Coefficient Of Determination Values Research Articles

ANALYSIS OF DIVIDENDS, DEBT, AND LIQUIDITY ON MANUFACTURING COMPANY VALUE IN THE COVID PERIOD

Company Value is a comparison between the market value of shares and the book value of the company's equity. The purpose of this study is to determine the effect of Dividends, Debt, and Liquidity on Company Value in manufacturing companies listed on the Indonesia Stock Exchange in 2020-2022. Using a sample of 48 companies and the analysis method using regression analysis with eviews software, it resulted that Dividends had a significant negative effect on Company Value. Debt Policy had a negative but insignificant effect on Company Value and Liquidity had a positive but insignificant effect on Company Value. The determination coefficient value of 75.03% means that the Company Value variable can be explained by the Dividend, Debt and Liquidity variables by 75.03%, while the remaining 24.97% is explained by other variables that affect Company Value. Suggestions that can be given to investors are to pay attention to the Dividend ratio because it affects Company Value, so that investment will be more profitable. For further researchers, take samples from other sectors so that results are obtained that better describe the overall condition of the company.

PENGARUH SERTIFIKASI HALAL DAN BRAND IMAGE TERHADAP KEPUTUSAN PEMBELIAN PADA PRODUK MIXUE DI PALEMBANG

This study aims to analyze the influence of halal certification and brand image on purchasing decisions on Mixue products. This study employs a quantitative methodology. A non-probability purposive sampling method was used to collect samples. This research was conducted by distributing questionnaires to 100 respondents who had purchased Mixue products at least once. The results of the research were carried out using classical assumption tests, which include normality tests, multicollinearity tests, heteroscedasticity tests, multiple linear regression analyses, determination coefficient analyses, t-tests, and F-tests. The results of the research show that, partially, there was a significant influence between halal certification and brand image on purchase decisions. And simultaneously, there is a significant influence between halal certification and brand image on purchasing decisions. The value of the R-squared determination coefficient indicated that the independent variable contributed as much as 66.1% of the dependent variable. Keywords: Halal Certification; Brand Image; Purchase Decision

Comparative Analysis for the Seasonal Variations of the IF2 and T Ionospheric Indices during Solar Cycles 23 and 24

In this work, a comparative analysis for the behavior and pattern of the variations of the IF2 and T Ionospheric indices was conducted for the minimum and maximum years of solar cycles 23 and 24. Also, the correlative relationship between the two ionospheric indices was examined for the seasonal periods spanning from August 1996 to November 2008 for solar cycle 23 and from December 2008 to November 2019 for solar cycle 24. Statistical calculations were performed to compare predicted values with observed values for the selected indices during the tested timeframes. The study's findings revealed that the behavior of the examined indices exhibited almost similar variations throughout the studied timeframe. The seasonal variations were adopted to examine the cross-correlation between the studied indices. The seasonal correlation between tested indices demonstrated that the two indices are highly correlated to each other, with determination coefficient (R2) values ranging from 0.991 to 0.998 during solar cycle 23 and from 0.996 to 0.998 during solar cycle 24. Furthermore, the results of the comparative analytical study revealed that the mathematical correlation equation between the tested indices could be described as a first-order polynomial equation. The proposed mathematical correlation formula for these two indices exhibited a high level of accuracy and good fit between observed values and generated datasets for all seasons during both solar cycles 23 and 24.

A Utilization of Marketing Strategies Through to Increase Sales of Umkm Member Products of The Wijaya Cfd Association In Sampang Regency

UMKM Actors, the use of digital marketing is the most appropriate solution to survive amidst technological developments. Utilization in conducting marketing or online transactions, the approach in this digital era is all technology-based services. One of the emerging technologies is the increasing activity through social networks. This study uses a descriptive quantitative method design, where the results are obtained to obtain information data. The research plan carried out by the researcher aims to find out what promotions are used by the CFD association in Sampang Regency. How social media can increase sales of MSMEs in the CFD Association. The results of the study are: (a) the results of the correlation coefficient test on the Entrepreneurial Characteristics variable (X1) against Business Success (Y) of 0.646; (b) the results of the correlation coefficient test on the Entrepreneurial Competence variable (X2) against Business Success (Y) of 0.734; and (c) Based on the results of data processing in the study, it can be seen that the Adjusted R Square determination coefficient value is 0.627, meaning 62.7% of the success of MSMEs in the CFD Association of Wijaya Regency. Lacquer

