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Journal articles on the topic 'Factor Analysi'

Author: Grafiati

Published: 9 March 2023

Last updated: 31 July 2025

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1

Han, Woo Shin, and Jeong Wook Choi. "A Study on the Type of Women's Body In their early 20s in China: Focused on the Residents in Shanghai." Institute of Art & Design Research 26, no. 2 (2023): 153–60. http://dx.doi.org/10.59386/jadr.2023.26.2.153.

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This study is to categorize the body types of Chinese w omen in their twenties based on their morphology and pr ovide basic data that can be used for Korean clothing co mpanies. Human body size data were directly measured o n 600 women in their twenties residing in Shanghai, Chi na from January 2020 to September 2023. The human bo dy measurement items include 9 perimeter items and 10 length items, measuring a total of 19 items. In order to extract factors that can analyze body shape, factor analysi s was conducted and two factors were identified. Factor 1 is “perimeter and width”, and factor 2

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2

Erawati, Teguh, and Sisilia Stefani Wuarlela. "Ukuran Perusahaan, Profitabilitas, Likuiditas, Pertumbuhan Laba Dan Kualitas Laba Pada Perusahaan Pertambangan Di Indonesia." Jurnal Literasi Akuntansi 2, no. 2 (2022): 157–66. http://dx.doi.org/10.55587/jla.v2i2.62.

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Purpose: This study aims to prove the effect of firm size ,profitability, liquidity and earnings growth on earnings quality.the research sample is mining companies listed on the indonesia stck exchange (IDX) in 2017-2020 using purposive sampling. Method: sampling used sampling method and produced 80 sample data. Data analysi technques wit multiple linier analysis Finding: this study shows that firm size has no significant effect on earnings quality,profitability has a significant effect on earnings quality,liquidity has asignificant offect on earnings quality and earning rowth has no significa

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3

Erawati, Teguh, and Sisilia Stefani Wuarlela. "Ukuran Perusahaan, Profitabilitas, Likuiditas, Pertumbuhan Laba Dan Kualitas Laba Pada Perusahaan Pertambangan Di Indonesia." Jurnal Literasi Akuntansi 2, no. 2 (2022): 157–66. http://dx.doi.org/10.55587/jla.v2i2.62.

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Purpose: This study aims to prove the effect of firm size ,profitability, liquidity and earnings growth on earnings quality.the research sample is mining companies listed on the indonesia stck exchange (IDX) in 2017-2020 using purposive sampling. Method: sampling used sampling method and produced 80 sample data. Data analysi technques wit multiple linier analysis Finding: this study shows that firm size has no significant effect on earnings quality,profitability has a significant effect on earnings quality,liquidity has asignificant offect on earnings quality and earning rowth has no significa

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4

Devica, Sadana. "PERSEPSI KONSUMEN TERHADAP FLASH SALE BELANJA ONLINE DAN PENGARUHNYA PADA KEPUTUSAN PEMBELIAN." Jurnal Bisnis Terapan 4, no. 1 (2020): 47–56. http://dx.doi.org/10.24123/jbt.v4i1.2276.

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Penelitian ini bertujuan untuk mengetahui bagaimana persepsi konsumen terhadap program promosi dalam bentuk flash sale dan bagaimana pengaruhnya tehadap keputusan pembelian. Penelitian ini dilakukan pada 145 orang responden, sedangkan untuk teknik analisis data menggunakan confirmatory factor analysi (CFA) dan analisis regresi. Terdapat tujuh indikator persepsi konsumen yang diteliti, meliputi flash sale belanja online merupakan kesepakatan harga yang sangat menguntungkan konsumen, flash sale belanja online benar-benar menawarkan harga produk yang murah, produk yang ditawarkan pada saat flash

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5

Shageev, D. A., and O. G. Markin. "Development of the technique for selecting effective projects based on the modified AHP through the expansion of the criteria base and the apparatus of mathematical statistics." Proceedings of the Voronezh State University of Engineering Technologies 84, no. 3 (2023): 368–79. http://dx.doi.org/10.20914/2310-1202-2022-3-368-379.

