-Faktor Yang Mempengaruhi Struktur Modal Pada Perusahaan Subsektor Makanan Dan Minuman Yang Terdaftar di Bursa Efek Indonesia

This study aims to examine and analyze the factors that influence the capital structure of food and beverage subsector companies listed on the INDONESIA STOCK EXCHANGE. The technique for collecting secondary data obtained from financial data on 22 food and beverage sub-sector companies listed on the Indonesian stock exchange from 2013 to 2020, and the research sample taken is annual data for 8 years. So the amount of data obtained is 176 samples. The results of the study have been tested on classical assumptions such as the assumption of normality, the assumption of multicollinearity and the assumption of hoteroscedasticity. By applying multiple linear regression techniques in the process of analyzing the data. This study aims to examine and analyze the factors that influence the capital structure of food and beverage subsector companies listed on the INDONESIA STOCK EXCHANGE. The technique for collecting secondary data obtained from financial data on 22 food and beverage sub-sector companies listed on the Indonesian stock exchange from 2013 to 2020, and the research sample taken is annual data for 8 years. So the amount of data obtained is 176 samples. The results of the study have been tested on classical assumptions such as the assumption of normality, the assumption of multicollinearity and the assumption of hoteroscedasticity. By applying multiple linear regression techniques in the process of analyzing the data.

THE FACTORS THAT INFLUENCE VISITOR SATISFACTION IN CISAAT TOURISM VILLAGE SUBANG

Tourism significantly contributes to the country's development, especially in economic growth. The tourism industry significantly declined in 2020 when the epidemic occurred, and implemented lockdown procedures worldwide. In Indonesia, tourism contribution decreased by about Rp. 27.5 billion to GDP. This research aims to analyze the factors that influence visitor satisfaction which in this study are seen in the three independent variables that affect the dependent variable. The independent variables in this study are attractiveness, facilities, and accessibility. At the same time, the dependent variable in this research is visitor satisfaction. The research method used in this study is used quantitative methods. The data collection technique was using a questionnaire. Respondents in this study were people who had visited Cisaat village with a minimum of 100 respondents. Questionnaires were distributed, and collected 121 respondents who have been tested with validity and reliability tests before trying data analysis. Based on the results of the validity and reliability tests, it is known that the measuring instrument used in this study is valid and reliable, so it is feasible to use as a measuring tool. Then the data analysis was used using multiple linear regression techniques. The study results showed that the variables of attractiveness, facilities, and accessibility positively and significantly affect visitor satisfaction in the Cisaat tourism village

THE EFFECT OF PRESSURE AND OPPORTUNITY IN DETECTING FINANCIAL STATEMENT FRAUDS IN CONSUMER GOODS INDUSTRY COMPANIES

This study aims to determine the effect of pressure and opportunity in detecting fraud in the financial statements of companies in the consumer goods industry sector which are listed on the Indonesia Stock Exchange. This study uses quantitative data obtained from annual reports of companies that have been audited during the study period. The population of this study is the consumer goods industry with a population of 63 companies, using a porposive sampling technique, the number of companies that meet the sample criteria is 22 companies. The analysis technique used is multiple linear regression technique using the Common Model Effect (CEM) approach to panel data. The results of this study found that Financial Stability, Financial Target and Ineffective Monitoring had a positive and significant effect on the detection of fraud in the financial statements of companies in the consumer goods industry sector which were listed on the Indonesia Stock Exchange. Whereas External Pressure has a negative and insignificant effect on the detection of fraud in the financial statements of companies in the consumer goods industry sector that are listed on the Indonesia Stock Exchange.

THE ROLE OF COVID-19 MEDIA EXPOSURE TO PANIC BUYING WITH ANXIETY AS MEDIATOR

Media exposure to traumatic event can cause anxiety. One of the actions taken during COVID-19 to reduce anxiety is panic buying behavior. This study aims to determine the role of media exposure related to COVID-19 on panic buying with coronavirus anxiety as a mediator. This research is conducted in Jabodetabek from September 2021 to April 2022. The population in this study was emerging adulthood (18-25 years old) with a sample of 397 people. Sampling is done by sharing questionnaires using google form through social media. Data analysis uses multiple linear regression techniques. The results showed that most of the respondents were female (58.7%), aged 21 years (43.8%), had a final high school/vocational/equivalent education (66.2%), domiciled in Jakarta (55.2%), had no history of COVID-19 (72.5%), had a family with a history of COVID-19 (51.1%). Based on the results of the main data analysis, it was found that participants in this study had low levels of media exposure, coronavirus anxiety, and panic buying. The results of the analysis showed that there was a significant and positive partial mediation role between media exposure to panic buying with coronavirus anxiety as a mediator variable. It can be concluded that excessive media exposure related to COVID-19 can increase coronavirus anxiety and trigger the emergence of panic buying behavior. Therefore, the government or information spreaders can pay more attention to the spread of valid information to prevent the emergence of panic from rumors and false information.

LinVec: A Stacked Ensemble Machine Learning Architecture for Analysis and Forecasting of Time-Series Data

Objectives: The proposed work integrates multiple Machine Learning approaches in a single model to be used for the analysis and forecasting of Time Series data. Methods: In the present work, the concept of Stacked Ensemble learning is proposed that uses Multiple Linear Regression and Support Vector Regression techniques as the base models. A Meta Model is constructed based on Multiple Linear Regression with necessary modifications. The outputs from the base models are fed into the meta-model which is mended with the capability of combining the predictions from the two base models to produce better results than the individual constituent parts, after running a k-fold training procedure. Findings: The proposed model is capable of analyzing and predicting any Time Series data. In the present study, stock data of six companies enlisted in the National Stock Exchange of India are analyzed for the prediction of the next day’s Open, High, and Low prices. The proposed work achieves better accuracy and reduces the error in prediction when compared to similar works done in the same field. Novelty: The amalgamated technique used in this work can be considered as a generalization of the stacked ensemble method in a broader aspect. The proposed model combines the strengths of multiple Machine Learning methods into a single model to achieve better performance than its individual counterparts. Further, several recent works have tried to predict only the next day’s Open and Closing Prices of stocks, but for an intraday trader, prediction of the next day’s Low and High prices of a stock are more significant than the closing prices. Very few works have predicted all of the Open, High and Low prices in a single study, our present work achieved this quite successfully. Keywords: Machine Learning; Stacked Ensemble Model; Support Vector Regression; Multiple Linear Regression; Time Series data analysis; Stock Price Prediction

THE EFFECT OF RELIGIOSITY AND LOVE OF MONEY ON ACCOUNTANT ETHICS CRISIS

The problem in this study is that there are still violations of accountant ethics committed by accountants when carrying out their duties as an accountant. As a profession that carries out its functions, accountants must comply with professional ethics and carry out their duties in a certain way in accordance with professional ethics or established standards. Behavior that violates professional ethics is not only for public accountants, but also for government accountants and management accountants. If the accountant has the integrity to apply ethical and ethical values in the professional behavior of his work, then there should be no unethical behavior. The purpose of this study was to determine the effect of religiosity and love of money on accountants' ethical crisis. The sample used was determined by the purposive sampling method with certain criteria. Data analysis in this study used multiple linear regression and data collection techniques in this study in the form of a questionnaire. The data obtained were analyzed using the f test, t test, normality test, and multiple linear regression analysis. The results showed that religiosity and love of money simultaneously affected the ethical crisis of accountants. Partially, the religiosity variable has no effect on the accountant's ethical crisis, and love of money also has no effect on the accountant's ethical crisis.Keywords: Accountant Ethics Crisis, Love of Money, Religiosity

