Partial Least-squares Analysis Research Articles

Psychological Empowerment, Its Effect On Employee Creativity Through Intrinsic Motivation

Empowerment is the main key to the motivation and productivity of an employee so that they can give maximum contribution to the company. Employee engagement and empowerment direct them to help each other both for themselves, between employees and for the company. The involvement and empowerment of employees are very effective in maintaining high levels of employee motivation. This study aims to determine the effect of psychological empowerment on employee creativity through intrinsic motivation. This study used a quantitative explanatory research approach. This study proposes several hypotheses with a total sample of 105 respondents. Data in this study were collected using a research instrument in the form of a questionnaire and analyzed using the PLS (Partial Least Square) analysis test. The results of this study indicate that psychological empowerment does not directly affect employee creativity. However, psychological empowerment significantly affects employee creativity through intrinsic motivation, and intrinsic motivation mediates the full/perfect mediation effect of psychological empowerment on employee creativity

Covariance patterns between ramus morphology and the rest of the face: A geometric morphometric study

The growth and development of the mandible strongly depend on modeling changes occurring at its ramus. Here, we investigated covariance patterns between the morphology of the ramus and the rest of the face. Lateral cephalograms of 159 adults (55 males and 104 females) with no history of orthodontic treatment were collected. Geometric morphometrics with sliding semi-landmarks was used. The covariance between the ramus and face was investigated using a two-block partial least squares analysis (PLS). Sexual dimorphism and allometry were also assessed. Differences in the divergence of the face and anteroposterior relationship of the jaws accounted for 24.1% and 21.6% of shape variation in the sample, respectively. Shape variation was greater in the sagittal plane for males than for females (30.7% vs. 17.4%), whereas variation in the vertical plane was similar for both sexes (23.7% for males and 25.4% for females). Size-related allometric differences between the sexes accounted for the shape variation to a maximum of 6% regarding the face. Regarding the covariation between the shapes of the ramus and the rest of the face, wider and shorter rami were associated with a decreased lower anterior facial height as well as a prognathic mandible and maxilla (PLS 1, 45.5% of the covariance). Additionally, a more posteriorly inclined ramus in the lower region was correlated with a Class II pattern and flat mandibular plane. The width, height, and inclination of the ramus were correlated with facial shape changes in the vertical and sagittal planes.

Peran Mediasi Inklusi Keuangan pada Literasi Keuangan dan Kinerja UMKM di Kabupaten Deli Serdang

This study aims to determine the mediating role of financial inclusion on the influence of Financial Technology on the performance of MSMEs in Deli Serdang Regency. This study uses an explanatory research approach. The sample of this research is 100 UMKM in Deli Serdang Regency. The sampling technique used was the purposive sampling method. The data analysis used is PLS (Partial Least Square) analysis. Based on the results of the study it can be concluded that: 1) Financial Literacy and Financial Technology have a positive and not significant effect on the performance of MSMEs in Deli Serdang Regency. 2) Financial literacy and Financial Technology have a positive and significant effect on financial inclusion on the performance of MSMEs in Deli Serdang Regency. 3) Financial inclusion has a positive and not significant effect on the performance of MSMEs in Deli Serdang Regency. 4) Financial inclusion does not mediate between Financial Literacy and Financial Technology on the performance of MSMEs in Deli Serdang Regency.

A unified strategy to rebalance multifactorial designs with unequal group sizes: application to analysis of variance multiblock orthogonal partial least squares

BackgroundAdequately handling unbalanced groups remains one of the major challenges for the analysis of multivariate data collected from multifactorial experimental designs. While partial least squares-based methods, such as analysis of variance multiblock orthogonal partial least squares (AMOPLS), can offer better discrimination between factor levels, they can be more heavily affected by this issue, and unbalanced designs of experiments may lead to a substantial confusion of the effects. Even state-of-the-art analysis of variance (ANOVA) decomposition methodologies using general linear models (GLM) lack the ability to efficiently disentangle these sources of variation when combined with AMOPLS. ResultsA versatile solution developed as an extension of a prior rebalancing strategy is proposed for the first decomposition step based on ANOVA. This approach has the advantage of yielding an unbiased estimation of the parameters and retaining the within-group variation in the rebalanced design, while preserving the orthogonality of effect matrices, even in presence of unequal group sizes. This property is of utmost importance for model interpretation because it avoids mixing sources of variation related to the different effects in the design. A real case study involving metabolomic data from in vitro toxicological experiments was used to demonstrate the potential of this strategy to handle unequal group sizes using a supervised approach. Primary 3D rat neural cell cultures were exposed to trimethyltin following a multifactorial design of experiments involving three fixed effect factors. Significance and NoveltyThe rebalancing strategy was demonstrated as a novel and potent solution to handle unbalanced experimental designs by offering unbiased parameter estimators and orthogonal submatrices, thus avoiding confusion of the effects and facilitating model interpretation. Moreover, it can be combined with any multivariate method used for the analysis of high-dimensional data collected from multifactorial designs.

The Influence of Brand Ambassador, Endorsement and Social Media on Consumers’ Buying Interest on The Shopee E-Commerce Platform

The purpose of this study was to determine the effect of Brand Ambassadors, Endorsements and Social Media on Consumer buying Interest on the Shopee E-Commerce Platform. The research sample used 100 respondents who are active users of the Shopee E-Commerce platform in Depok using primary data sources derived from filling out questionnaires and secondary data obtained from previous research, journals, the internet and books. Data analysis used the PLS (Partial Least Square) analysis technique through the SmartPLS software. The results of this study indicate that Brand Ambassadors, Endorsements and Social Media have a positive and significant effect on consumer buying interest on the Shopee E-Commerce platform

The Growth of Social Commerce: How It Is Affected by Users’ Privacy Concerns

Over recent years, social commerce has evolved into a powerful segment of e-commerce, creating new opportunities for brands of all types and sizes. However, if social commerce is to continue to grow and deliver the many benefits it promises, it must address a number of key challenges, including privacy, trust, and ethical concerns. This paper explores the extent to which privacy issues affect the attitudes and behaviours of social media platform (SMP) users towards social commerce, and investigates whether these attitudes and behaviours are a function of cultural context. The approach adopted for the research is a two-stage method, which initially uses semi-structured interviews of social-commerce users to identify their key privacy concerns. These concerns are then used to develop, using the theory of reasoned action (TRA), a structural model that facilitates the formation of hypotheses which relate users’ attitudes to privacy to subsequent behaviour. This model is assessed by analysing the responses to a questionnaire from a large sample of participants. This allows us to evaluate the general accuracy of the model and to compare culturally distinct subgroups (Saudi vs. Chinese) using partial least-squares analysis. Results show good support for all of our hypotheses and indicate that there are clear cultural effects. One of these effects is the inadequacy of privacy policies implemented by SMP providers, regarding culturally specific ethical concerns.

Variation in accuracy of industrially relevant NIR-based multivariate models for sulfur in crude oil and spectral trends during an extended period of time

This study presents a detailed analysis of commercial crude oil partial least square (PLS) predictions of Sulfur based on near-infrared (NIR) spectra over a period of six months, covering hundreds of samples from very diverse crudes. A significant trend in the accuracy of Sulfur predictions is observed when the entire six-month data set is split in approximately monthly subsets. Using the wealth of samples most advantageously, we selected several individual crudes, three heavy and one light, and ran principal component analysis (PCA) of their respective spectra. It is found that for the heavy crudes there is a trend in the spectra that largely overlaps with the observed trend in the Sulfur predictions for those crudes. The one light crude analyzed shows only a weak trend in the raw spectra, which also agrees with the PLS predictions remaining largely unchanged through the inspected six-month time interval for that crude. All the trends identified in PC scores are clearly illustrated in the spectral differences among the pre-treated spectra. The spectral trends are found to partially translate into the trends in predictions of distillation fractions.

Enhancing partial least squares modeling of comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry data by tile-based variance ranking

Chemometric methods like partial least squares (PLS) regression are valuable for correlating sample-based differences hidden in comprehensive two-dimensional gas chromatography (GC × GC) data to independently measured physicochemical properties. Herein, this work establishes the first implementation of tile-based variance ranking as a selective data reduction methodology to improve PLS modeling performance of 58 diverse aerospace fuels. Tile-based variance ranking discovered a total of 521 analytes with a square of the relative standard deviation (RSD2) in signal between 0.07 to 22.84. The goodness-of-fit for the models were determined by their normalized root-mean-square error of cross-validation (NRMSECV) and normalized root-mean-square error of prediction (NRMSEP). PLS models developed for viscosity, hydrogen content, and heat of combustion using all 521 features discovered by tile-based variance ranking had a respective NRMSECV (NRMSEP) equal to 10.5 % (10.2 %), 8.3 % (7.6 %), and 13.1 % (13.5 %). In contrast, use of a single-grid binning scheme, a common data reduction strategy for PLS analysis, resulted in less accurate models for viscosity (NRMSECV = 14.2 %; NRMSEP = 14.3 %), hydrogen content (NRMSECV = 12.1 %; NRMSEP = 11.0 %), and heat of combustion (NRMSECV = 14.4 %; NRMSEP = 13.6 %). Further, the features discovered by tile-based variance ranking can be optimized for each PLS model with RReliefF analysis, a machine learning algorithm. RReliefF feature optimization selected 48, 125, and 172 analytes out of the original 521 discovered by tile-based variance ranking to model viscosity, hydrogen content, and heat of combustion, respectively. The RReliefF optimized features developed highly accurate property-composition models for viscosity (NRMSECV = 7.9 %; NRMSEP = 5.8 %), hydrogen content (NRMSECV = 7.0 %; NRMSEP = 4.9 %), heat of combustion (NRMSECV = 7.9 %; NRMSEP = 8.4 %). This work also demonstrates that processing the chromatograms with a tile-based approach allows the analyst to directly identify the analytes of importance in a PLS model. Coupling tile-based feature selection with PLS analysis allows for deeper understanding in any property-composition study.

Cerebellar and subcortical atrophy contribute to psychiatric symptoms in frontotemporal dementia.

Recent studies have reported early cerebellar and subcortical impact in the disease progression of genetic frontotemporal dementia (FTD) due to microtubule-associated protein tau (MAPT), progranulin (GRN) and chromosome 9 open reading frame 72 (C9orf72). However, the cerebello-subcortical circuitry in FTD has been understudied despite its essential role in cognition and behaviors related to FTD symptomatology. The present study aims to investigate the association between cerebellar and subcortical atrophy, and neuropsychiatric symptoms across genetic mutations. Our study included 983 participants from the Genetic Frontotemporal dementia Initiative including mutation carriers and noncarrier first-degree relatives of known symptomatic carriers. Voxel-wise analysis of the thalamus, striatum, globus pallidus, amygdala, and the cerebellum was performed, and partial least squares analyses (PLS) were used to link morphometry and behavior. In presymptomatic C9orf72 expansion carriers, thalamic atrophy was found compared to noncarriers, suggesting the importance of this structure in FTD prodromes. PLS analyses demonstrated that the cerebello-subcortical circuitry is related to neuropsychiatric symptoms, with significant overlap in brain/behavior patterns, but also specificity for each genetic mutation group. The largest differences were in the cerebellar atrophy (larger extent in C9orf72 expansion group) and more prominent amygdalar volume reduction in the MAPT group. Brain scores in the C9orf72 expansion carriers and MAPT carriers demonstrated covariation patterns concordant with atrophy patterns detectable up to 20 years before expected symptom onset. Overall, these results demonstrated the important role of the subcortical structures in genetic FTD symptom expression, particularly the cerebellum in C9orf72 and the amygdala in MAPTcarriers.

JOB INVOLVEMENT AND JOB RELEVANT INFORMATION IN MODERATING BUDGETING PARTICIPATION ON BUDGETARY SLACK

Budgetary slack frequently happens in local governments. This can also occur due to indications of individual behavior lowering the income target to facilitate the achievement of local government budgets. The purpose of the study was to examine and analyze job involvement and job relevant information moderating budgetary participation on budgetary slack with empirical study on the regency of Sijunjung. The sample of this research is echelon II, III and IV officials in government of Sijunjung Regency. The sampling technique use in this study is a purposive sampling technique. The sample used in this studi were 59 respondents. The analysis of Partial Least Square (PLS) based on variance is the analytical technique used in this research. The results of the study found that budgetary participation has a positive and significant effect on the level of budget slack reduction. Job involvement was not evidenced to moderate the effect of budgetary participation on the level of budget slack reduction while job relevant information was evidenced to moderate the effect of budgetary participation on the level of budget slack reduction and is in quacy moderation. Suggestions for further research should be to examine the entire regional apparatus organization (OPD) in Sijunjung Regency to see budget slack in the budget preparation process and how employee involvement and information can reduce gaps in employee participation in budget preparation. In the participatory budgeting process, the government must consider the factors that influence budget participation, which can have an impact on budgetary slack, such as job involvement and job relevant information.

Evaluating the influence of environmental variables on the length-weight relationship and prediction modelling in flathead grey mullet, Mugil cephalus Linnaeus, 1758.

