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Journal : INFOKUM

SINGLE EXPONENTIAL SMOOTHING IN FORECASTING TOOLS AND MEDICINE STOCKS Revi Sesario; Tobias Duha; Agry Alfiah; Susatyo Adhi Pramono; Pandu Adi Cakranegara
INFOKUM Vol. 10 No. 4 (2022): October, computer, information and engineering
Publisher : Sean Institute

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Abstract

Problems that arise when acquiring equipment and pharmaceuticals include procurement delays caused by waiting for genuine data from the storage area, as well as surplus stock of various types of drugs. This is due to the fact that administrative documents are still kept in the traditional manner. In this article, we provide forecasting tool and medicine stock based on the demand ratio in order to overcome stock delays and surplus stock. Because of the needs (in the month of forecasting carried out and the amount of data held), single exponential smoothing with alpha 0.1 is utilized. The prediction findings are also considered accurate because the forecasting smoothing computation with an average error value of MAD (21,4), MSE (710,4), and MAPE (7%) was assessed as very good.
RECRUITMENT OF NEW EMPLOYEE USING SELECTION PROCESS FOR DETERMINING DECISIONS WITH THE PREFERENCE SELECTION INDEX METHOD Pandu Adi Cakranegara; Efendi; Aditya Wardhana; Tienni Mariana Simanjorang; Revi Sesario
INFOKUM Vol. 10 No. 4 (2022): October, computer, information and engineering
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (198.877 KB)

Abstract

The most important thing for companies is to hire new people who have the skills and qualities needed for the job or acceptance offered. The ability of a company to run well depends a lot on the quality of its employees. The issue of hiring people and getting the finest applicants can be overcome with the aid of decision-making procedures. In a recruitment process, there are many selection mechanisms in businesses with varying criteria. In this study, decision-makers are selecting candidates for employment based on specified criteria, including an intelligence test (C1), an interview test (C2), a test of skills and abilities (C3), an assessment of attitudes and behaviors (C4), and work experience (C5). The calculating approach employs the Preference Selection Index (PSI) method because it can be applied to situations with multiple criteria and attributes and does not require the decision maker to calculate the weights of the criterion. The 3 best option candidates for the employees with the greatest PSI value, which is PSI = 0.88186, are determined by the results of the final PSI method computation from 5 alternatives.