PENGARUH MINAT BELAJAR DAN SEMANGAT BELAJAR SISWA MTS NEGERI TERHADAP HASIL BELAJAR BACA AL-QUR’AN DI KABUPATEN KAMPAR

This research aims to find out the effect of learning interest and learning spirit on the learning outcomes of Al-Qur’an reading. The type of this research was field research with quantitative approach. The samples of this research were students of State Islamic Junior High School in Kampar Regency in the amount of 93 students. The data collection techniques used were questionnaire, documentation, and interview. Data analysis in this research used Multiple Linear Regression Technique. The results of this research show that: 1) the learning interest has significant effect on Al-Qur’an reading learning outcomes of State Islamic Junior High School students in Kampar Regency. This was proved by the result of t test where tcount is bigger than ttable namely 7,792 > 1,987, with significant value 0,00 < 0,05 and contributes 40%; 2) learning spirit has significant effect on Al-Qur’an reading learning outcomes of State Islamic Junior High School Students in Kampar Regency. This was proven by the result of t test, where tcount is bigger than ttable namely 12,134 > 1,987, with significance value 0,00 < 0,05 and contributes 61.8%; 3) learning interest and learning spirit altogether have significant effect on Al-Qur’an reading learning result of State Islamic Junior High School Students in Kampar Regency. This was proven by the result of Fcount bigger than Ftable namely 75,140 > value of F table 0,310 and contribute 62.50%. TRANSLATE with x EnglishArabicHebrewPolishBulgarianHindiPortugueseCatalanHmong DawRomanianChinese SimplifiedHungarianRussianChinese TraditionalIndonesianSlovakCzechItalianSlovenianDanishJapaneseSpanishDutchKlingonSwedishEnglishKoreanThaiEstonianLatvianTurkishFinnishLithuanianUkrainianFrenchMalayUrduGermanMalteseVietnameseGreekNorwegianWelshHaitian CreolePersian // TRANSLATE with COPY THE URL BELOW Back EMBED THE SNIPPET BELOW IN YOUR SITE Enable collaborative features and customize widget: Bing Webmaster PortalBack// This page is in Japanese Translate to English AfrikaansAlbanianAmharicArabicArmenianAzerbaijaniBengaliBulgarianCatalanCroatianCzechDanishDutchEnglishEstonianFinnishFrenchGermanGreekGujaratiHaitian CreoleHebrewHindiHungarianIcelandicIndonesianItalianJapaneseKannadaKazakhKhmerKoreanKurdish (Kurmanji)LaoLatvianLithuanianMalagasyMalayMalayalamMalteseMaoriMarathiMyanmar (Burmese)NepaliNorwegianPashtoPersianPolishPortuguesePunjabiRomanianRussianSamoanSimplified ChineseSlovakSlovenianSpanishSwedishTamilTeluguThaiTraditional ChineseTurkishUkrainianUrduVietnameseWelsh Always translate Japanese to EnglishPRO Never translate Japanese Never translate ejournal.uin-suska.ac.id

Determinasi Kepuasan Kerja dan Implikasinya terhadap Turnover Intention: Studi pada PT Hayati Pratama Mandiri Padang

<em>This study aims to determine the effect of work environment and financial compensation on turnover intention which is mediated by job satisfaction at PT Hayati Pratama Mandiri Padang, West Sumatera. The method used in this research is quantitative-descriptive. This study uses primary data collected through a questionnaire instrument from 60 permanent employees of PT Hayati Pratama Mandiri Padang. Data analysis in this study used multiple linear regression techniques to find the effect of independent variables on the dependent and path analysis to examine the effect of intermediary variables. Data analysis in this study used the help of the Statistical Product and Service Solution (SPSS) version 21. The results of this study indicate that the work environment has a significant and positive effect on job satisfaction, while financial compensation has no significant effect on job satisfaction. The opposite result was also obtained, i.e. the work environment did not have a significant effect on turnover intention, while financial compensation had a significant effect on turnover intention. Furthermore, job satisfaction does not have a significant effect on turnover intention. This study also proves that work environment and financial compensation have a significant effect on job satisfaction simultaneously. In line with these results, the work environment, financial compensation, and job satisfaction have a significant effect on turnover intention simultaneously. This study also confirms that job satisfaction is able to mediate the effect of the work environment on turnover intention. However, job satisfaction is not able to mediate the effect of financial compensation on turnover intention</em>.