Fish stocks that are grown under diverse environmental conditions have different biometric relationships and growth patterns. The biometric length-weight relationship (LWR) is an essential fishery assessment tool, as fish growth is continuous and depends on genetic and environmental factors. The present study attempts to understand the LWR of the flathead grey mullet, Mugil cephalus Linnaeus, 1758, from different locations. The study area encompassed its distribution in the wild across freshwater location (one), coastal habitats (eight locations), and estuaries (six locations) in India to determine the relationship between various environmental parameters. Specimens (n = 476) of M. cephalus were collected from commercial catches and the length and weight of individual specimens were recorded. Monthly data from the study locations were extracted for nine environmental variables from the datasets downloaded from the Physical Oceanography Distributed Active Archive Center (PO.DAAC) and the Copernicus Marine Environment Monitoring Service (CMEMS) over 16 years (2002 to 2017) on the Geographical Information System platform. The parameters of the LWR, intercept 'a' and slope or regression coefficient 'b', varied from 0.005321 to 0.22182 and 2.235 to 3.173, respectively. The condition factor ranged from 0.92 to 1.41. The partial least squares (PLS) score scatter plot matrix indicated differences in the environmental variables between the locations. PLS analysis of the regression coefficient and environment parameters revealed that certain environment variables viz., sea surface temperature, salinity, dissolved oxygen, nitrate, and phosphate, played a positive role. However, chlorophyll, pH, silicate, and iron played a negative role in influencing weight growth across various locations. The results revealed that the M. cephalus specimens from three locations, Mandapam, Karwar, and Ratnagiri, possessed significantly higher fitness to their environment than those from the other six locations. The PLS model can be used to predict weight growth under the various environmental conditions of different ecosystems. The three identified locations are useful sites for the mariculture of this species considering their growth performance, the environmental variables, and their interactions. The results of this study will improve the management and conservation of exploited stocks in regions affected by climate change. Our results will also aid in making environment clearance decisions for coastal development projects and will improve the efficiency of mariculture systems.

Common and distinct roles of amygdala subregional functional connectivity in non-motor symptoms of Parkinson’s disease

Neuroimaging studies suggest a pivotal role of amygdala dysfunction in non-motor symptoms (NMS) of Parkinson’s disease (PD). However, the relationship between amygdala subregions (the centromedial (CMA), basolateral (BLA) and superficial amygdala (SFA)) and NMS has not been delineated. We used resting-state functional MRI to examine the PD-related alterations in functional connectivity for amygdala subregions. The left three subregions and right BLA exhibited between-group differences, and were commonly hypo-connected with the frontal, temporal, insular cortex, and putamen in PD. Each subregion displayed distinct hypoconnectivity with the limbic systems. Partial least-squares analysis revealed distinct amygdala subregional involvement in diverse NMS. Hypo-connectivity of all four subregions was associated with emotion, pain, olfaction, and cognition. Hypo-connectivity of the left SFA was associated with sleepiness. Our findings highlight the hypofunction of the amygdala subregions in PD and their preliminary associations with NMS, providing new insights into the pathogenesis of NMS.

Changes in annual transcriptome dynamics of a clone of Japanese cedar (Cryptomeria japonica D. Don) planted under different climate conditions.

Environmental responses are critical for plant growth and survival under different climate conditions. To elucidate the underlying biological mechanisms of environmental responses in Japanese cedar (Cryptomeria japonica D. Don), the annual transcriptome dynamics of common clonal trees (Godai1) planted at three different climate sites (Yamagata, Ibaraki, and Kumamoto Prefectures) were analyzed using microarrays. Both principal component analysis (PCA) and hierarchical clustering of the microarray data indicated the transition to dormant transcriptome status occurred earlier and the transition to active growth status later in the colder region. Interestingly, PCA also indicated that the transcriptomes of trees grown under three different conditions were similar during the growth period (June to September), whereas the transcriptomes differed between sites during the dormant period (January to March). In between-site comparisons, analyses of the annual expression profiles of genes for sites 'Yamagata vs. Kumamoto', 'Yamagata vs. Ibaraki', and 'Ibaraki vs. Kumamoto' identified 1,473, 1,137, and 925 targets exhibiting significantly different expression patterns, respectively. The total of 2,505 targets that exhibited significantly different expression patterns in all three comparisons may play important roles in enabling cuttings to adapt to local environmental conditions. Partial least-squares regression analysis and Pearson correlation coefficient analysis revealed that air temperature and day length were the dominant factors controlling the expression levels of these targets. GO and Pfam enrichment analyses indicated that these targets include genes that may contribute to environmental adaptation, such as genes related to stress and abiotic stimulus responses. This study provided fundamental information regarding transcripts that may play an important role in adaptation to environmental conditions at different planting sites.