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The author continues a series of publications in the subject area of the first generation modifications of the Analytic Hierarchy Process (AHP) method for the effective project selection technique. The long term aim of the research is to develop this technique to the qualitatively new and universal states to be further transformed into methodology. The research results are presented. A new concept of “Supermarket” extends the criteria basis of the core in the technique providing a possibility to take into account conventionally unlimited number of any criteria in multilevel hierarchy. The firs

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6

Kratochvíl, Petr. "The determination of factors in linear models of factor analysis." Applications of Mathematics 35, no. 5 (1990): 350–55. http://dx.doi.org/10.21136/am.1990.104416.

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7

Budi S, Surawan Setya. "PENGARUH INPUT PROSES RELATIONSHIP MARKETING TERHADAP OUTPUT PROSES RELATIONSHIP MARKETING." Kajian Bisnis STIE Widya Wiwaha 27, no. 2 (2019): 190–206. http://dx.doi.org/10.32477/jkb.v27i2.349.

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This research use relationship marketing teory which applied 4 factor of input process understanding customer expectations, building service partnerships, empowiring employers, and total quality management, and output relationship marketing process: customer satisfaction and customer layalty. The objective of this research is to find out wich factors of input process that has more impact on the output process in relationship marketing. There are 60 trusted correspondencea from Grand Inna Malioboro Hotel customer whom at least have been stayed at the hotel three times. The method of collecting

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8

S, Surawan Setya Budi. "PENGARUH INPUT PROSES RELATIONSHIP MARKETING TERHADAP OUTPUT PROSES RELATIONSHIP MARKETING STUDI KASUS GRAND INNA MALIOBORO HOTEL & CONVENTION." Kajian Bisnis Sekolah Tinggi Ilmu Ekonomi Widya Wiwaha 27, no. 2 (2019): 190–206. http://dx.doi.org/10.32477/jkb.v27i2.62.

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This research use relationship marketing teory which applied 4 factor of input process understanding customer expectations, building service partnerships,empowiring employers, and total quality management, and output relationship marketing process: customer satisfaction and customer layalty. The objective of this research is to find out wich factors of input process that has more impact on the output process in relationship marketing. There are 60 trusted correspondencea from Grand Inna Malioboro Hotel customer whom at least have been stayed at the hotel three times. The method of collecting d

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9

Dr.G.Kalaivanan, Dr G. Kalaivanan, and B. Ussaima B.Ussaima. "Factors Attracting Children to View TV Commercials - A Study Using Factor Analysis." Indian Journal of Applied Research 4, no. 6 (2011): 71–73. http://dx.doi.org/10.15373/2249555x/june2014/21.

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10

Pattnaik, Sudhanshu. "An Empirical Investigation into the Factors Influencing While Purchasing Car in India-A Confirmatory Factor Analysis." Journal of Advanced Research in Dynamical and Control Systems 11, no. 10-SPECIAL ISSUE (2019): 404–10. http://dx.doi.org/10.5373/jardcs/v11sp10/20192821.

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11

Tavasoli, Azin, Benjamin B. Gelman, Christina M. Marra, et al. "Increasing Neuroinflammation Relates to Increasing Neurodegeneration in People with HIV." Viruses 15, no. 9 (2023): 1835. http://dx.doi.org/10.3390/v15091835.

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Background: HIV infection causes neuroinflammation and immune activation (NIIA) and systemic inflammation and immune activation (SIIA), which in turn drive neurodegeneration (ND). Cross-sectionally, higher levels of NIIA biomarkers correlate with increased biomarkers of ND. A more convincing confirmation would be a longitudinal demonstration. Methods: PWH in the US multisite CHARTER Aging project were assessed at a baseline visit and after 12 years using standardized evaluations. We measured a panel of 14 biomarkers of NIIA, SIIA, and ND in plasma and CSF at two time points and calculated chan

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12

Majumdar, Dr Kakali. "Factor Analysis and Business Research." Indian Journal of Applied Research 1, no. 6 (2011): 151–54. http://dx.doi.org/10.15373/2249555x/mar2012/52.

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13

Soewin, E., and T. Chinda. "Factors affecting construction performance: exploratory factor analysis." IOP Conference Series: Earth and Environmental Science 140 (April 2018): 012102. http://dx.doi.org/10.1088/1755-1315/140/1/012102.

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14

Jun Li and Dacheng Tao. "Exponential Family Factors for Bayesian Factor Analysis." IEEE Transactions on Neural Networks and Learning Systems 24, no. 6 (2013): 964–76. http://dx.doi.org/10.1109/tnnls.2013.2245341.