Pengaruh Pergaulan Teman Sebaya Terhadap Motivasi Belajar Siswa

This research aimed to determine the influence of peer social interaction on the learning motivation of class VIII students at SMP Negeri 08 Paguyaman, Boalemo Regency. The research approach used in this research was a quantitative approach using descriptive research methods. The data used were primary data obtained from distributing questionnaires to class VIII-1 and class VIII-2 students. The number of samples involved in this research was 40 respondents determined through Purposive Sampling. In the meantime, the data analysis used in this research was simple linear regression analysis with the help of the SPSS 21 program. The research findings confirmed the emergence of a positive and significant influence between peer social interaction and the learning motivation of class VIII students at SMP Negeri 08 Paguyaman, Boalemo Regency. The coefficient of determination value from the regression model previously obtained was 0,720, which indicated that 72% of the variability in student learning motivation could be elucidated by social interactions between peers in the on and off-school area. In other words, the better the relationships students have with their peers, the greater the learning motivation of Class VIII students at SMP Negeri 08 Paguyaman, Boalemo Regency. In the meantime, the remaining value generated or influenced by other variables not examined in this research was 28%.

Analisis Pengaruh desain Produk dan Kualitas Produk terhadap Keputusan Pembelian Motor Honda Beat di Kabupaten Karawang

This study aims to analyze the influence of product design and product quality on purchasing decisions for Honda Beat motorcycles in Karawang Regency. Using a quantitative research design, this study involved 100 respondents from prospective consumers of Honda Beat motorcycles. Data were collected through questionnaires and analyzed using SPSS 26 software. The results showed that product design had a positive and significant influence on purchasing decisions, with a regression coefficient value of 0.322. Product quality was also shown to have a positive and significant influence on purchasing decisions, with a regression coefficient value of 0.348. Multiple linear regression tests revealed that product design and product quality simultaneously influenced purchasing decisions, with a determination coefficient value (R²) of 71.9%, indicating that 71.9% of the variation in purchasing decisions could be explained by these two variables. This study contributes to the understanding of how motorcycle product design and quality can influence consumer purchasing decisions in the Indonesian automotive market. These findings are expected to provide guidance for motorcycle manufacturers, especially Astra Honda Motor, in designing better products to meet consumer expectations and win the competition in the market.

Pengaruh Kedisiplinan Guru Terhadap Pendidikan Karakter Siswa Kelas XI di SMA Negeri 1 Tapa

This research aims to observe the influence of teacher discipline on the character education of XI grade students at SMA Negeri 1 Tapa. This research uses a quantitative approach with a descrpyive method. The data in this research are primary data that is obtained by distributing quetionnaires to XI grade students at SMA Negeri 1 Tapa. The sample size is 65 respondents, consisting of all XI grade students. The data in this research are analyzed by using a simple linear regression alongside with the utilization of IBM SPSS 21.0 software. The results of this research show a positive and significant influence of teacher discipline on the character education of XI grade students at SMA Negeri 1 Tapa. The partial results indicate that the teacher discipline variable has a positive influence on the students character education, with an R Square determination coefficient value of 0.311 or 31,1%, which means that the independent variable could explain the dependent variable (Character education). In comparison, the remaining 69,9% is influenced by other variables that are not analyzed in this research.

Peran Fear of Negative Evaluation Terhadap Body Dissatisfaction pada Perempuan Emerging Adulthood

The aim of this study is to determine the role of fear of negative evaluation on body dissatisfaction in emerging adulthood women. Cluster sampling was used as a sampling technique with a total of 411 women aged 18 to 25 years in West Sumatra. The measurement instrument for fear of negative evaluation and body dissatisfaction used in this study is a questionnaire. The data from the questionnaire results were analyzed using a simple regression test. The results of a simple regression analysis showed a significance value of 0.000 (p < 0.05) which means that fear of negative evaluation plays a role in body dissatisfaction in the group of women in the emerging adulthood stage with a determination coefficient (R square) value of 0.230. This value means that fear of negative evaluation plays a role in 23% of body dissatisfaction in emerging adulthood women, while the remaining 77% is influenced by other factors

Spatial analysis and soft computational modeling for hazard assessment of potential toxic elements in potable groundwater

