Coefficient Of Determination Values Research Articles

Application of monomer structures and fragments of local symmetry for simulation of glass transition temperatures of polymers

ABSTRACT A scheme for constructing models of the ‘structure-glass transition temperature of a polymer’ is proposed. It involves the representation of the molecular structure of a polymer through the architecture of monomer units represented through a simplified molecular input-line entry system (SMILES) and the fragments of local symmetry (FLS). The statistical quality of such models is quite good: the determination coefficient values for active training set, passive training set, calibration set, and validation set are 0.711, 0.715, 0.859, and 0.884, respectively. The reliability of the approach was assessed for three random distributions of experimental data in the training and validation sets. Machine learning technique was used for a structured training sample distributed in so-called active and passive learning, combined with a calibration set. The optimal descriptors for developed the models were calculated by the Monte Carlo technique.

Hemolytic activity of saponins from the leaves and stems of the specie Boldoa purpurascens Cav., determined by HPLC – UV: Validation of the method

This research contributes on the chemical composition of the species Boldoa purpurascens Cav. although the identification, quantification, and hemolytic activity evaluation of saponins isolated from this specie, moreover, high-performance liquid chromatography - ultraviolet detection (HPLC - UV) methodology has been developed and validated. To determine the saponin content of Boldoa purpurascens Cav. hydroalcoholic extract, a HPLC – UV was used. A Quil-A® pattern has been used to evaluate the validation parameters, such as method linearity, limits of detection and quantification, precision, accuracy, selectivity, and specificity. The research showed that each target component was well-separated under the optimal analytical settings with great selectivity. The technique was found to be precise, accurate, and repeatable. The method's linearity was determined to be robust, with an excellent determination coefficient value (R2≥0.999). The evaluation of the matrix effect revealed that each target component had a high degree of selectivity and was well-separated. It could be inferred that the established HPLC-UV methodology is accurate and useful for identifying saponins in the hydroalcoholic extract of Boldoa purpurascens Cav. The hydroalcoholic extract of Boldoa purpurascens Cav. was used to quantitatively determine the saponin content, and it was discovered that the concentration of QS 7 in the 80% hydroalcoholic extract was 1.9 x 10-2 g L-1 in the stem whereas 1.6 x 10-2 g L-1 in the leaves. The Boldoa purpurascens Cav. saponins have hemolytic activity comparable to Quil-A®, as shown by a thin layer chromatographic hemolysis experiment.

Analysis of The Determination of Rail-Based Urban Transportation Routes in The City Of Manado (Case Study: Zero Point Manado - Sam Ratulangi International Airport)

Consequently, the activities that develop as a result of the formation of activity/land use centers such as government administration centers, residential areas, schools, hospitals, entertainment facilities, shopping centers, tourism accommodation centers, causes huge movement generation which affects the existing transportation systems. It can be concluded that the resulting travel time will decrease with a large enough passenger carrying capacity. The recommended form is the type of LRT (Light Rail Transit) with rail-based technology. The method used in this research is literature study, primary data collection in the form of household interview surveys, and secondary data collected from several related institutions. The survey results were analyzed with the help of Microsoft Office Excel and modeling using a linear regression equation with the independent variables measured, namely family composition (X1), number of working members (X2), number of members attending school (X3), number of members working and attending school (X4), vehicle ownership (X5), family income (X6), and the dependent variable (Y) as the number of family movements per day. The modeling results obtained the best equation, namely Y=1.394+0.888X1 and the Determinant Coefficient (R²) value obtained was 0.824 or 82.4%. LRT (Light Rail Transit) line concept with the starting point of the Station Zero Point Manado - Paal Dua Station 1 - Paal Dua Station 2 - Manado-Bitung Toll Gate Station - Manado-North Minahasa Station - Mapanget Station - Sam Ratulangi International Airport Station with a total of 7 stations and 6 segments and a total length of 15,400 meters.