Product Quality and Digital Marketing Analysis of Brand Equity through Brand Image of Mesran Super Lubricant Oil in Surabaya

The objectives of this study are: To analyze and determine the effect of Product Quality on Brand equity, To analyze and determine the effect of Digital marketing on Brand equity, To analyze and determine the effect of Product Quality on Brand equity through Brand image and to analyze and determine the effect of Digital marketing on Brand equity through Brand image The population of this study were customers of Mesran Super Lubricating Oil in Surabaya, with the number of samples in this study being 140 respondents (28 x 7). Data analysis was carried out using the Partial Least Square (PLS) method using SmartPLS version 3 software. Based on the test results using PLS analysis, to test the effect of several variables on Brand equity, the following conclusions can be drawn: Based on the test results, it shows that Product Quality has an effect on Brand equity, Based on the test results, it shows that Digital marketing has an effect on Brand equity, Based on the test results show that Product Quality has an effect on Brand equity through Brand image. Based on the test results, it shows that Digital marketing has an effect on Brand equity through Brand image.

The Impact of Acetic Acid on Measuring Ethanol Concentrations in Water and Human Serum Using Short-Wave Infrared Spectroscopy.

Ethanol intoxication, although an elemental part of life in many places around the world, still presents several issues associated with excessive consumption. These issues range from drunk driving, violence, and antisocial behavior to self-harm, all exerting an increased cost on the society. Monitoring of intoxication levels can help to limit the impact of these issues by preventing the use of automobiles or heavy machinery and personal monitoring. Previous works on noninvasive measurement of ethanol tissue concentration for estimation of blood alcohol concentration (BAC) performed worst during the first hour of intoxication. Gas chromatography research of intoxication shows that levels of acetic acid rise together at a similar rate as those of ethanol after initial imbibement. In this research, short-wave infrared (SWIR) spectroscopy was utilized with the aim of establishing the interaction between ethanol and acetic acid in water and serum mixtures. The most consistent and clear correlation between ethanol and acetic acid was recorded at 2262 and 2302 nm wavelengths. Partial least-squares (PLS) analysis indicates that the most effective region for consideration in measurement of ethanol is the therapeutic window four (IV) due to high variance in vibration of carbon bonds. The behavior of spectra at different concentration ranges was examined and described in detail in relation to the consequence of alcohol measurement. The investigation concluded that ethanol shows distinctive regions of absorbance at wavelengths of 2262 and 2302 nm, with variations arising from increasing concentrations of acetic acid, whilst also showing that therapeutic window four is amongst the most influential regions of the spectrum for SWIR.

Early Warning of Abnormal Bridge Frequencies Based on a Local Correlation Model under Multiple Environmental Conditions

The accuracy of frequency prediction is markedly affected by the nonlinearity and model degradation caused by multiple environmental conditions, which may hinder the prediction accuracy and detectability of damage. Therefore, this paper proposes a local correlation model (LCM) between multiorder bridge frequencies and multiple environmental factors for early warning of abnormal frequencies. First, partial least-squares analysis was conducted to extract several environmental principal components sensitive to modal frequencies. The most relevant local data set for each online environmental sample was selected according to similarity measurements based on Euclidean distance metrics. On this basis, more accurate environment–frequency relation models were formed using relatively simple local linear regression models. To filter out the residual environmental variability not suppressed by the LCM and to enlarge slightly abnormal frequency variation, a warning index (i.e., the weighted Mahalanobis distance) was defined using the residual subspatial reconstruction of principal component analysis. Finally, the validity of the proposed method was verified on a cable-stayed bridge. The results show that in contrast to conventional methods, the proposed LCM can accurately describe complicated frequency variations under changing environmental conditions by considering both the nonlinearity of environmental conditions and the time-varying properties of relation models. The detectability of frequency anomalies induced by sudden events can be effectively improved.