Swiftly increasing population and industrial developments of urban areas has accelerated the worsening of the water quality in recent years. Groundwater samples from different locations of the Doon valley, Garhwal Himalaya were analyzed to measure concentrations of six potential toxic elements (PTEs) viz. chromium (Cr), nickel (Ni), arsenic (As), molybdenum (Mo), cadmium (Cd), and lead (Pb) using Inductively Coupled Plasma Mass Spectrometer (ICP-MS) with the aim to study the spatial distribution and associated hazards. In addition, machine learning algorithms have been used for prediction of water quality and identification of influencing PTEs. The results inferred that the mean values (in the units of µg L−1) of analyzed PTEs were observed in the order of Mo (1.066) > Ni (0.744) > Pb (0.337) > As (0.186) > Cr (0.180) > Cd (0.026). The levels and computed risks of PTEs were found below the safe limits. The radial basis function neural network (RBF-NN) algorithms showed high level of accuracy in the predictions of heavy metal pollution index (HPI), heavy metal evaluation index (HEI), non-carcinogenic (N-CR) and carcinogenic (CR) parameters with determination coefficient values ranged from 0.912 to 0.976. However, the modified heavy metal pollution index (m-HPI) and contamination index (CI) predictions showed comparatively lower coefficient values as 0.753 and 0.657, respectively. The multilayer perceptron neural network (MLP-NN) demonstrated fluctuation in precision with determination coefficient between 0.167 and 0.954 for the prediction of computed indices (HPI, HEI, CI, m-HPI). In contrast, the proficiency in forecasting of non-carcinogenic and carcinogenic hazards for both sub-groups showcased coefficient values ranged from 0.887 to 0.995. As compared to each other, the radial basis function (RBF) model indicated closer alignments between predicted and actual values for pollution indices, while multilayer perceptron (MLP) model portrayed greater precision in prediction of health risk indices.

The Influence of Return on Asset, Debt to Total Asset Ratio, and Economic Value Added, on Company Value with Dividends as a Moderating Variable in Industrial Sector Companies

The purpose of this study is to determine the Effect of Return On Assets, Debt To Total Assets Ratio, and Economic Value Added on Company Value with Dividend Policy as a Moderating Variable in Industrial Sector Companies. The sampling technique in this study is purposive sampling. So that the number of samples obtained is 54 companies. The tests used are Normality Test, Multicollinearity Test, Heteroscedasticity Test, Autocorrelation Test, Interaction Test / MRA. The correlation coefficient value is 0.177, meaning that between ROA, DAR, EVA and Dividend Policy on company value, the relationship is low. The determination coefficient value (R²) or R square obtained is 0.031, indicating that 3.1% of the influence on company value is explained by the variables ROA, DAR, EVA and Dividend Policy. While the remaining 96.6% is influenced by other variables not examined in this study.

Pengaruh Kompensasi dan Beban Kerja terhadap Kinerja Karyawan (Studi pada PT. Dipa Puspa Labsains Jakarta Selatan)

The aim of this research is to determine the effect of compensation and workload on the performance of PT Dipa Puspa Labsains South Jakarta employees, both partially and simultaneously. The method used is quantitative. The sampling technique used the Slovin formula and a sample of 99 respondents was obtained. Data analysis uses validity tests, reliability tests, classical assumption tests, regression analysis, correlation coefficients, coefficients of determination and hypothesis testing. The results of this research show that partially there is a positive and significant influence between compensation on employee performance with the simple linear regression equation Y= 24.957 + 0.367X1. The correlation value is 0.576 and the tcount value is 6.948 > ttable 1.985 with a significance of 0.000 <0.05. Partially there is a positive and significant influence between workload on employee performance with the simple linear regression equation Y = 15.317 + 0.602X2. The correlation value is 0.536 and the tcount value is 6.259 > ttable 1.985 with a significance of 0.000 <0.05. Simultaneously there is a positive and significant influence between compensation and workload on employee performance with the multiple linear regression equation Y = 16.210 + 0.253X1 + 0.332X2. The coefficient of determination value is 62.3%. And the Fcount value is 30.428 > Ftable 3.09 with a significance level of 0.000 < 0.05.

Shrinkage and tree-based regression methods for the prediction of the live weight of Akkaraman sheep using morphological traits.

