Coefficient Of Determination Values Research Articles

Pengaruh Ukuran Perusahaan dan Working Capital Turnover terhadap Profitabilitas pada PT Unilever Tbk Tahun 2014-2023

This study purpose to analyze the Effect of Company Size and Working Capital Turnover (WCT) on Profitability (ROA) at PT Unilever Indonesia Tbk in 2014-2023. This study uses a quantitative method. The population and sample in this study are the Quarterly Financial Reports of PT Unilever Indonesia Tbk in 2014-2023. The sample in the study was 40 financial reports taken using saturated sampling techniques. The data analysis used in this study is multiple linear regression analysis using the SPSS 22 application. The results of the study indicate that partially the Working Capital Turnover (WCT) variable has an effect on Profitability (ROA). While the company size variable partially has no effect on Profitability (ROA). Simultaneously, the company size and Working Capital Turnover (WCT) variables have an effect on Profitability (ROA) with a determination coefficient value of 16.1%.

Pengaruh Penggunaan Girlband Blackpink Sebagai Brand Ambassador Terhadap Minat Beli Konsumen

This research is motivated by Shopee's inclusion in the e-commerce category which is the most recommended in the MarkPlus Inc survey and this study aims to find out the influence of Blackpink as a Brand Ambassador during the 12.12 Birthday Sale 2018 promotional event on consumers' buying interest. The results of this study used a quantitative approach using the survey method with non-probability sampling type data collection techniques. The results of this study showed a calculated t value of 7.075 greater than the table t of 1.66008. It states that in this study H1 was accepted, the statement that the Brand Ambassador had an effect on buying interest was strengthened by a correlation value of 0.576 which means that two variables have a significant relationship, with a determination coefficient value of 33% of the buying interest variable can be explained by the brand ambassador variable. In this study, it can be concluded that there is an influence of Blackpink as a Brand Ambassador during the Shopee 12.12 Birthday Sale 2018 promotion.

IMPACT OF PRODUCT QUALITY AND SERVICE QUALITY ON CONSUMER SATISFACTION

The rapid growth of food business in Indonesia also leads to increased competition. Restaurants should have the advantage of being able to compete in order to survive and win the competition in this food business. One way that can be used to achieve such excellence is to implement the right quality of service and product quality so as to improve customer satisfaction and create consumer loyalty. This research aims to analyse the impact of service quality and product quality on customer satisfaction and the customer loyalty in restaurants and to know which factors are influential in the restaurant. This research aims to determine the influence of product quality and service quality on consumer satisfaction at Mie Gacoan Kenjeran 2 Surabaya. The research method uses quantitative methods. The data used are primary and secondary data. Data was obtained by distributing questionnaires to a sample of 97 respondents. This research uses a purposive sampling method and the analytical tool used is multiple linear regression with the help of the SPSS 29 program. Partial test results show that product quality has a significant effect on consumer satisfaction, service quality has a significant effect on consumer satisfaction. For the simultaneous test, it shows that product quality and service quality have a significant effect on customer satisfaction. The coefficient of determination value is 0.665, meaning that the regression model obtained is able to explain that product quality and service quality variables can influence consumer satisfaction at Mie Gacoan Kenjeran 2 Surabaya by 66.5%. Meanwhile, the remaining 33.5% is influenced by other variables not explained in this research.

Keputusan Pembelian melalui Live Streaming E-Commerce Shopee, Online Customer Review, dan Free Gift (Studi Kasus pada Pelanggan MS Glow by Mirza)

This research aims to determine the influence of Shopee e-commerce live streaming, online customer reviews, and free gifts on purchasing decisions for MS Glow by Mirza. The research method uses quantitative methods. The data used are primary and secondary data. Data was obtained by distributing questionnaires to a sample of 100 respondents. This research uses a purposive sampling method and the analytical tool used is multiple linear regression with the help of the SPSS 29 program. Partial test results show that live streaming has a significant influence on purchasing decisions, online customer reviews have no significant influence on purchasing decisions, and free gifts have no significant influence on purchasing decisions. For simultaneous tests, it shows that live streaming, online customer reviews, and free gifts have a significant influence on purchasing decisions. The coefficient of determination value is 0.665, meaning that the regression model obtained is able to explain that the variables live streaming, online customer reviews, and free gifts can influence purchasing decisions for MS Glow by Mirza products by 66.5%. Meanwhile, the remaining 33.5% is influenced by other variables not explained in this research.