FTIR-Based Metabolomics for Characterization of Antioxidant Activity of Different Parts of Sesbania grandiflora Plant

Sesbania grandiflora, one of the flowering plants with great potential as a source of natural antioxidants because it contains chemicals such as tannin, phenolics, and flavonoids. However, there has been no extensive investigation on the antioxidant activity of isolated from different parts of this plant. This study aims to investigate the correlation between antioxidant activity and secondary metabolites extracted from three different parts (leaves, stem barks, and roots) of S. grandiflora plant using Fourier-transform infrared spectroscopy (FTIR) based metabolomics approach. The FTIR is a very useful technique for identifying the functional groups present in the mixtures, while antioxidant assay provides the base to select the part of the plant as the most potential source of antioxidant. The antioxidant properties were determined using 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2'-azino-bis-3-ethylbenzthiazoline-6-sulphonic acid (ABTS), and potassium ferricyanide reduction method. The multivariate data - analyses using Principal Component Analysis (PCA) and Partial Least Square (PLS) were conducted to compare the distribution of metabolites extracted from different parts of the S. grandiflora plant investigated. The PLS was performed to evaluate the relationship between the components of the extracts obtained from different parts of the plant and their antioxidant activities. The results exhibited that antioxidant activities of the extract of the stem barks, and roots are higher than that of the extract of the leaves. Also, the PLS model indicated that the functional group absorption data were significantly correlated with the IC50 values of antioxidant activity. Subsequently, based on the results of PLS ​​analysis displayed that C=C, C=O, and along with C-O functional groups are proposed as the main contributors to the antioxidant activity of the extracts tested. The extracts of different parts were grouped using PCA analysis with a total of principal components (PC) of 94%.

Management Accounting System Dimensions as Mediating The Effect of Decentralization and Environmental Uncertainty on Managerial Performance

This research aims to determine and examine the effect of Decentralization and Environmental Uncertainty on Managerial Performance with the Management Accounting System as Intervening Variables in STARKES Accredited Hospitals in Bandung. The research method used is a combination method: sequential explanatory design. This study uses primary data consisting of questionnaires and interviews. The total population of this study is 11 hospitals. This research is hypothesis testing research. The research model was analyzed using PLS (Partial Least Square) analysis. The analysis results show that the management accounting system can mediate the effect of decentralization on managerial performance, where the company is more decentralized and supported by a high management accounting system, which will produce an adequate managerial performance. In addition, the management accounting system can mediate the effect of environmental Uncertainty on managerial performance. The higher the environmental Uncertainty and supported by the high use of MAS (Management Accounting System), the more adequate managerial performance.

THE INFLUENCE OF ENTREPRENEUR SPIRIT, MOTIVATION AND ORGANIZATIONAL CULTURE ON PERFORMANCE THROUGH THE COMPETENCY OF CIVIL SERVANTS IN TANJUNGPINANG CITY GOVERNMENT

In realizing the achievement of strategic programs, it is necessary to develop the competence of human resources, especially the state civil apparatus. Improving the quality of human resources representing change must not be stagnant, must be on par with the times or even develop beyond the skills and knowledge needed to run a modern government in the future. This means that competency development for state apparatus plays an important role in supporting organizational performance. The purpose of this study was to analyze the influence of the entrepreneurial spirit, motivation and organizational culture on performance through the competence of civil servants in the Government of Tanjungpinang City. Sampling in this study amounted to 150 samples. In this research, the sampling technique used is non-probability sampling with the technique taken is saturated sampling (census). The research method uses an associative method with a quantitative approach to the analysis of Partial Least Square (PLS) analysis techniques with the SmartPLS program. The results of the research on the entrepreneurial spirit variable affect competence. Entrepreneurial spirit does not affect performance. Motivational variables affect competence. Motivational variables affect performance. Organizational culture variables affect competence. Organizational culture variables do not affect performance. Competency variables affect performance. While the indirect relationship Entrepreneurial spirit affects performance with competence as an intervening variable,

FAKTOR-FAKTOR PENENTU DALAM HARGA SAHAM PERUSAHAAN PROPERTI

The goal of this research was to determine if ROA, NPM, and DER play a role in the stock price formation process in the real estate industry from 2017-2021. Inductive, quantitative, and descriptive features all play a role in the research technique. Thirty firms listed in IDX's property sector match the requirements for inclusion in the sample, which was selected using a purposive selection method. Using a Partial Least Squares (PLS) model for data analysis on a Structural Equation Model (SEM). SmartPLS 3.0 was utilized to perform the PLS analysis. Based on the findings of this study, it can be concluded that ROA and NPM have a positive and negative influence on stock prices, respectively, but DER has no effect on stock prices. Rate of return, net profit margin, and dividend yield all have a role in determining stock prices. The corrected R2 value shows that this component explains 15.7% of the variance, while the remaining 84.3% is accounted for by independent variables.