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15

Dykema, Kenneth J., Allan M. Sinclair, and Roger R. Smith. "Values of the Pukánszky invariant in free group factors and the hyperfinite factor." Journal of Functional Analysis 240, no. 2 (2006): 373–98. http://dx.doi.org/10.1016/j.jfa.2006.03.026.

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16

Gurčík, Ľ., and V. Jančíková. "Factor analysis of owners equity effectiveness." Agricultural Economics (Zemědělská ekonomika) 48, No. 5 (2012): 229–32. http://dx.doi.org/10.17221/5308-agricecon.

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The paper shows methodical procedure and results of factor analysis of owners equity effectiveness in form of quantification and determination of analytical indicators of their pyramidal system. The analysis is realised through comparison of aggregated values of two groups of enterprises (per 30 each group) for the period 1998&ndash;2000. First group of enterprises is in the first third of soil price groups in Slovakia (cheapest soil) and the second group in the third of price group of the most expensive soil.

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17

Álvarez Orozco, Dolores Guadalupe, Verónica Esperanza Ruiz Domínguez, and Nidia Isela Ramírez Manjarrez. "Codependencia laboral: análisis factorial confirmatorio." Investigación & Desarrollo 30, no. 02 (2022): 167–90. http://dx.doi.org/10.14482/indes.30.2.158.7.

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El objetivo de esta investigación es validar un instrumento para medir la codependencia laboral, el método que se implementó fue un enfoque cuantitativo, de diseño no experimental transeccional, utilizando un análisis factorial confirmatorio basado en ecuaciones estructurales. Los resultados, mostraron que el modelo presentó un ajuste adecuado NC =1.86; ?=0.000; NFI=.979; IFI=.990; CFI=.990; MFI=.925 Y RMSEA=.68, se concluye que los factores relacionados con la falta de confianza y los comportamientos abusivos son los elementos que describen la codependencia en el ámbito laboral.

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18

Raghuvanshi, Monika. "Attitude Exploration Using Factor Analysis Technique." unibulletin 5, no. 1-2 (2016): 13–25. http://dx.doi.org/10.22521/unibulletin.2016.512.2.

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19

Maman, Abdurrohman, and Marsus Soffan. "Factor Analysis for Slow Budget Realization." INTERNATIONAL JOURNAL OF INNOVATION AND ECONOMIC DEVELOPMENT 3, no. 1 (2017): 28–50. http://dx.doi.org/10.18775/ijied.1849-7551-7020.2015.31.2002.

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The government of Indonesia has long experienced an uneven pattern of budget realization. Our budget realization is characterized by small absorption in the first three-quarters and then piled up in the last quarter. An increase in spending at the end of the year eventually led to the quality of work on the national economy, which is not considered optimal. Through factor analysis, the researchers reviewed what factors are causing slow realization of the budget, especially for spending unit in the working area of KPPN Jakarta II. Several studies have been conducted to determine the problem, in

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20

Jagadish, Mohan, and Tiwari Dr.Sushil. "INVESTIGATING THE CUSTOMER BUYING BEHAVIOR OF FABRIC PRODUCTS IN INDIA." International Journal of Social Sciences & Economic Environment 5, no. 2 (2020): 20–24. https://doi.org/10.53882/IJSSEE.2020.0502003.

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<strong><em>ABSTRACT</em></strong> <strong><em>Purpose:</em></strong><em> The purpose of this study is to understand the variables affecting the consumers while purchasing the products and to identify whether the purchase of theproducts creates or disappointment leading to affinity towards handloom products.</em> <strong><em>Design/Research Methodology/approach: </em></strong><em>Data were collected from 251handloom product customers in Bhopal through a questionnaire and collected data is analysed with the help of Percentage analysisand Factor analysis</em><em>. </em> <strong><em>Findings:</em

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21

M, Deepan, Deepa N, Rohini A, Malarkodi M, and Indumathi VM. "Factors influencing mutual fund investment decisions-factor analysis." International Journal of Chemical Studies 8, no. 1 (2020): 2106–9. http://dx.doi.org/10.22271/chemi.2020.v8.i1ae.8578.

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22

Le, Thu, Daniel Bolt, Eric Camburn, Peter Goff, and Karl Rohe. "Latent Factors in Student–Teacher Interaction Factor Analysis." Journal of Educational and Behavioral Statistics 42, no. 2 (2017): 115–44. http://dx.doi.org/10.3102/1076998616676407.

