The Influence of Leadership Style and Work Motivation on Employee Performance
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Employee, Leadership Style, Work Motivation
Abstract
This study aims to determine and analyze the effect of leadership style and work motivation on employee performance at the Regional Financial Management Agency, Sidenreng Rappang Regency. The analytical method used is Quantitative Analysis, namely data analysis in the form of numbers in the discussion, through statistical calculations based on the answers to the questionnaires from the respondents. The results of the calculation of the score or value are then used in statistical analysis carried out with the help of the SPSS program to prove the relationship and influence between research variables, using the following data test; Validity Test, Reliability Test, Classical Assumption Test and Regression Analysis; Y = a + b1 X1 + b2X2 Where :Y: Employee Performance, X1: Leadership style, X2: Work Motivation, a: Constants, b1b2: Regression Coefficient The results showed that: The results of hypothesis testing has proven that there is an influence between motivation and employee performance. Tests prove that motivation has a positive influence on employee performance. Judging from the calculations that have been done, the t-count coefficient is 1.902 with a significance level of 0.064. The significance level is greater than 0.05, which means that the hypothesis in this study rejects Ha and accepts Ho. The results of hypothesis testing have proven that there is an influence between leadership style and employee performance. Tests prove that leadership style has a positive influence on employee performance. Judging from the calculations that have been done, the coefficient value of t count is 2.538 with a significance level of 0.015. The yield significance level of 0.015 is smaller than 0.05, thus Ha is accepted and Ho is rejected. Motivation has the strongest influence on employee performance.
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Bayomie, O. S., Kandeel, H., Shoeib, T., Yang, H., Youssef, N., & El-Sayed, M. M. H. (2020). Novel approach for effective removal of methylene blue dye from water using fava bean peel waste. Scientific Reports, 10(1), 7824. https://doi.org/10.1038/s41598-020-64727-5
Biswas, P. P., Suganthan, P. N., Wu, G., & Amaratunga, G. A. J. (2019). Parameter estimation of solar cells using datasheet information with the application of an adaptive differential evolution algorithm. Renewable Energy, 132, 425–438. https://doi.org/10.1016/j.renene.2018.07.152
Blanco-Melo, D., Nilsson-Payant, B. E., Liu, W.-C., Uhl, S., Hoagland, D., Møller, R., Jordan, T. X., Oishi, K., Panis, M., Sachs, D., Wang, T. T., Schwartz, R. E., Lim, J. K., Albrecht, R. A., & tenOever, B. R. (2020). Imbalanced Host Response to SARS-CoV-2 Drives Development of COVID-19. Cell, 181(5), 1036-1045.e9. https://doi.org/10.1016/j.cell.2020.04.026
Cai, R.-G., Pi, S., & Sasaki, M. (2019). Gravitational Waves Induced by Non-Gaussian Scalar Perturbations. Physical Review Letters, 122(20), 201101. https://doi.org/10.1103/PhysRevLett.122.201101
Cartenì, A., Di Francesco, L., & Martino, M. (2020). How mobility habits influenced the spread of the COVID-19 pandemic: Results from the Italian case study. Science of The Total Environment, 741, 140489. https://doi.org/10.1016/j.scitotenv.2020.140489
Chen, S., Arrouays, D., Leatitia Mulder, V., Poggio, L., Minasny, B., Roudier, P., Libohova, Z., Lagacherie, P., Shi, Z., Hannam, J., Meersmans, J., Richer-de-Forges, A. C., & Walter, C. (2022). Digital mapping of GlobalSoilMap soil properties at a broad scale: A review. Geoderma, 409, 115567. https://doi.org/10.1016/j.geoderma.2021.115567
Fegert, J. M., Vitiello, B., Plener, P. L., & Clemens, V. (2020). Challenges and burden of the Coronavirus 2019 (COVID-19) pandemic for child and adolescent mental health: A narrative review to highlight clinical and research needs in the acute phase and the long return to normality. Child and Adolescent Psychiatry and Mental Health, 14(1), 20. https://doi.org/10.1186/s13034-020-00329-3
Gielen, D., Boshell, F., Saygin, D., Bazilian, M. D., Wagner, N., & Gorini, R. (2019). The role of renewable energy in the global energy transformation. Energy Strategy Reviews, 24, 38–50. https://doi.org/10.1016/j.esr.2019.01.006
Hjorth, M. F., Blædel, T., Bendtsen, L. Q., Lorenzen, J. K., Holm, J. B., Kiilerich, P., Roager, H. M., Kristiansen, K., Larsen, L. H., & Astrup, A. (2019). Prevotella-to-Bacteroides ratio predicts body weight and fat loss success on 24-week diets varying in macronutrient composition and dietary fiber: Results from a post-hoc analysis. International Journal of Obesity, 43(1), 149–157. https://doi.org/10.1038/s41366-018-0093-2
