SISTEM PENGOLAHAN DATA MUTASI PEGAWAI PADA WAROENG SPESIAL SAMBAL MA SEMARANG DENGAN METODE SIMPLE MULTI ATTRIBUTE RATING TECHNIQUE

TitleSISTEM PENGOLAHAN DATA MUTASI PEGAWAI PADA WAROENG SPESIAL SAMBAL MA SEMARANG DENGAN METODE SIMPLE MULTI ATTRIBUTE RATING TECHNIQUE
AuthorMuhammad Soleh
AbstractABSTRACT

The era of the Industrial Revolution 4.0, the rapid development of technology has an important role, one of which is in processing data on the mutation of Waroeng Spesial Sambal Management employees in the Semarang Area. Mutations are needed for employees in order to improve employee competence, develop motivation, increase knowledge in work experience, quality of work processes, and productivity, and organizational efficiency. Employee mutation data processing uses the SMART method to manipulate data quickly and precisely and can be designed and organized to automatically receive and store input data, process it and produce output based on instructions that have been stored in memory. The ability of computers to process data at high speed makes computers more efficient for use in every field of work.The purpose of this research is to build a decision support system that applies the SMART (Simple Multi Attribute Rating Technique Exploiting Rank) method to provide recommendations to decision makers in processing employee mutation data that is in accordance with the criteria and is relevant and provides convenience. The results of this study state that the results of the value ranking are subject to predetermined conditions for each criterion so that the assessment for mutations is more objective. The work appraisal is based on criteria that have been determined for the maximum and minimum limits, employees will be declared MUTATED if the value is more than 46.9, then the employee is declared NOT MUTATED if the score is less than
46.9.
KeywordsSimple Multi Attribute Rating Technique (SMART), Decision Support System, PHP, MySQL.
Document
DownloadDownload File
Issn2302-0709
Doi-
Viewed277
Created At6 Des 2021 11.46.33