The prediction of live weight (LW) is of critical importance to farmers in a range of applications, including breeding and monitoring animal growth. In this context, Ridge, Least Absolute Shrinkage and Selection Operator (LASSO), and Elastic Net as shrinkage methods, and Classification and Regression Trees (CART) and Random Forest (RF) as tree-based regression methods were used in this study to predict LW of Akkaraman Sheep at 6-month age using sex, birth weight (BW) and some morphological traits such as withers height (WH), chest depth (CD), body length (BL), chest width (CW), rump height (RH), and chest circumference (CC). The dataset of 100 sheep, consisting of 44 males and 56 females, was randomly divided into training and test sets with a ratio of 80% and 20%, respectively. 10-fold cross-validation method was implemented using the training set to obtain optimum regression models and avoid overfitting. A test set was used to compare the prediction performance of regression methods based on various comparison criteria. Results revealed that LW was significantly correlated with all morphological traits and BW with coefficients ranging from 0.216 to 0.757. RF outperformed the other regression models with a coefficient of determination value (R2) of 0.865, followed by Ridge (R2 = 0.761), LASSO (R2 = 0.755), Elastic Net (R2 = 0.750), and CART (R2 = 0.654). The results indicated that WH and CD contributed the most, while sex and BW contributed the least in constructing the optimum RF model. In conclusion, the use of RF is recommended for predicting the LW of Akkaraman sheep. These results can provide a data-driven approach to improve decision-making in animal breeding.

Field-scale variability and dynamics of soil moisture in Southwestern Nigeria

This research leverages field-based sensors and Geographic Information Systems (GIS) to elucidate soil moisture dynamics across diverse land uses in Southwestern Nigeria, including Cocoa, Cassava, Oil Palm, and Riparian ecosystems. The study synthesizes soil moisture data and geospatial coordinates from strategically selected land covers with satellite-derived soil moisture records from NASA's Prediction of Worldwide Energy Resources (POWER) and the US Geological Survey. Through a robust analytical framework combining cross-correlation functions, wavelet analysis, and inverse distance weighting interpolation, we revealed distinct soil moisture patterns ranging from 0 to 47.9% in arable farms, 0 to 46.8% in built-up areas, 0 to 49.9% in cocoa farms, 0.2 to 49.7% in oil palm farms, and 5.6 to 94.1% in riparian vegetation. The coefficient of determination values between 0.7 and 0.97 (p ≤ 0.05) underscore the significant influence of periodic land use on soil moisture during the study period. A comparative analysis of ground-based and satellite data revealed a potential overestimation of minimum soil moisture values by 66% and an underestimation of maximum values by 4%. This investigation provides critical insights into the interplay between hydrological variables and agro-meteorological factors, informing the management and assessment of agricultural resources.

The HPLC-PDA Method for Simultaneous Determination of Regalosides from Bulbs of Lilium lancifolium Thunb. and Their Antioxidant Effects.

Lilium lancifolium Thunb. is a herbal medicine that is widely used to treat inflammation and lung diseases. In this study, a simultaneous quantitative method was developed for the quality control of BLL using high-performance liquid chromatography coupled with a photodiode array detector (HPLC-PDA), and their antioxidant effects were evaluated. Eight regalosides (i.e., regaloside A, B, C, E, F, H, I, and K) were selected as marker substances and separated on a Gemini C18 reversed-phase analytical column by gradient elution with distilled water-acetonitrile mobile phase containing 0.1% (v/v) formic acid. The method was validated with respect to linearity, sensitivities (limit of detection (LOD) and limit of quantitation (LOQ)), accuracy, and precision. The antioxidant effects of the extract and each component were evaluated using the 2,2-diphenyl-1-picrylhydrazyl radical scavenging assay and 2-2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) assay. The coefficients of determination values used as indicators of linearity for all components were ≥0.9999. LOD and LOQ concentrations were 0.10-0.66 μg/mL and 0.29-2.01 μg/mL, respectively. The recovery was 95.39-103.925% (relative standard deviation; RSD ≤ 2.55%), and precision RSD was <2.78%. The HPLC-PDA method was applied to real samples, and all components were detected at 1.12-29.76 mg/freeze-dried g. The evaluation of antioxidant effects showed that regalosides C, E, and K exhibited significant antioxidant effects. Our knowledge will be appropriately utilized in raw material management and conducting clinical and non-clinical studies on L. lancifolium or herbal medicine prescriptions containing L. lancifolium.

Lag Plot: A Novel Method to Determine Viable Bacterial Cell Number via a Single OD Measurement.