An Integrated Approach to Reservoir Characterization for Evaluating Shale Productivity of Duvernary Shale: Insights from Multiple Linear Regression

In the development of unconventional shale resources, production forecasts are fraught with uncertainty, especially in the absence of a full, multi-data study of reservoir characterization. To forecast Duvernay shale gas production in the vicinity of Fox Creek, Alberta, the multi-scale experimental findings are thoroughly evaluated. The relationship between shale gas production and reservoir parameters is assessed using multiple linear regression (MLR). Three hundred and five core samples from fifteen wells were later examined using the MLR technique to discover the fundamental controlling characteristics of shale potential. Quartz, clay, and calcite were found to comprise the bulk of the Duvernay shale. The average values for the effective porosity and permeability were 3.96% and 137.2 nD, respectively, whereas the average amount of total organic carbon (TOC) was 3.86%. The examined Duvernay shale was predominantly deposited in a gas-generating timeframe. As input parameters, the MLR method calculated the components governing shale productivity, including the production index (PI), gas saturation (Sg), clay content (Vcl), effective porosity (F), total organic carbon (TOC), brittleness index (BI), and brittle mineral content (BMC) (BMC). Shale gas output was accurately predicted using the MLR-based prediction model. This research may be extended to other shale reservoirs to aid in the selection of optimal well sites, resulting in the effective development of shale resources.

Prediction model for the compressive strength of green concrete using cement kiln dust and fly ash

Integrating artificial intelligence and green concrete in the construction industry is a challenge that can help to move towards sustainable construction. Therefore, this research aims to predict the compressive strength of green concrete that includes a ratio of cement kiln dust (CKD) and fly ash (FA), then recommend the optimum sustainable mixture design. The artificial neural network (ANN) and multiple linear regression techniques are used to build prediction models and statistics using MATLAB and IBM SPSS software. The input parameters are based on 156 data points of concrete components and compressive strengths that are collected from the literature. The developed models have been trained, validated, and tested for each technique. TOPSIS method is used to assign the optimum mixture design according to three sustainable criteria: compressive strength, carbon dioxide (CO2) emission, and cost. The results of ANN models showed a better prediction of the compressive strength with regression (R) equal to 0.928 and 0.986. The optimum mixture includes CKD 10–20% and FA 0–30%. Predicting the compressive strength of green concrete is a non-destructive approach that has sustainable returns including preservation of natural resources, reduction of greenhouse gas emissions, cost, time, and waste to landfill as well as saving energy.

Pengaruh Akuntabilitas, Transparansi, dan Partisipasi Masyarakat Terhadap Pengelolaan Alokasi Dana Desa Studi Kasus Pada Pemerintah Desa Kecamatan Gantarang Kab.Bulukumba Provinsi Sulawesi Selatan

This study was conducted to determine whether accountability, transparency and community participation have an influence on the Gantarang District Village Government in 2020 either simultaneously or partially. This study uses multiple linear regression techniques. This research is included in descriptive research and is a clause in nature. The population in this study is the Village Government of Gantarang District. Sampling in this study used a non-probability sampling technique with a saturated sampling method so that 90 respondents were obtained from all village officials in the Gantarang District Village Government. The results of the study show that simultaneously accountability, transparency, and community participation affect the management of village fund allocations in the Gantarang District Village Government in 2020. While partially shows that accountability, transparency, and community participation have a significant positive effect on the management of village fund allocations in Gantarang District Village Government in 2020

Audit Forensik, Audit Investigasi, dan Profesionalisme Terhadap Pengungkapan Kecurangan di BPKP