Predicting Particle Size and Soil Organic Carbon of Soil Profiles Using VIS-NIR-SWIR Hyperspectral Imaging and Machine Learning Models

Modeling spectral reflectance data using machine learning algorithms presents a promising approach for estimating soil attributes. Nevertheless, a comprehensive investigation of the most effective models, parameters, wavelengths, and data acquisition techniques is essential to ensure optimal predictive accuracy. This work aimed to (a) explore the potential of the soil spectral signature obtained in different spectral bands (VIS-NIR, SWIR, and VIS-NIR-SWIR) and, by using hyperspectral imaging and non-imaging sensors, in the predictive modeling of soil attributes; and (b) analyze the accuracy of different ML models in predicting particle size and soil organic carbon (SOC) applied to the spectral signature of different spectral bands. Six soil monoliths, located in the central north region of Parana, Brazil, were collected and scanned via hyperspectral cameras (VIS-NIR camera and SWIR camera) and spectroradiometer (VIS-NIR-SWIR) in the laboratory. The spectral signature of the soils was analyzed and subsequently applied to ML models to predict particle size and SOC. Each set of data obtained by the different sensors was evaluated separately. The algorithms used were k-nearest neighbors (KNN), support vector machine (SVM), random forest (RF), linear regression (LR), artificial neural network (NN), and partial least square regression (PLSR). The most promising predictive performance was observed for the complete VIS-NIR-SWIR spectrum, followed by SWIR and VIS-NIR. Meanwhile, KNN, RF, and NN models were the most promising algorithms in estimating soil attributes for the dataset obtained from both sensors. The general mean R2 (determination coefficient) values obtained using these models, considering the different spectral bands evaluated, were around 0.99, 0.98, and 0.97 for sand prediction, and around 0.99, 0.98, and 0.96 for clay prediction. The lower performances, obtained for the datasets from both sensors, were observed for silt and SOC, with R2 results between 0.40 and 0.59 for these models. KNN demonstrated the best predictive performance. Integrating effective ML models with robust sample databases, obtained by advanced hyperspectral imaging and spectroradiometers, can enhance the accuracy and efficiency of soil attribute prediction.

Urine Glucose Detection Via Gold Nanoparticle Formation Using 3D-Connector Microfluidic Paper Based Analytical Devices

A metabolic disorders that have experienced a significant increase in the world are diabetes mellitus. Diabetes is caused by two main factors: the first is damage to pancreatic beta cells, which prevents insulin from being produced, and the second is impaired insulin secretion and function. Chronic diabetes, if not treated properly, can lead to acute complications including eye, kidney, lung, nerve, and even death. Diabetes can be diagnosed through blood and urine. In general, glucose detection is carried out using invasive methods that use blood samples, which can cause pain and discomfort for users. Current research is developing non-invasive glucose detection using urine samples. This research aims to develop non-invasive glucose detection technology using 3D-connector μPADs (Microfluidic Paper Based Analytical Devices) which have the advantages of being safe, easy, and simple. The three-dimensional connector on the device functions as a connector to facilitate the coordination of fluid flow in the sample zone and detection zone. The glucose detection method uses gold (III) chloride as a gold nanoparticle (AuNPs) precursor, an aqueous extract of Acalypha indica Linn as a stabilizing agent, sodium hydroxide (NaOH) as a catalyst, and glucose in artificial urine as a sample. Method validation results using imageJ software indicated linearity with a coefficient of determination value (R2) of 0.9714, precision with a %RSD value (Relative Standard Deviation) of 2.69, and an accuracy level ranging from 92.22-99.23%.

Enhancing Winter Wheat Representation in Noah‐MP‐Crop for Improved Dynamic Crop Growth Simulation in the North China Plain

AbstractExplicitly representing the world's most frequently cultivated winter wheat in land surface model (LSM) is important for understanding carbon and energy cycling over cropland and its interactions with climate, which is crucial for global food security. However, in the latest version of Noah‐MP‐Crop LSM, winter wheat is significantly underrepresented. This study improved the winter‐wheat parameterization in Noah‐MP‐Crop model by optimizing the phenological scheme, incorporating vernalization process, and calibrating several key parameters associated with winter wheat photosynthesis and carbon allocations. Focusing on the North China Plain as area representative region, model performance in simulating crop dynamic growth, carbon flux, and energy fluxes was validated at both site and regional scales. Results showed that the simulated phenological development matched well with the real‐world phenological records. A comparison between the simulated results by the default and developed parameterizations revealed the significant improvements in the reproductions of leaf area index (LAI) and gross primary production (GPP). The determination coefficient (R2) value of GPP was increased from 0.15 to 0.46 to 0.39–0.91. Simulations of energy fluxes showed smaller improvements, with R2 values increasing from 0.46 to 0.67 to 0.61–0.84 for latent heat (LE) and 0.18–0.55 to 0.25–0.61 for sensible heat. Additionally, the mean average error of net radiation was reduced. Improvements in spatial and temporal variations of LAI, GPP, and LE in regional simulation were also observed. This work can facilitate incorporating winter wheat cultivation and its interactions with climate system, particularly when coupling the Noah‐MP‐Crop model with the widely used Weather Research and Forecasting model.

THE INFLUENCE OF WORK MOTIVATION ON EMPLOYEE PERFORMANCE AT PT. KOPENBA JOB SITE ENGINEERING AND MANUFACTURING TANJUNG ENIM

The purpose of this study was to determine and explain how to improve work motivation at PT. Kopenba Job Site Rekayasa Enjiniring and Manufaktur Tanjung Enim. The data analysis method used is quantitative descriptive with SPSS calculations using saturated sample techniques. In analyzing data using the Likert scale, Validity Test, Reliability, Correlation Coefficient, Determination Coefficient, Simple Linear Regression, and Hypothesis Test (t-test). The correlation coefficient result of 83.1% shows a perfect relationship between work motivation and employee performance. Hypothesis (t-test), work motivation is obtained from Tcount> Ttable which is 5.383> 2.306 with a significant value of 0.000 <0.05 then H1 is accepted. This shows that partially the work motivation variable affects employee performance. While the determination coefficient value of 78.8% has a positive and significant effect of work motivation on employee performance at PT. Kopenba Job Site Engineering Engineering and Manufacturing Tanjung Enim This motivation has an important role in improving Employee Performance and the remaining 21.2% is determined by other factors.

Pengaruh Fitur, Variasi Produk, dan Kemudahan Transaksi terhadap Kepuasan Pengguna Mobile Banking pada Lembaga Keuangan Perbankan Syariah di Kota Jambi

This research aims to determine the influence of features, product variations and ease of transactions on mobile banking user satisfaction at sharia banking financial institutions in Jambi City. This research used a quantitative approach which was carried out by distributing questionnaires to 112 Mobile Banking users in Jambi City. The methods used in this research are instrument tests (validity and reliability tests), classical assumption tests (normality, multicollinearity and heteroscedasticity tests) and multiple liner analysis along with statistical tests (t test, F test and R2 Determination Coefficient). The results of this research show that features have a positive and significant effect on user satisfaction which can be determined using the t test with a significance value of 0.001 < 0.05 and a value of tcount > ttable, namely 3.426 > 0.198217. Product variations have a positive and significant effect on user satisfaction as evidenced by the significance value of 0.001 < 0.05 and the tcount > ttable value, namely 3.577 > 0.198217. ease of transactions has a positive and significant effect on user satisfaction which can be seen with a significance value of 0.001 < 0.05 and a value of tcount > ttable, namely 3.385 > 0.198217. Simultaneously, features, product variations and ease of transactions have a positive and significant effect on mobile banking user satisfaction at sharia banking financial institutions which can be seen from the F test, namely fcount > ftable or 40.058 > 2.69 and the resulting significance value is 0.000 < 0.005. The determinant coefficient value is 0.514 or 51.4% and the remaining 0.486 or 48.6% can be explained by other variables outside this research.

The effect of financial distress on accounting misstatements during the Covid-19 pandemic

This study aims to examine the effect of financial distress on accounting misstatements and to find out whether the COVID-19 pandemic moderates the relationship between financial distress and accounting misstatements. This study uses data from property and real estate companies listed on the Indonesia Stock Exchange (IDX) for the period from 2017 to 2021. The total research sample is 145 entities. The statistical methodology used in this study is panel regression analysis with the following steps: selecting the best regression model, classical assumption testing, and regression testing to determine coefficient values and significance levels. The results of this study show that financial distress has no significant effect on accounting misstatements. This study also finds empirical evidence that the COVID-19 pandemic does not moderate the relationship between financial distress and accounting misstatement. Although accounting misstatements have been a research topic for many years, little attention has been paid to their impact on companies experiencing financial distress and crises. Further research still needs to be carried out regarding the impact of the COVID-19 pandemic on the relationship between financial distress and accounting misstatement using a sample of companies that have a high multiplier effect. It is hoped that the results of this study can provide additional references to prove that agency theory and prospect theory can explain accounting misstatements.