Bactericidal activity is a valuable parameter which is considered and measured for antimicrobial compounds. The available standard protocol to evaluate bactericidal activity is based on the direct colony count. Colony counting requires serial dilution, plating, overnight incubation, and direct counting, which is time-and labor-intensive. In regard to eliminate direct plate count, novel techniques were developed based on the real-time growth monitoring which can come with some limitations and drawbacks. These drawbacks encourage us to develop a novel technique with simple procedure to determine viable bacterial cell count. In this procedure, real-time growth monitoring is not required. In fact, after an incubation time, the number of viable bacteria can be determined with a single OD measurement and through an equation. In this regard, four standard bacterial strains, including Staphylococcus aureus (ATCC 25923), Escherichia coli (ATCC 25922), Pseudomonas aeruginosa (ATCC 27853), and Bacillus subtilis (ATCC 23857), were cultured with descending inoculum densities (1.5 × 107 to 15CFU/mL) and growth curves were drawn. As expected, growth in the samples with lower inoculum densities recorded with longer lag phase. Also, a direct relation was observed between the recorded turbidities and initial cell counts. A logarithmic curve (lag plot) was obtained by plotting the OD, after 12-18h incubation, against initial cell counts. In all examined strains, R2 was calculated in the range of 0.96-0.99 which is acceptable value for coefficient of determination. Equation corresponding to the lag plot was obtained and called lag equation. This equation is applicable to calculate the number of viable cells in unknown samples simply by inoculation, incubation, and single OD measurement. Developed technique can be introduced as a simple substitution for labor- and time-intensive direct colony counting.

Zynq FPGA for hardware co-simulation of Takagi-Sugeno neuro-fuzzy for MPPT algorithm incorporating sensorless wind speed estimation in grid-connected wind system

This paper presents a hardware implementation on the Field Programmable Gate Array (FPGA) Zed-Board of a Maximum Power Point Tracking (MPPT) incorporating pitch angle control system and sensorless wind speed estimation using the Takagi-Sugeno (TS) Adaptive Neuro-Fuzzy Inference System (ANFIS). The described approach is applied specifically to a grid-connected Permanent Magnet Synchronous Generator-based Variable Speed Wind Turbine (VSWT). Firstly, the paper proposes an estimator-based TS-ANFIS model for real-time wind speed estimation, addressing challenges with conventional anemometers, such as precision, and susceptibility to adverse weather conditions. The estimated wind speed guides the calculation of an optimized mechanical speed for MPPT control. Secondly, an MPPT-based TS-ANFIS controller is introduced to achieve the maximum power point, integrating pitch angle control to prevent turbine failures in high wind speeds. Finally, the paper emphasizes the hardware implementation on the FPGA Zed-Board, leveraging its parallel processing capabilities to enhance control system quality by reducing sampling periods and loop delays. Validation includes simulations in Matlab/Simulink using the Xilinx system generator and hardware co-simulation on the FPGA Zed-Board. A comparative analysis highlights the contributions and advancements of the proposed models and controllers compared to recent schemes in the field. Indeed, the proposed MPPT-based TS-ANFIS approach effectively maximizes the power extracted from the VSWT, achieving an estimated average efficiency of 99.84 %. In contrast, PID methods show average efficiencies of 92.63 %. Additionally, compared to other published works, the proposed MPPT-based TS-ANFIS method demonstrates a rapid response time of 0.001 s and lower static error at 0.02 %. Furthermore, the proposed WSE-based TS-ANFIS model exhibits superior performance and effectiveness, yielding a root mean squared error (RMSE) of 0.0085381, a determination coefficient (R2) value of 0.99985, and a Pearson correlation coefficient (r) value of 0.99996. Moreover, the proposed hardware implementation of these approaches maintains lower power usage, operating at a high frequency of 80.38 MHz and achieving a high throughput of 2572.16 Mbps.

Application of Machine Learning Methods in Predicting Lysine-specific Histone Demethylase 1 (LSD1) Inhibitors