The research objective is to obtain empirical evidence of the effect of disclosing fraud on forensic auditing, investigative auditing and professionalism. The research was conducted at BPKP Bali Province. The number of samples used were 37 samples with purposive sampling method. The research instrument used was a questionnaire. The collected data were analyzed using multiple linear regression techniques. The results showed that the forensic audit had no effect on disclosing fraud, while the investigative audit and professionalism had a positive effect on disclosing fraud. The implications of this research are able to confirm the theory of fraud triangle and Theory of Planned Behavior (TPB) which argue that behavior does not only depend on a person's intentions, but also on other factors that are not under the control of the individual's behavior that causes fraud or fraud.
 Keywords: Forensic Audit; Investigative Audit; Professionalism; Fraud Disclosure

Pedestrian Gap Acceptance Behavioral Modelling at Midblock and Uncontrolled Intersections

Pedestrian safety is one of the major concerns and pedestrian gap acceptance (PGA) behaviour depends on various characteristics of pedestrians, vehicles, geometry and environment. This study is intended to develop PGA models at various pedestrian crossing locations (mid-blocks and uncontrolled intersections). Video graphic data was collected from four different pedestrian crossing locations and extracted the required data from videos manually. The multiple linear regression (MLR) technique was used to model the pedestrian gap acceptance behaviour by the vehicular gap size accepted by the pedestrians. MLR models reveal that the frequency of attempts significantly affects the PGA behaviour only in the case of mid-blocks whereas the frequency of disturbances significantly affects only in the case of intersections. The statistical results showed that the pedestrian road crossing behaviour depends on the type of crossing location also. The results can be used to analyse the pedestrian safety levels at various crossing locations.

Mapping clay mineral types using easily accessible data and machine learning techniques in a scarce data region: A case study in a semi-arid area in Iran

Understanding the abundance variability of clay minerals, as fundamental soil components, will help the users to improve land management and address concerns over climate change and soil fertility. Therefore, this investigation aimed to model the abundance and spatial distribution of clay types, including palygorskite, illite, and kaolinite, and identify the most significant variables affecting their variability using a digital soil mapping (DSM) approach in Darab district, southern Iran. Multiple Linear Regression (MLR) and Random Forest (RF) techniques were applied to link clay types and environmental attributes that were obtained from a Landsat-8 operational land imager (OLI) and digital elevation model (DEM). A ten-fold cross-validation approach was applied to calibrate and validate the models, and 50 bootstrap models were used to quantify the prediction uncertainty. The models accuracy was defined by the coefficient of determination (R2), root mean square error (RMSE), and the ratio of performance to the interquartile range (RPIQ). Findings denoted that the RF model better predicts the abundance and variability of clay minerals in the study area (R2 = 0.56, 0.47, and 0.48, RMSE = 5.3, 1.91 and 0.63 % and RPIQ = 2.82, 3.28 and 2.62 for palygorskite, illite and kaolinite, respectively). Based on the feature selection analysis, topographic covariates and soil properties determined palygorskite and kaolinite content variations, while for illite, only soil properties could explain the spatial distribution. Besides, the RF produced a lower uncertainty for palygorskite compared to the other clay types. The present research can provide new insight into the spatial variability of clay minerals in arid and semi-arid regions of Iran that could be extended to other similar environments. Moreover, the results showed that the easily available environmental variables could provide reliable predictions. However, other environmental covariates, such as XRF analysis, Vis-NIR, and MIR spectroscopy, are also recommended as input variables for further studies.

Pengaruh Persepsi, Pengetahuan Akuntansi Syariah, dan Religiusitas terhadap Minat Mahasiswa Akuntansi Berkarir di Lembaga Keuangan Syariah

This research explore the impact of Shariah calculations, implications and knowledge on professional interests in Shariah financial institutions. The sample in this study is students who have taken sharia accounting courses. The type of research used in this study is quantitative approach using primary data. Primary data was obtained by distributing questionnaire directly to 100 respondents. The data was the analyzed using multiple linear regression techniques. The results of this study are (1) perception (2) Sharia accounting knowledge (3) religiosity on the interest of accounting students for a career in Sharia financial institutions.