Modeling of milling forces in facing process of aluminum alloy AL7075 using the square inserts

Cutting forces play very important in designing the tool machine, cutting tool, and in optimization of machining processes. Modeling and prediction of cutting forces by theoretical methods are quite difficult, so, this study was focused on modeling the cutting force in face milling process using combination of theoretical and experimental methods. This study was performed to model the milling forces (MFs) and determine the milling force coefficients (MFCs) in the face milling process of aluminum alloy Al7075 using square inserts. From theoretical and experimental methods, the relationship of average milling forces (AMFs) and feed per flute (ft) were determined as the linear regression. Using experimental data, the linear regressions of AMFs and feed per flute were determined with high values of determination coefficients (larger than 95 %). MFCs were determined including shear and edge MFCs (tangential shear MFC (Ktc) of 538.127 N/mm2, radial shear MFC (Krc) of 185.967 N/mm2, axial shear MFC (Kac) of -691.297 N/mm2, tangential edge MFC (Kte) of 11.253 N/mm, radial edge MFC (Kre) of 6.991 N/mm, and axial edge MFC (Kae) of –32.971 N/mm. The MF models were successfully verified by comparing the measured and predicted MFs in face milling process of Al7075. The tendency and shape of predicted MFs were quite close to the measured ones. The differences between the predicted and the measured MFs can be due to the several reasons such as the influence of vibrations, the influence of cutting heat, etc., and these are also the limitations of this study. The modeling and prediction methods of this study can be used to model and predict the cutting forces in face milling of other milling types and other pairs of cutting tool and workpiece material as well

Classification and regression machine learning models for predicting the combined toxicity and interactions of antibiotics and fungicides mixtures

Antibiotics and triazole fungicides coexist in varying concentrations in natural aquatic environments, resulting in complex mixtures. These mixtures can potentially affect aquatic ecosystems. Accurately distinguishing synergistic and antagonistic mixtures and predicting mixture toxicity are crucial for effective mixture risk assessment. We tested the toxicities of 75 binary mixtures of antibiotics and fungicides against Auxenochlorella pyrenoidosa. Both regression and classification models for these mixtures were developed using machine learning models: random forest (RF), k-nearest neighbors (KNN), and kernel k-nearest neighbors (KKNN). The KKNN model emerged as the best regression model with high values of determination coefficient (R2 = 0.977), explained variance in prediction leave-one-out (Q2LOO = 0.894), and explained variance in external prediction (Q2F1 = 0.929, Q2F2 = 0.929, and Q2F3 = 0.923). The RF model, the leading classifier, exhibited high accuracy (accuracy = 1 for the training set and 0.905 for the test set) in distinguishing the synergistic and antagonistic mixtures. These results provide crucial value for the risk assessment of mixtures.

Pengaruh Metode Lattice Terhadap Hasil Belajar Operasi Perkalian Bilangan Cacah dengan Menggunakan Model PBL di Kelas IV Sekolah Dasar

This study aims to determine the effect of using the lattice method on the learning outcomes of multiplication operations of integers in class IV elementary school. This research is experimental research in the form of Quasi Exsperimental Type Nonequivalent Control Group Design. The sampling technique used cluster random sampling. In hypothesis testing, simple linear regression test, correlation analysis, and t test were used. Based on correlation analysis, the experimental class obtained rxy 0.825 which is categorized as very strong. The coefficient determination value obtained is 68.06%, so it can be interpreted that the use of the lattice method has an effect of 68.06% on the learning outcomes of multiplying small numbers in class IV. Through the t-test in the form of an independent t-test based on the posttest scores of the experimental and control classes, a tcount of 2.04613 was obtained with a ttable of 2.014 at a significance level of 0.05. When the tcount and ttable are compared, 2.04613> 2.014. This means that Ho is rejected, and Ha is accepted, so it can be concluded that there is a significant effect of using the lattice method with the PBL model on the learning outcomes of multiplication operations of small numbers in class IV elementary schools

The Influence of Parental Education Level on Learning Discipline of PPKn FKIP Students at Riau University

This study is motivated by the role of parents' level of education in guiding and directing their children in the learning process, especially in student learning disciplines. This research aims to determine whether there is an influence between the level of parental education on the learning discipline of PPKn FKIP Riau University students. This research uses quantitative research methods carried out in the PPKn FKIP study program at Riau University with data collection methods using questionnaires and statistical data analysis using SPSS Version 20. Based on the findings from data analysis, the hypothesis test has a calculated f value f table, this shows the alternative hypothesis in this study was rejected. The coefficient of determination value in this study was obtained at 0.006, so it can be concluded that the influence of the parental education level variable on the student learning discipline variable was 0.6%, while the other 99.4% (100% - 0.6%) was influenced by other factors. others not examined in this study.

ANALISIS CITRA MEREK DAN STRATEGI HARGA DALAM KEPUTUSAN PEMBELIAN MOBIL MITSUBISHI DI PT LAUTAN BERLIAN UTAMA MOTOR CABANG JAKARTA BARAT

This research aims to determine the influence of brand image and price on purchasing decisions for Mitsubishi passenger cars at PT Lautan Berlian Utama Motor West Jakarta Branch, both partially and simultaneously. This research is descriptive quantitative with an associative approach. Sampling was taken using purposive sampling technique. The population in this study are people who have purchased Mitsubishi passenger cars in residential areas in West Jakarta and its surroundings, including the Depok, Bogor, Bekasi, Tangerang areas. The ancient Rao sample used in this research was 96 respondents. Data collection techniques using observation, questionnaires, data analysis techniques using validity tests, reliability tests, classical assumption tests, linear regression tests, correlation coefficient tests, coefficient of determination tests, hypothesis tests, t tests and f tests with the help of SPSS Version 26 software. The research results show that (1) Brand Image influences purchasing decisions with the regression equation Y=7.081=0.789X1. The correlation coefficient value is 0.837, the coefficient of determination value is 0.700, which has a significant effect on purchasing decisions with a calculated t result of 14.824 > t table 1.986. with a significance level of 0.000 < 0.05. (2) Price influences purchasing decisions with the regression equation Y = 3.524+1.073 .05. (3) Brand Image and Price influence purchasing decisions with the regression equation Y = 1.055+0.420X1+0.694X2, correlation coefficient value of 0.931, determination coefficient value of 0.867, significant influence on purchasing decisions with the result Fcount 302,881 > Ftable 3.094 with a significance of 0.000 < 0.05, then in this study Ha is acceptable.

Role of Childhood Trauma in Addiction and Social Anxiety of Young Drug Users in Islamshahr City

The purpose of this study was to investigate the role of childhood trauma in addiction and social anxiety among young drug users in Islamshahr City. This research is applied in terms of purpose and in terms of descriptive-correlation method and it is survey type. The statistical population of the present study was 800 young drug users in Islamshahr City who had been referred to addiction treatment and counselling clinics. Based on the table of Morgan Karjesi, the sample size was calculated to be 260 people. To collect information, a questionnaire tool was used, which was distributed among the sample using the available sampling method. 22SPSS software was used to analyze the findings and regression analysis was used to check the hypotheses. The results showed that the correlation between childhood trauma and the addiction tendency of drug users is 0.75. Also, the determination coefficient value is 0.29, which shows that 0.29 changes in the variable of tendency towards addiction among drug users can be explained by childhood trauma. Therefore, it can be concluded that childhood trauma with a confidence level of 95%; has a significant effect on the addiction tendency of young drug users. Also, the correlation between childhood trauma and social anxiety of young drug users is 0.465. Also, the coefficient of determination is 0.441, which shows that 0.44 of the changes in the social anxiety variable of drug users can be explained through childhood trauma. Therefore, it can be concluded that childhood therapy has a direct and significant effect on addiction and social anxiety of drug users with a confidence level of 95%. Therefore, paying attention to childhood trauma plays an important role in predicting young people's tendency to addiction as well as their social anxiety.

PENGARUH PEMBIASAAN KEAGAMAAN TERHADAP AKHLAK SISWA KELAS 8 DI SMP NEGERI 1 SAWAHAN NGANJUK

Abstraction This study aims to determine the Influence of Religious Habits on the Morals of 8th Grade Students at SMP Negeri 1 Sawahan Nganjuk. This study uses a quantitative approach, because the data obtained is presented in the form of numbers and analysis based on statistics. The data that will be presented in the form of numbers in this study are religious habits and moral data taken from the research object. While the data collection methods used in this study are: Observation method, Documentation method and Questionnaire method. Data analysis techniques in this study include descriptive statistical analysis, inferential analysis, and hypothesis testing. The results of this study indicate that: religious habits have an influence on the morals of 8th grade students at SMP Negeri 1 Sawahan Nganjuk with a correlation coefficient of 0.602. This means that religious habits carried out by 8th grade students have a high influence on their morals. The coefficient of determination value in SPSS v.25 data processing is 0.355. Keywords: Religious Habits; Student Morals

The Influence of Tahfidz and Qiro'ati on Islamic Religious Education Learning Outcomes at Islamic Middle School "Al Hasanah" Bengkulu City

The purpose of research is to determine influence of the foundation program toward the result of Islamic Religious Education learning at Al Hasanah Islamic Junior High School, to know the influence of the Tahfidz program on improving learning outcomes of Islamic Religious Education, and to know the influence of the Qiro'ati method on improving learning outcomes of Islamic Religious Education at Al Hasanah Islamic Middle School Bengkulu City. The method used in this research is quantitative research approach, this type of research is non-experimental quantitative research. Research data collection techniques through observation, questionnaire, and documentation. The data analysis technique in this study using simple linear regression analysis with the help of a computer program SPSS version 16.0. The results of this research indicate is no significant influence between the Tahfidz program and the Qiro'ati method on improving the learning outcomes of Islamic Religious Education. Results of testing the hypothesis above, namely the F test, and the coefficient of determination that the foundation program variable (X) does not significantly influence the variable of learning outcomes of Islamic Religious Education (Y). The contribution given by the foundation program variable (X) to the variable of increasing learning outcomes of Islamic Religious Education (Y) is only 0.1% which is indicated by the determinant coefficient value of 0.1%. Thus it can be concluded that there is no significant influence between the Tahfidz program and the Qiro'ati method in improving the learning outcomes of Islamic Religious Education at Al Hasanah Islamic Middle School, Bengkulu City.

Leverage Moderates the Effect of Capital Intensity on Accounting Conservatism in Metal Sub Sector Manufacturing Companies Listed on the IDX In 2018-2022

This study aims to determine the Effect of Capital Intensity (X) on Accounting Conservatism (Y) with Leverage (Z) as a moderating variable in Metal Sub-Sector Manufacturing Companies listed on the Indonesia Stock Exchange in 2018-2022. The results of this study indicate that Capital Intensity has no effect on Accounting Conservatism. This result is evidenced by the calculated t of 1.289 <t table value of 2.005 and a significant value of 0.203> 0.05. After that Leverage strengthens the relationship between Capital Intensity and Accounting Conservatism. This result is evidenced by the results of the Moderate Regression Analysis (MRA) test seen from the determination coefficient (R2) value in the regression equation structure 1, which is 3% <the determination coefficient (R2) value in the regression equation structure 2, which is 4.1%. This can also be seen from the slope value in the regression equation structure 2, where the regression coefficient X * Z is positive, which is 1%.

Bifenthrin Residues in Table Grapevine: Method Optimization, Dissipation and Removal of Residues in Grapes and Grape Leaves.

The QuEChERS method was adjusted to determine bifenthrin residues in grapes and grape leaves. Extraction and cleanup procedures were optimized to decrease co-extracted materials and enhance the detection of bifenthrin. The method was validated per the European Union (EU) Guidelines criteria. Accuracy ranged from 98.8% to 93.5% for grapes and grape leaves, respectively. Precision values were 5.5 and 6.4 (RSDr) and 7.4 and 6.7 (RSDR) for grapes and grape leaves, respectively. LOQs (the lowest spiking level) were 2 and 20 µg/kg for grapes and grape leaves, respectively. Linearity as determination coefficient (R2) values were 0.9997 and 0.9964 for grapes and grape leaves, respectively, in a matrix over 1-100 µg/L range of analyte concentration. This was very close to the value in the pure solvent (0.9999), showing the efficiency of the cleanup in removing the co-extracted and co-injected materials; the matrix effect was close to zero in both sample matrices. Dissipation of bifenthrin was studied in a supervised trial conducted in a grapevine field during the summer of 2023 at the recommended dose and double the dose. Dissipation factor k values were 0.1549 and 0.1672 (recommended dose) and 0.235 and 0.208 (double dose) for grapes and grape leaves, respectively. Pre-harvest interval (PHI) was calculated for the Maximum Residue Limit (MRL) values of the EU database. Residues of bifenthrin were removed effectively from grapes using simple washing with tap water in a laboratory study. Residues reached the MRL level of 0.3 mg/kg in both washing treatments, running or soaking in tap water treatments for 5 min. Removal from leaves did not decrease residue levels to the MRL in grape leaves.