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Classroom interactions between students and teachers form a two-way or dyadic network. Measurements such as days absent, test scores, student ratings, or student grades can indicate the “quality” of the interaction. Together with the underlying bipartite graph, these values create a valued student–teacher dyadic interaction network. To study the broad structure of these values, we propose using interaction factor analysis (IFA), a recently developed statistical technique that can be used to investigate the hidden factors underlying the quality of student–teacher interactions. Our empirical stu

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23

Parmet, Yisrael, Edna Schechtman, and Michael Sherman. "Factor Analysis Revisited – How Many Factors are There?" Communications in Statistics - Simulation and Computation 39, no. 10 (2010): 1893–908. http://dx.doi.org/10.1080/03610918.2010.524332.

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24

Chen, Dachuan, Wenqi Lu, and Siyu Xie. "High frequency factor analysis with partially observable factors." Journal of Econometrics 251 (September 2025): 106058. https://doi.org/10.1016/j.jeconom.2025.106058.

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25

Hong, Soo-Young. "Kinetics Comparison Analysis of X-Factor and O-Factor according to Long Iron Swing Motion of Golf Skilled and UnSkilled." Korean Journal of Sports Science 27, no. 6 (2018): 1083–94. http://dx.doi.org/10.35159/kjss.2018.12.27.6.1083.

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26

Devasena, Dr S. Valli. "Physical Evidence –A Part of Customer Satisfaction An Analysis Using Factor Analysis." Indian Journal of Applied Research 3, no. 12 (2011): 87–90. http://dx.doi.org/10.15373/2249555x/dec2013/23.

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27

Liew, Sharifah, Rizati Hamidun, and Azhar Hamzah. "Factors that cause anger among motorcyclists: exploratory factor analysis." International Journal of Public Health Science (IJPHS) 11, no. 3 (2022): 893. http://dx.doi.org/10.11591/ijphs.v11i3.21079.

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Anger arising while riding a motorcycle is becoming a common problem on the road and it may be caused by many factors. The main objective of this study is to examine factors that could provoke anger among motorcyclists while riding. This study was based on self-reported questionnaires and comprised of 407 motorcyclists who owned valid riding licenses. exploratory factor analysis (EFA) indicated that the sample fit was suitable for factor analysis. In total, eight factors (unsafe or inappropriate actions, rude or sluggish actions, road conditions and design, police or enforces presence, illegal

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28

Milošević, Isidora, Ivan Mihajlović, and Anđelka Stojanović. "Dominant factors of SMEs failure: Multigroup confirmatory factor analysis." Serbian Journal of Management 14, no. 2 (2019): 345–60. http://dx.doi.org/10.5937/sjm14-23536.

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29

Kukreja, Vinay, Sakshi Sakshi@chitkara.edu.in, Amandeep Kaur, and Arun Aggarwal. "What Factors Impact Online Education? A Factor Analysis Approach." Journal of Engineering Education Transformations 34 (January 31, 2021): 365. http://dx.doi.org/10.16920/jeet/2021/v34i0/157180.

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30

Lipovetsky, Stan. "Factor analysis by limited scales: which factors to analyze?" Journal of Modern Applied Statistical Methods 16, no. 1 (2017): 233–45. http://dx.doi.org/10.22237/jmasm/1493597520.

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31

Bandalos, Deborah L. "Factors Influencing Cross-Validation of Confirmatory Factor Analysis Models." Multivariate Behavioral Research 28, no. 3 (1993): 351–74. http://dx.doi.org/10.1207/s15327906mbr2803_3.

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32

Ramirez, David, Ignacio Santamaria, Louis L. Scharf, and Steven Van Vaerenbergh. "Multi-Channel Factor Analysis With Common and Unique Factors." IEEE Transactions on Signal Processing 68 (2020): 113–26. http://dx.doi.org/10.1109/tsp.2019.2955829.

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33

Tamimi, Nabil. "A second‐order factor analysis of critical TQM factors." International Journal of Quality Science 3, no. 1 (1998): 71–79. http://dx.doi.org/10.1108/13598539810196886.