Jones, E. R., Van Vliet, M. T. H., Qadir, M., & Bierkens, M. F. P. (2021). Country-level and gridded estimates of wastewater production, collection, treatment and reuse. Earth System Science Data, 13(2), 237–254. https://doi.org/10.5194/essd-13-237-2021
Kalluri, R., & LeBleu, V. S. (2020). The biology , function , and biomedical applications of exosomes. Science, 367(6478), eaau6977. https://doi.org/10.1126/science.aau6977
Liu, X., Zhu, X., Li, M., Wang, L., Tang, C., Yin, J., Shen, D., Wang, H., & Gao, W. (2019). Late Fusion Incomplete Multi-View Clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 41(10), 2410–2423. https://doi.org/10.1109/TPAMI.2018.2879108
Martins, F., Sofiya, L., Sykiotis, G. P., Lamine, F., Maillard, M., Fraga, M., Shabafrouz, K., Ribi, C., Cairoli, A., Guex-Crosier, Y., Kuntzer, T., Michielin, O., Peters, S., Coukos, G., Spertini, F., Thompson, J. A., & Obeid, M. (2019). Adverse effects of immune-checkpoint inhibitors: Epidemiology, management and surveillance. Nature Reviews Clinical Oncology, 16(9), 563–580. https://doi.org/10.1038/s41571-019-0218-0
Pant, M., Krovi, H., Towsley, D., Tassiulas, L., Jiang, L., Basu, P., Englund, D., & Guha, S. (2019). Routing entanglement in the quantum internet. Npj Quantum Information, 5(1), 25. https://doi.org/10.1038/s41534-019-0139-x
Shiva Kumar, S., & Himabindu, V. (2019). Hydrogen production by PEM water electrolysis – A review. Materials Science for Energy Technologies, 2(3), 442–454. https://doi.org/10.1016/j.mset.2019.03.002
Sung, H., Ferlay, J., Siegel, R. L., Laversanne, M., Soerjomataram, I., Jemal, A., & Bray, F. (2021). Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: A Cancer Journal for Clinicians, 71(3), 209–249. https://doi.org/10.3322/caac.21660
Suparmi, S., Mulder, P. P. J., & Rietjens, I. M. C. M. (2020). Detection of pyrrolizidine alkaloids in jamu available on the Indonesian market and accompanying safety assessment for human consumption. Food and Chemical Toxicology, 138, 111230. https://doi.org/10.1016/j.fct.2020.111230
Syn, N. L., Cummings, D. E., Wang, L. Z., Lin, D. J., Zhao, J. J., Loh, M., Koh, Z. J., Chew, C. A., Loo, Y. E., Tai, B. C., Kim, G., So, J. B.-Y., Kaplan, L. M., Dixon, J. B., & Shabbir, A. (2021). Association of metabolic–bariatric surgery with long-term survival in adults with and without diabetes: A one-stage meta-analysis of matched cohort and prospective controlled studies with 174 772 participants. The Lancet, 397(10287), 1830–1841. https://doi.org/10.1016/S0140-6736(21)00591-2
Wang, Z., Li, C., & Domen, K. (2019). Recent developments in heterogeneous photocatalysts for solar-driven overall water splitting. Chemical Society Reviews, 48(7), 2109–2125. https://doi.org/10.1039/C8CS00542G
Wong, H. Y., Mo, H. Y., Potenza, M. N., Chan, M. N. M., Lau, W. M., Chui, T. K., Pakpour, A. H., & Lin, C.-Y. (2020). Relationships between Severity of Internet Gaming Disorder, Severity of Problematic Social Media Use, Sleep Quality and Psychological Distress. International Journal of Environmental Research and Public Health, 17(6), 1879. https://doi.org/10.3390/ijerph17061879
Wortham, J. M., Lee, J. T., Althomsons, S., Latash, J., Davidson, A., Guerra, K., Murray, K., McGibbon, E., Pichardo, C., Toro, B., Li, L., Paladini, M., Eddy, M. L., Reilly, K. H., McHugh, L., Thomas, D., Tsai, S., Ojo, M., Rolland, S., … Reagan-Steiner, S. (2020). Characteristics of Persons Who Died with COVID-19—United States, February 12–May 18, 2020. MMWR. Morbidity and Mortality Weekly Report, 69(28), 923–929. https://doi.org/10.15585/mmwr.mm6928e1
Xing, H., Liu, L., Xu, J., & Nallanathan, A. (2019). Joint Task Assignment and Resource Allocation for D2D-Enabled Mobile-Edge Computing. IEEE Transactions on Communications, 67(6), 4193–4207. https://doi.org/10.1109/TCOMM.2019.2903088
Xue, J., Wu, T., Dai, Y., & Xia, Y. (2019). Electrospinning and Electrospun Nanofibers: Methods, Materials, and Applications. Chemical Reviews, 119(8), 5298–5415. https://doi.org/10.1021/acs.chemrev.8b00593
Yang, B., Chen, Y., & Shi, J. (2019). Reactive Oxygen Species (ROS)-Based Nanomedicine. Chemical Reviews, 119(8), 4881–4985. https://doi.org/10.1021/acs.chemrev.8b00626
Zhao, Z.-Q., Zheng, P., Xu, S.-T., & Wu, X. (2019). Object Detection With Deep Learning: A Review. IEEE Transactions on Neural Networks and Learning Systems, 30(11), 3212–3232. https://doi.org/10.1109/TNNLS.2018.2876865
Zhu, J., Chen, N., & Shen, C. (2020). A New Deep Transfer Learning Method for Bearing Fault Diagnosis Under Different Working Conditions. IEEE Sensors Journal, 20(15), 8394–8402. https://doi.org/10.1109/JSEN.2019.2936932
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