WASPAS Method for Defining a Content Creator

In the era of the Industrial Revolution 4.0, social media is very influential in marketing company products, therefore companies interested in using social media need the role of content creators and employees. This is because the selection of prospective employees for content creators is still manual, and the selection of employees who are still related to family leads to an objective selection. Information technology and decision support systems need to be used as a tool to determine the selection of quality content creation staff using the WASPAS method, a combination of the WSM and WPM methods. By assigning weights to each criterion and then conducting a ranking evaluation process, this method can be used to solve the "multi-criteria decision making" problem. The result of this research is to find content creators who meet the standards of the WASPAS analysis method.


INTRODUCTION
In the era of the Industrial Revolution 4.0, social media is currently very influential (Daniel et al., 2018) (Salman et al., 2016), and many companies are interested in using social media as a way to market products(McShane et al., 2019)(McShane et al., 2019), so it takes creative people to come. Create content, but what is happening now is that the content obtained is not in accordance with the company's wishes (McShane et al., 2019). The problem of content creator employees is due to the manual recruitment process and the selection of employees who are still connected with their families. Employee records itself is a process of finding, finding and attracting job applicants in a company or organization (Setiani, 2013). Therefore, information technology and decision support systems are needed as a tool to determine the selection of quality content creator employees. Like previous studies, a decision support system is a system specifically designed for semi-structured and unstructured problem decision-making processes. In order to properly achieve the objectives of the DSS, a method in the decision support system (namely the WASPAS method) can be used to assist this method, which is a combination of the WSM and WPM methods. This method can be used to solve MCDM (multi-criteria decision-making) problems. Previous research has proven that by using the WASPAS method to determine the weighted value of each criterion, then through the ranking process prospective employees can select prospective employees who meet the requirements.

METHODOLOGY
Decision Support System (DSS) is an interactive information system used to provide information, modeling, and data processing. This system functions in making decisions in both semistructured and unstructured situations(Kusrini M.Kom, n.d.) (Purwokerto et al., 2014) (Zavadskas et al., 2012). The Decision Support System states that the Decision Support System is a system that helps make decisions using data and models (Abdullah & Adawiyah, 2014

Research Article
Vol. 12 No.6 (2021), 2739-2748 providing information, modeling and manipulating data. This system is used for a problem in decision making in a semi-structured and unstructured situation. Basically, a Decision Support System is designed to support all stages of decision making, from identifying problems, selecting relevant data, determining the approach used in the decision-making process, to evaluating alternative choices. Decision support system (DSS) is part of a computerbased information which includes a knowledge-based system or knowledge management that is used as decision support in an organization or company.Decision Support Systems have the following objectives, to assist managers in making decisions to solve a structured problem. support the manager's judgment in making decisions and not try to replace the manager's position, increasing the effectiveness of manager's decision-making rather than its efficiency. In Decision Making, there are three stages that must be passed as follows: a. The tracing and detection stage of the problematic scope is in the process of problem recognition, the incoming data is processed and tested in order to identify the problem. b. The design stage is the process of tracing, developing, and analyzing alternative actions that can be taken. c. The stage of selecting among various alternative actions that may be carried out. The result or output of a Decision Support System is in the form of a decision from a problem being researched or discussed which can be used as a benchmark for a policy. In weighting, the weight is the value or value of a criterion indicator. There are things that need to be considered in the weighting of a decision support system, namely, the weighting sources of the criteria, the sub-criteria (indicators) the causes of a problem being discussed must come from the optional standards (standard standards) and the policy makers from the case studies (case studies) discussed. . There are several rules for weighting criteria in a decision support system, namely: a. The percentage approach. Has a value range of 0 to 100% with a record value of ∑ Wj = 100% b. 2. Fuzzy Logic Approach. Has a value range of 0 to 1 c. 3. Actual Value Approach. Has a value range of 0 to 10 or 0 to 100 with normalization ∑ Wj = 100% except for the Profile Matching method which has an sktusl value from 0 to 5

Weighted Aggregated Sum Product Assessment
Weighted Aggregated Sum Product Assessment (WASPAS) is a method that has an error rate which is a combination method from two sources commonly known as WMM, MCDM (Multi Criteria Decision Making) approaches and WPM (Weigth Product Models). The WASPAS method is a method used to reduce errors and determine estimates when selecting the highest and lowest scores. The WASPAS method is a unique combination of the WSM and WPM methods. WASPAS is used to solve various problems, such as decision making, evaluation, alternatives, etc [9][8] [18]. Following are the steps that must be completed using the Weighted Sum Product Evaluation (WASPAS) method, namely ( Where : Qi = Value from Q to i Xij W = Multiply the value of Xij by weight (w) 0.5 = Provision The alternative that has the highest Qi value is the best alternative.

3.
EXPERIMENTAL RESULT The following research methods used in this study are(Indriani & Warnilah, 2019):

Observation
In making observations, it is reviewed directly to companies that need a content creator. In these companies, analysis and observations are carried out how the previous system was in the selection of content creator employees, where the system there is still manual in selecting content creator employees.

Interview
After making observations, interviews are conducted with company leaders or related parties who need a system in selecting content creator employees. In Table 1. below shows the data obtained from companies that require content creators with the criteria used, the data are as follows:  Interview 10% = 0,1 Benefit Based on the data that has been obtained, conversion of each criterion is carried out so that the calculation process can be carried out into the WASPAS method. The following is a conversion table of the criteria used: a. Ethics Table 3. below explains the weight value of the Ethical criteria as follows:  c. Video Editing Mastery Table 5 explains the weight value of the Video Editing Mastery criteria as follows:  Based on the data above, it is necessary to evaluate each criterion with a criteria table in order to perform calculations. In table 10, the following is the data conversion result of alternative data.

Algorithm
The system algorithm is an explanation of the steps for solving problems in the design of a decision support system in Defining A Content Creator. This is done to increase the effective and efficient assessment. The following is a Flowchart of the WASPAS algorithm, which is as follows:

Analysis and Result
The following are the steps in completing the WASPAS method as follows: