Simple Additive Weighting as Decision Support System for Determining Employees Salary

 
 
 
  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract


    Employees are seen as one of the important company assets and need to be managed and developed to support the survival and achievement of corporate goals. One form of employee organization that can be done by the company is to provide the appropriate remuneration or salary payments for employees. Increase in salary greatly affects the motivation and productivity of employees in implementing and completing the work. To determine the magnitude of the salary increase, a system is needed that can support the decision making done by the manager. Utilization of decision support system using Simple Additive Weighting (SAW) method helps managers to make quicker and more accurate decision making. This method is chosen because it is able to select the best alternative from a number of alternatives that exist based on the criteria specified. The research is done by finding the weight value for each attribute then done ranking which will determine the optimal alternative.

     

     


  • Keywords


    Decision Support System, Employees, Simple Additive Weighting

  • References


      [1] R. Nasriyah, Z. Arham, and Q. Aini, “Profile matching and competency based human resources management approaches for employee placement decision support system (case study),” Asian J. Appl. Sci., vol. 9, no. 2, pp. 75–86, 2016.

      [2] C. Truss, A. Shantz, E. Soane, K. Alfes, and R. Delbridge, “Employee engagement, organisational performance and individual well-being: Exploring the evidence, developing the theory,” International Journal of Human Resource Management, vol. 24, no. 14, pp. 2657–2669, 2013.

      [3] J. Jasri, D. Siregar, and R. Rahim, “Decision Support System Best Employee Assessments with Technique for Order of Preference by Similarity to Ideal Solution,” Int. J. Recent Trends Eng. Res., vol. 3, no. 3, pp. 6–17, Mar. 2017.

      [4] R. Rahim, H. Nurdiyanto, A. S. Ahmar, D. Abdullah, D. Hartama, and D. Napitupulu, “Keylogger Application to Monitoring Users Activity with Exact String Matching Algorithm,” J. Phys. Conf. Ser., vol. 954, no. 1, 2018.

      [5] A. Putera, U. Siahaan, and R. Rahim, “Dynamic Key Matrix of Hill Cipher Using Genetic Algorithm,” Int. J. Secur. Its Appl., vol. 10, no. 8, pp. 173–180, Aug. 2016.

      [6] R. Rahim, M. Dahria, M. Syahril, and B. Anwar, “Combination of the Blowfish and Lempel-Ziv-Welch algorithms for text compression,” World Trans. Eng. Technol. Educ., vol. 15, no. 3, pp. 292–297, 2017.

      [7] R. Rahim, “Man-in-the-middle-attack prevention using interlock protocol method,” ARPN J. Eng. Appl. Sci., vol. 12, no. 22, pp. 6483–6487, 2017.

      [8] D. Siregar, D. Arisandi, A. Usman, D. Irwan, and R. Rahim, “Research of Simple Multi-Attribute Rating Technique for Decision Support,” J. Phys. Conf. Ser., vol. 930, no. 1, p. 012015, Dec. 2017.

      [9] A. Alesyanti, R. Ramlan, H. Hartono, and R. Rahim, “Ethical decision support system based on hermeneutic view focus on social justice,” Int. J. Eng. Technol., vol. 7, no. 2.9, pp. 74–77, 2018.

      [10] Y. Rossanty, D. Hasibuan, J. Napitupulu, M. Dharma, and T. Putra, “Composite performance index as decision support method for multi case problem,” Int. J. Eng. Technol., vol. 7, no. 2.9, pp. 33–36, 2018.

      [11] S. H. Sahir, R. Rosmawati, and R. Rahim, “Fuzzy model tahani as a decision support system for selection computer tablet,” Int. J. Eng. Technol., vol. 7, no. 2.9, pp. 61–65, 2018.

      [12] T. Simanihuruk et al., “Hesitant Fuzzy Linguistic Term Sets with Fuzzy Grid Partition in Determining the Best Lecturer,” Int. J. Eng. Technol., vol. 7, no. 2.3, pp. 59–62, 2018.

      [13] M. D. T. P. Nasution et al., “Decision support rating system with Analytical Hierarchy Process method,” Int. J. Eng. Technol., vol. 7, 2018.

      [14] C. H. Primasari, R. Wardoyo, and A. K. Sari, “Integrated AHP, Profile Matching, and TOPSIS for selecting type of goats based on environmental and financial criteria,” Int. J. Adv. Intell. Informatics, vol. 4, no. 1, pp. 28–39, Mar. 2018.

      [15] N. Kurniasih, A. S. Ahmar, D. R. Hidayat, H. Agustin, and E. Rizal, “Forecasting Infant Mortality Rate for China: A Comparison Between α-Sutte Indicator, ARIMA, and Holt-Winters,” J. Phys. Conf. Ser., vol. 1028, no. 1, p. 012195, 2018.

      [16] A. S. Ahmar, “A Comparison of α-Sutte Indicator and ARIMA Methods in Renewable Energy Forecasting in Indonesia,” Int. J. Eng. Technol., vol. 7, no. 1.6, pp. 20–22, 2018.

      [17] A. Rahman and A. S. Ahmar, “Forecasting of primary energy consumption data in the United States: A comparison between ARIMA and Holter-Winters models,” in AIP Conference Proceedings, 2017, vol. 1885.

      [18] A. S. Ahmar et al., “Modeling Data Containing Outliers using ARIMA Additive Outlier (ARIMA-AO),” J. Phys. Conf. Ser., vol. 954, 2018.

      [19] D. U. Sutiksno, A. S. Ahmar, N. Kurniasih, E. Susanto, and A. Leiwakabessy, “Forecasting Historical Data of Bitcoin using ARIMA and α-Sutte Indicator,” J. Phys. Conf. Ser., vol. 1028, no. 1, p. 012194, 2018.

      [20] A. S. Ahmar, “A comparison of α-Sutte Indicator and ARIMA methods in renewable energy forecasting in Indonesia,” Int. J. Eng. Technol., vol. 7, 2018.

      [21] Surahman, A. Viddy, A. F. O. Gaffar, Haviluddin, and A. S. Ahmar, “Selection of the best supply chain strategy using fuzzy based decision model,” Int. J. Eng. Technol., vol. 7, no. 22, pp. 117–121, 2018.

      [22] Haviluddin, F. Agus, M. Azhari, and A. S. Ahmar, “Artificial Neural Network Optimized Approach for Improving Spatial Cluster Quality of Land Value Zone,” Int. J. Eng. Technol., vol. 7, no. 2.2, pp. 80–83, 2018.

      [23] A. Indahingwati, M. Barid, N. Wajdi, D. E. Susilo, N. Kurniasih, and R. Rahim, “Comparison Analysis of TOPSIS and Fuzzy Logic Methods On Fertilizer Selection,” Int. J. Eng. Technol., vol. 7, no. 2.3, pp. 109–114, 2018.

      [24] U. Khair, H. Fahmi, S. Al Hakim, and R. Rahim, “Forecasting Error Calculation with Mean Absolute Deviation and Mean Absolute Percentage Error,” J. Phys. Conf. Ser., vol. 930, no. 1, p. 012002, Dec. 2017.

      [25] E. Azimirad and J. Haddadnia, “Target threat assessment using fuzzy sets theory,” Int. J. Adv. Intell. Informatics, vol. 1, no. 2, pp. 57–74, Aug. 2015.

      [26] H. Hamdani and R. Wardoyo, “A review on fuzzy multi-criteria decision making land clearing for oil palm plantation,” Int. J. Adv. Intell. Informatics, vol. 1, no. 2, pp. 75–83, Jul. 2015.

      [27] I. Kaliszewski and D. Podkopaev, “Simple additive weighting - A metamodel for multiple criteria decision analysis methods,” Expert Syst. Appl., vol. 54, pp. 155–161, 2016.

      [28] A. Pranolo and S. M. Widyastuti, “Simple Additive Weighting Method on Intelligent Agent for Urban Forest Health Monitoring,” in 2014 INTERNATIONAL CONFERENCE ON COMPUTER, CONTROL, INFORMATICS AND ITS APPLICATIONS (IC3INA), 2014, pp. 132–135.

      [29] N. Nurmalini and R. Rahim, “Study Approach of Simple Additive Weighting For Decision Support System,” Int. J. Sci. Res. Sci. Technol., vol. 3, no. 3, pp. 541–544, 2017.

      [30] I. Tahyudin, R. Rosyidi, A. S. Ahmar, and Haviluddin, “Comparison of the Simple Additive Weighting (SAW) with the Technique for Others Reference by Similarity to Ideal Solution (TOPSIS) methods,” Int. J. Eng. Technol., vol. 7, no. 2.2, pp. 87–89, 2018.

      [31] A. Aljuaidi, “Decision support system analysis with the graph model on non-cooperative generic water resource conflicts,” Int. J. Eng. Technol., vol. 6, no. 4, p. 145, Oct. 2017.

      [32] J. Shang, P. R. Tadikamalla, L. J. Kirsch, and L. Brown, “A decision support system for managing inventory at GlaxoSmithKline,” Decis. Support Syst., vol. 46, no. 1, pp. 1–13, 2008.

      [33] R. Rahim, I. Zulkarnain, and H. Jaya, “A review: search visualization with Knuth Morris Pratt algorithm,” in IOP Conference Series: Materials Science and Engineering, 2017, vol. 237, no. 1, p. 012026.

      [34] R. Rahim, A. S. Ahmar, A. P. Ardyanti, and D. Nofriansyah, “Visual Approach of Searching Process using Boyer-Moore Algorithm,” J. Phys. Conf. Ser., vol. 930, no. 1, p. 012001, Dec. 2017.

      [35] R. Ratnadewi, E. M. Sartika, R. Rahim, B. Anwar, M. Syahril, and H. Winata, “Crossing Rivers Problem Solution with Breadth-First Search Approach,” in IOP Conference Series: Materials Science and Engineering, 2018, vol. 288, no. 1.

      [36] R. Rahim et al., “Block Architecture Problem with Depth First Search Solution and Its Application,” J. Phys. Conf. Ser., vol. 954, no. 1, p. 012006, 2018.

      [37] F. Haswan, “Decision Support System For Election Of Members Unit Patients Pamong Praja,” Int. J. Artif. Intell. Res., vol. 1, no. 1, p. 21, Jun. 2017.

      [38] S. H. Zanakis, A. Solomon, N. Wishart, and S. Dublish, “Multi-attribute decision making: A simulation comparison of select methods,” Eur. J. Oper. Res., vol. 107, no. 3, pp. 507–529, 1998.


 

View

Download

Article ID: 14698
 
DOI: 10.14419/ijet.v7i2.12.14698




Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.