Evaluation of genotypic variations in the protein content of soybean through near infrared spectroscopy

Demand for soybean seeds with increased protein content is high in the international market. In this context, breeding soybean varieties targeting high protein content is the need of the day. In this paper, elite soybean germplasm accessions were screened for protein content. Eighty-eight soybean germplasm was evaluated for protein content through near infrared spectroscopy. A prediction model to determine the protein content of soybean germplasm through a non-destructive method was developed to calibrate the NIR. The protein content of 39 lines was analyzed in wet lab conditions and used to calibrate in NIRs between 1400 and 2400 nm at 2 nm intervals. High determination coefficient and low values of root mean square error (2.585) and standard error of prediction (2.832) confirmed the model’s utility for predicting the protein content of unknown samples. Accordingly, the protein content of 49 germplasm lines revealed that the genotypes LU96, TNAU20056, and SL525 depicted high values of 56.66, 55.51, and 54.48% protein content, respectively, but with fewer yields. The genotype RKS45 recorded a protein content of 45.33% with a single plant yield of 34.09 g, which can be further utilized for hybridization and selection. Thus, a non-significant correlation was observed between the protein content and single plant yield, suggesting that an increase in protein content will not directly influence the yield parameters. This paper provides a simple methodology to accurately determine the protein in a large set of samples in a short time, which helps in speed breeding programs.

Relationship between body weight and dorsal area in female buffaloes

Background: Body weight (BW) has been reported as important information in the decision-making process; therefore, it is necessary to determine if body measurements obtained from the dorsal view of the animal are related to BW, considering that we are currently living in the era of the so-called "livestock 4.0". Objective: The objective of the present study was to evaluate the relationship between BW and dorsal area (DA) in water buffaloes (Bubalus bubalis) reared in southeastern Mexico. Methods: The BW (340 ± 161.68 kg), hip width (BW), thorax width (TW) and body length (BL) were measured in 215 female Murrah buffaloes aged between 3 months and 5 years. The DA (m2) was calculated using the mathematical formulae for calculating the area of a trapezoid, considering the HW, TW, and BL in the calculation. The relationship between BW and DA was assessed using correlation and regression models. Results: The correlation coefficient between BW and AD was 0.96 (P<0.001). The linear equation demonstrates the highest determination coefficient value (R2 = 0.94) along with the lowest mean square error (MSE = 1716.86), root MSE (RMSE = 41.43), Akaike Information Criterion (AIC = 1603.36), and Bayesian Information Criterion (BIC = 1610.10). Conversely, the allometric equation exhibits the highest values of MSE, RMSE, AIC, and BIC. The quality of fit using the k-folds technique allowed us to identify that the three proposed equations showed consistent adjustments, with an accuracy above 90% (R2 = 0.92). Among them, the quadratic equation exhibited lower values of mean squared prediction error and mean absolute error. Conclusions: The DA can be a good predictor of BW in buffaloes, especially when incorporated into first and second-degree linear equations.

Pengaruh Kecemasan Matematika terhadap Prestasi Belajar Matematika Siswa SMP Negeri 2 Jogoroto

Students' mathematics learning achievement is influenced by several factors, one of which is anxiety. The purpose of this study was to determine whether or not there is an effect of mathematics anxiety on students' mathematics learning achievement. This study is a correlational study. The population in this study were all students of class VIII of SMP Negeri 2 Jogoroto in the 2021/2022 academic year consisting of 160 students. The sampling technique in this study used a random sampling technique, namely a random sampling technique. The number of samples in the study was 40 students. Data collection used two methods, namely the questionnaire method and the documentation method. The research instrument used a questionnaire sheet and a documentation sheet. The validity of the instrument used expert validity. Data analysis used simple linear regression analysis. The results of the data analysis obtained a Sig value of 0.000 <0.05 so that H_0 was rejected, meaning that there is an effect of mathematics anxiety on students' mathematics learning achievement at SMP Negeri 2 Jogoroto with a regression equation Y = 94.614-0.739, which means that for every 1 increase in the score obtained in mathematics anxiety, learning achievement will decrease by 0.739. The magnitude of the correlation is -0.822 with a Sig value of 0.000 <0.05 so that H_0 is rejected, meaning that there is a significant relationship between mathematics anxiety and students' mathematics learning achievement at SMP Negeri 2 Jogoroto. With a Determination Coefficient value of 0.676, it shows that there is an influence of mathematics anxiety of 67.6% and 32.4% is influenced by other factors that are not studied.

Pengaruh Non Performing Financing, Return On Assets, dan BOPO pada Kondisi Financial Distress pada BPRS di Jawa Barat 2020-2023

This study was conducted to determine the risk of financial distress of Islamic Rural Credit Banks in West Java for the period 2020-2023 using the Springate S-score calculation model. The financial ratios used in this study are NPF, ROA and BOPO. The data in this study were 32 data, namely 4 years of time series data on 8 Islamic Rural Credit Banks obtained through the official Islamic banking statistics website of the Financial Services Authority (https://www.ojk.go.id). The data analysis used in this study was multiple regression. Based on the results of the study (1) Non Performing Financing (NPF) partially has no negative and insignificant effect on Financial Distress (increase in Score value) with a magnitude of influence of 10.4%. (2) Return On Asset (ROA) partially has a positive and significant effect on Financial Distress (increase in S-score value). With a magnitude of influence of 40.5%. (3) BOP) has no positive and significant effect on Financial Distress (increase in S-score value). With a magnitude of influence of 19.4%. (4) NPF, ROA and BOPO simultaneously affect the financial distress condition at Islamic Rural Credit Banks in West Java in 2020-2023 with a determination coefficient value of 41.5. While the remaining 58.5% is influenced by other variables not examined in the study.

Analysis of the Influence of Marketing Mix and Store Layout on Purchase Decisions at Kimia Farma Pharmacy Central Jakarta Branch

In 2020, the Ministry of Health reported that there were 30,199 registered pharmacies (Ministry of Health of the Republic of Indonesia, 2022). This number fluctuated from 2018 to 2020, indicating competition in the pharmacy business. To face this competition, pharmacies need to implement strategies that can influence customers' purchasing decisions. This study aims to determine the influence of marketing mix and store layout on purchase decisions. The method used is quantitative with data collection through a Likert scale questionnaire. The number of samples was 100 respondents, calculated using the Yamane and Isaac-Michael formulas, and tested for validity and reliability using SPSS. The results of the multiple regression test show that the marketing mix and store layout together influence the purchase decision. This proved that both significantly influenced the purchase decision, so Ho was rejected and H1 was accepted. In addition, the test results also show that partially, these two factors have a significant influence on purchase decisions. The marketing mix strategy and store layout implemented by Kimia Farma's Central Jakarta branch is considered effective because it is able to influence purchasing decisions, as evidenced by the value of the R2 determination coefficient of 85.2%.

Application of robust estimation methods in real estate valuation

Motives: Conducting real estate appraisals in well-developed markets presents a multitude of data analysis challenges. Some property price data may contain outliers that can significantly affect the valuation process and, as a result, the estimated value. In the case of real estate valuation regression models, estimation is most often based on the least squares method, where outliers are taken into account just like the rest of the data. Eliminating or minimizing the influence of outliers can lead to more reliable estimation results. Such problems can be solved by implementing robust regression methods. Aim: The main goal is to determine whether robust estimation methods using M-estimators with multiple regression models can provide more accurate estimates of property values. Results: Research has shown that multiple regression models using robust regression methods can be applied to estimate property values. The use of different types of M-estimators allows for the objective elimination of outliers through algorithms that operate on the entire data set. The calculations are carried out iteratively, and at each iteration step the residuals are verified and the observations are re-weighted. The following M-estimators were considered: Huber, Hampel, Tukey, Faire, Cauchy and Welsch. The reference point was the estimation results from the ordinary least squares method (OLS). All analysed M-estimators led to an increase in the coefficient of determination value and a decrease in standard estimation errors. Each algorithm detected the outliers. The valuation results for the selected properties were also more reliable. The results obtained depend on the characteristics of the data, and the choice of the best estimator may vary across different property markets. The selection of the best estimator may even vary within the same local property market, where the valuer makes subjective assessments of the location or other attributes.

Carbon stock in calophyllum inophyllum provenances from eight islands in Indonesia: associate soil physicochemical properties and litter fiber content