Background: Lysine-specific histone demethylase 1 (LSD1) is a well-known anti-cancer target for drug discovery. Novel reversible inhibitors of LSD1 are desirable to be developed. Objective: This study aimed to build reliable predictive models to evaluate the antineoplastic efficacy of compounds and reveal the structural foundation underlying the inhibitory activity of LSD1. Methods: Multiple artificial intelligence algorithms were utilized in the development of quantitative structure-activity relationship (QSAR) models. A dataset comprising 915 compounds with welldefined IC50 values against LSD1 was assembled for analysis. The structures of these compounds were described by different descriptor packages. Principal component analysis (PCA) was performed to explore the chemical space distribution of each dataset. Y-randomization test and applicability domain (AD) analysis were deployed to validate the reliability of models. Results: For regression models, a consensus model was constructed by integrating the predictions of four top-performing individual models (SVM_ECFP4, RFR_PyDescriptor, RFR_RDKIT, and TRANSNNI), resulting in enhanced predictive performance as compared to the individual models. The consensus model achieved a determination coefficient (r2, for the test set) value of 0.82. For classification models, the consensus model was derived from the amalgamation of three individual models (ASNN_RDKIT, ASNN_ECFP4, and RFR_ECFP4), and the overall prediction accuracy of the model was 0.96 for external validation. Conclusion: The reliable models could be used to identify highly active LSD1 inhibitors for the purpose of efficient virtual screening. In addition, the important molecular properties and structural fragments derived from this work can provide guidance for the structural optimization of novel LSD1 inhibitors.

Effect of Implementing the Balanced Scorecard on the Management Performance of PT YKK AP Indonesia

This study aims to determine the effect of a balanced scorecard on the management performance of PT. YKK AP Indonesia. This study used 40 employees of PT. YKK AP Indonesia, who met the criteria to be respondents. This study was conducted using the conventional sampling method on PT employees. YKK AP Indonesia and analyzed using multiple linear regression. The first stage tested the validity and reliability of questions for each variable. The second stage conducted a classical test, and the third stage conducted an F test, t-test, and determination coefficient test. The results of the t-test study showed that the variables of financial perspective, customer perspective, internal business process perspective, and growth and learning perspective had a partial effect on management performance. In the F test, all independent variables simultaneously affected the dependent variable. Meanwhile, the determination coefficient value shows that the independent variables of financial perspective, customer perspective, internal business process perspective, and growth and learning perspective contributed to the dependent variable, namely management performance, by 49%, while other factors outside the model influenced the remaining 51%.

Why Does Organizational Citizenship Behaviour Affect The Organizational Sustainability Performance Of Msmes With The Role Individual Work Behaviour?

A person's behavioural condition will affect the continuity of work and activity. This study seeks to understand how organizational citizenship behaviour will affect the organizational sustainability performance of MSMEs with the role of individual work behaviour directly or indirectly. Research with sample of 266 MSMEs is considered sufficient in a study. Data analysis is carried out through data quality tests, path analysis, statistical tests and determination coefficients equipped with Sobel tests. The results in this study show that 1) organizational citizen behaviour has a positive significant effect on individual work behaviour; 2) organizational citizen behaviour has a positive significant effect on organizational sustainability performance; 3) individual work behaviour has a positive significant effect on organizational sustainability performance; 4) individual work behaviour as an intervening of affect organizational citizen behaviour influence on organizational sustainability performance; 5) the indirect influence of organizational citizen behaviour on organizational sustainability performance through individual work behaviour is more effective than the direct influence. 6) total determination coefficient value= 0.8206. this means that 82.06% of the organizational citizen behaviour variable affects organizational sustainability performance with individual work behaviour as an intervening. other factors outside the model influence the remaining 17.94%.

Pengaruh Lingkungan Kerja dan Disiplin Kerja Terhadap Kinerja Karyawan: Penilaian Kinerja Menggunakan Key Performance Indicator

This research aims to find out: 1) How the influence of work environment on employee performance at PT ARBA Group Gorontalo, 2) How the influence of work discipline on employee performance at PT ARBA Group Gorontalo, and 3) How the influence of work environment and work discipline on employee performance at PT ARBA Group Gorontalo. With 35 respondents determined using saturated sampling method. The approach in this study uses a quantitative approach with data collection techniques using a questionnaire (questionnaire). Data analysis techniques using multiple linear regression. Based on the results of the analysis it was found that: 1) Partially, the work environment has a significant effect on employee performance with t count&gt; t table, namely 2.718&gt; 2.036. 2) Work discipline has a significant effect on employee performance with t count&gt; t table, namely 4,770&gt; 2,036 and 3) Simultaneously the work environment and work discipline have a significant effect on employee performance at PT. ARBA Group Gorontalo with f count&gt; f table, namely 38,140&gt; 3,284. With a coefficient determination value of work environment and work discipline of 0.686 or 68.8% strong effect on employee performance at PT. ARBA Group Gorontalo. While 0.314 or 31.4% is influenced by other variables not explained in this study.