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34

Windasari, Windasari, Karwanto Karwanto, Supriyanto Supriyanto, and Puji Setiani. "Factors Affecting Teacher Digital Competence : An Exploratory Factor Analysis." Jurnal Kependidikan: Jurnal Hasil Penelitian dan Kajian Kepustakaan di Bidang Pendidikan, Pengajaran dan Pembelajaran 8, no. 4 (2022): 1029. http://dx.doi.org/10.33394/jk.v8i4.6095.

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This study aims to analyze the factor affecting the teacher competence in mastering digital technology in classroom learning during face-to-face learning in elementary schools in Lamongan district. This study used a quantitative approach using exploratory factor analysis (EFA) techniques. EFA is used to determine indicators related to teacher competence in mastering digital technology. The population of this study were teachers in Lamongan district. The sample of this research is 60 respondents with a cluster sampling method. The research stages include 1) instrument development, 2) instrument

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35

Sharifah, Liew, Hamidun Rizati, and Hamzah Azhar. "Factors that cause anger among motorcyclists: exploratory factor analysis." International Journal of Public Health Science (IJPHS) 11, no. 3 (2022): 893~902. https://doi.org/10.11591/ijphs.v11i3.21079.

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Anger arising while riding a motorcycle is becoming a common problem on the road and it may be caused by many factors. The main objective of this study is to examine factors that could provoke anger among motorcyclists while riding. This study was based on self-reported questionnaires and comprised of 407 motorcyclists who owned valid riding licenses. exploratory factor analysis (EFA) indicated that the sample fit was suitable for factor analysis. In total, eight factors (unsafe or inappropriate actions, rude or sluggish actions, road conditions and design, police or enforces presence, illegal

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36

Adachi, Kohei. "SOME CONTRIBUTIONS TO DATA-FITTING FACTOR ANALYSIS WITH EMPIRICAL COMPARISONS TO COVARIANCE-FITTING FACTOR ANALYSIS ." Journal of the Japanese Society of Computational Statistics 25, no. 1 (2012): 25–38. http://dx.doi.org/10.5183/jjscs.1106001_197.

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37

Makhmanazarovna, Ravshanova Mukhayyo. "Skills required to perform two-factor econometric analysis." European International Journal of Pedagogics 5, no. 1 (2025): 52–53. https://doi.org/10.55640/eijp-05-01-10.

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In this article, the author provides information on the selection of factors, the implementation of correlation and regression analysis. The construction of an econometric model is shown step by step. Information is also provided on the stage of generating a regression equation using correlation coefficients and a system of normal equations.

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38

Boyanov, Petar. "IMPLEMENTATION OF FACTOR ANALYSIS IN THE OPTICAL MANIFACTURING." Journal Scientific and Applied Research 8, no. 1 (2015): 16–20. http://dx.doi.org/10.46687/jsar.v8i1.173.

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A model of factor analysis is developed in the process of designing of complex optical systems. Factor analysis is indispensable in designing of photometric and spectrophotometric optical-electronic devices which consist of entrance-scanning system by space, lens with inner focusing, collimator objective which ensure the entering of a parallel bundle of rays over a dispersing diffraction grate over a wave length, a chamber lens and respectively, a sensor. These and similar optical systems require higher degree of elimination of chromatic aberration, etc. which ensures good quality of the optic

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39

Dominguez-Lara, Sergio. "Una guía amigable de psicometría: análisis factorial exploratorio." Liberabit. Revista Peruana de Psicología 31, no. 1 (2025): e963. https://doi.org/10.24265/liberabit.2025.v31n1.963.

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40

Edwards, Noralee R., and Diana L. Mindrila. "Improving graduation rates: Legitimate practices and gaming strategies." education policy analysis archives 27 (April 15, 2019): 41. http://dx.doi.org/10.14507/epaa.27.4222.

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Accountability pressures faced by teachers and leaders may lead well-intentioned educators to engage in strategic reporting and operational practices to increase test scores, graduation rates, and other indicators of student success. Such practices are referred to as gaming behaviors. School district personnel attending a Georgia educational conference (N=146) reported a significant prevalence of two such practices – purging data for students enrolled for a short period of time and fabricating withdrawal forms in case of audit. Exploratory factor analysis yielded three categories of strategies

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41

G., Ramesh Pandi. "Attitude of Retailers towards Green Marketing Practices: Analysis through Factor Analysis and Cluster Analysis Techniques." International Journal of Psychosocial Rehabilitation 24, no. 5 (2020): 3595–608. http://dx.doi.org/10.37200/ijpr/v24i5/pr202068.

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42

Liu, Shuyang, Jiaye Wu, Yue Yue, and Yingqian Zhang. "Analysis of Factors Affecting the Hidden Costs of Construction Projects Factor Analysis." OALib 06, no. 08 (2019): 1–8. http://dx.doi.org/10.4236/oalib.1105665.

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43

Utami, Wikan Budi, Punaji Setyosari, Cholis Sa'dijah, and Henry Praherdhiono. "Analysis of factors that influence student engagement in mathematics learning." Perspektivy Nauki i Obrazovania, no. 2 (April 30, 2025): 257–69. https://doi.org/10.32744/pse.2025.2.17.

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Introduction. Student engagement in mathematics learning is a form of active student participation in mathematicslearning, both learning activities in mathematics class and outside mathematics class. Several studies state that studentengagement consists of cognitive, behavioural, emotional, and contextual aspects. Therefore, analyzing the four factorsrelated to student engagement is necessary. In addition, an instrument that comes from the four dimensions is neededto measure student engagement. This needs to be done because there has not been much research that focuses on thedevelopment of Stu

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44

Buvat, I., H. Benali, and R. Di Paola. "Statistical distribution of factors and factor images in factor analysis of medical image sequences." Physics in Medicine and Biology 43, no. 6 (1998): 1695–711. http://dx.doi.org/10.1088/0031-9155/43/6/023.

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45

R. Menaga, R. Menaga, and CHANDRASEKARAN S. CHANDRASEKARAN. S. "Adopting Marketing Strategies of Small Traders - From Factor Analysis." International Journal of Scientific Research 3, no. 6 (2012): 86–88. http://dx.doi.org/10.15373/22778179/june2014/32.

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46

Tao, Kunwang, Liang Wang, and Xinlin Qian. "Multi-factor Constrained Analysis Method for Geological Hazard Risk." International Journal of Engineering and Technology 8, no. 3 (2016): 198–201. http://dx.doi.org/10.7763/ijet.2016.v6.884.

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47

Tao, Kunwang, Liang Wang, and Xinlin Qian. "Multi-factor Constrained Analysis Method for Geological Hazard Risk." International Journal of Engineering and Technology 8, no. 3 (2016): 198–201. http://dx.doi.org/10.7763/ijet.2016.v8.884.

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48

Sophia R Peligrino, Maria. "Students Motivation Towards Science Learning: A Confirmatory Factor Analysis." International Journal of Science and Research (IJSR) 12, no. 1 (2023): 689–704. http://dx.doi.org/10.21275/sr201124091859.

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49

Huda Atma Dirgatama, Chairul. "Exploratory and confirmatory factor analysis of digital entrepreneur skills." Problems and Perspectives in Management 22, no. 2 (2024): 299–312. http://dx.doi.org/10.21511/ppm.22(2).2024.23.

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Research in the field of entrepreneurship has become an intriguing area for further investigation. In an era where digital advancements are ubiquitous, previous researchers have identified a gap: the lack of a specific instrument to identify digital entrepreneur skills. Therefore, this study aims to determine the constructs of students’ digital entrepreneur skills. The analysis techniques include confirmatory factor analysis (CFA), exploratory factor analysis (EFA), Pearson correlation, Kendall’s, Spearman’s, and Cronbach’s alpha. The study was conducted over five phases with 235 participants

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50

Harsanto, Cahyo, Isman Kadar, and Yossa Istiadi. "Factor analysis of waste management in Serang Regency, Indonesia." Indonesian Journal of Applied Environmental Studies 5, no. 2 (2024): 97–108. https://doi.org/10.33751/injast.v5i2.9829.

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Serang Regency, with an area of 1,467.35 km2 in 2020 had a population of 1,622,630 people. By referring to SNI 19-3983-1995, the waste capacity produced on average is 2.25 liters per person per day, so the potential waste in Serang Regency in 2020 is around 1,212,903.7 m3 /year, while the amount of waste that can be transported to the final waste processing site (or TPA) is 98,339 m3 . Based on this data, waste services in Serang Regency have only reached 7.37%, far from the target of the Serang District Regional Policy and Strategy (Jakstrada) of 74% as stated in the Serang Regency Regulation

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