Calophyllum inophyllum is a superior choice for sustainable biodiesel production. This tree is highly productive, adaptable to various land types, and has a significant potential for carbon sequestration. This study aimed to determine carbon storage variation in biomass, litter, and soil among C. inophyllum provenances from eight islands in Indonesia; identify the best allometric model for estimating total plant biomass carbon stock; and assess the impact of soil physicochemical properties and litter fiber content on total carbon stock. Plant, litter and soil samples were purposively selected from a total of 32 sample points of 8 provenances. Analysis of variance was carried out to determine variations among provenances on carbon storage in plant biomass and its components (stems, branches, twigs, leaves, stumps, and roots), in litter, as well as in soil organic carbon. The best allometric equation was selected to estimate the total plant biomass carbon based on the value of coefficient determination (R2) and RMSE (Root Mean Square Error). Redundancy Analysis (RDA) was carried out to determine the effect of the soil physicochemical properties and litter fiber content on total biomass carbon and total soil organic carbon followed by a partial analysis (Variation Partitioning Analysis). The results of this study showed that variations on carbon storage in plant biomass and its components, in litter, as well as in soil organic carbon were not significantly different among the provenances. The tBC averaged 13.46 tons ha−1, the litter carbon 4.75 tons ha−1, and tSOC 75.91 ton ha−1 with most biomass carbon stored in trunks (31.02%) and most of carbon stock was stored as tSOC (81%). Quadratic (tBC = 0,4172DBH2 - 1,3433DBH + 2,3498) was the best allometric model for estimating carbon storage on plant biomass with diameter at breast height (DBH) as a predictor variable. Most of the variation in total carbon stock was influenced by soil chemical properties (76%) followed by soil physical properties (11%) and litter fiber content (5%). This study implies that the development of C. inophyllum in Indonesia for carbon storage may utilize seeds or planting materials from any origin, disregarding provenances. Applying organic and/or mineral nutrients (N, P, and K) will increase carbon stock in C. inophyllum plantations. This study underscores the significance of assessing C. inophyllum carbon stocks to enhance its role in establishing climate change policies and promoting sustainable resource management.

Development and validation of mathematical model for population estimation of the two-spotted spider mite in soybeans

The two-spotted spider mite Tetranychus urticae Koch, 1836 (Acari: Tetranychidae) causes bronzing and leaf drop in soybeans, reducing grain production and quality. Using colorimetric measurements in soybean-producing areas can be an alternative for monitoring the mite, aiding in the estimation of field populations. The objective of this study was to estimate the quantity of the two-spotted spider mite in soybeans through colorimetric measurements using the CIE-L*a*b* color space. Soybean plants at the V3 stage were used with 4 treatments (Control=0; T1=30; T2=60; and T3=100 adult female T. urticae per plant), 4 repetitions, and 170 measurements. Regression and variance analyses were performed using Origin Pro 2015 software. Prediction equations were calibrated. Our results show that there was a significant difference for the L*, a*, and ΔE* variables. Regression analyses presented determination coefficient values of 0.87, 0.93, and 0.55 for L*, a*, and b*, respectively. The use of the (a*) variable in the CIE-L*a*b* color space proved effective in distinguishing between infestation levels. The model created to estimate the quantity of mites on soybean leaves has the potential to be applied in soybean production areas with infestations of the two-spotted spider mite.

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.

Decoupling and Insensitivity of Greenness and Gross Primary Productivity Across Aridity Gradients in China

The ecosystem’s gross primary productivity (GPP) and greenness, as indicated by the normalized difference vegetation index (NDVI), are both essential ecological indicators used to evaluate how ecosystems responded to climate variability. However, the relationships between NDVI and GPP under the influence of drying and wetting and its characteristics along aridity (AI) gradients were not yet fully understood. In this study, we investigated the relationships of the NDVI-GPP (i.e., the strength of the coupling and the sensitivity, as quantified by the coefficient of determination (R2) and slope of the linear regression, respectively) along the aridity gradients during the growing season from 1982 to 2018 in China. The results show that the coupling between NDVI and GPP was stronger (i.e., high R2) in semi-arid regions (0.24) compared to humid and hyper-humid regions (R2 values were 0.11). For different plant functional types (PFTs), decoupling occurred in ENF with a determination coefficient value (R2) of 0.04, whereas GRA shows a higher coupling with an R2 of 0.20. The coupling trend experienced a shift in semi-arid regions, characterized by an aridity index (AI) ranging from 0.20 to 0.50. Additionally, the sensitivity of GPP to NDVI also decreased with increasing aridity. The slope values were 0.19, 0.21, 0.24, 0.20, 0.11, and 0.11 in hyper-arid, arid, semi-arid, dry sub-humid, humid, and hyper-humid, respectively. What is more, asynchronous changes in vegetation productivity and greenness can be detected by capturing the inter-annual variability (IAV) of NDVI and GPP. The IAV of GPP steadily decreased with the aridity gradients, while the IAV of NDVI present fluctuated, suggesting that NDVI was more variable than GPP under the influence of drying and wetting conditions. Our study suggests that there may be a stronger trade-off between ecosystem greenness and photosynthesis in more humid areas.

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