Komariyah Komariyah, Muhamad Muslihudin

DECISION MAKING SYSTEMS FOR THE PERFORMANCE MEASUREMENT OF THE COVID-19 TASK FORCE IN PAGELARAN DISTRICT USING THE COMPARISON OF THE SIMPLE ADDITIVE WEIGHTING (SAW) METHOD AND THE WEIGHTED PRODUCT (WP) METHOD

Introduction

Decision making systems for the performance measurement of the covid-19 task force in pagelaran district using the comparison of the simple additive weighting (saw) method and the weighted product (wp) method. Evaluate COVID-19 task force performance in Pagelaran District using decision systems. Compares Simple Additive Weighting (SAW) and Weighted Product (WP) methods.

Abstract

Coronavirus is a virus which originated in Wuhan, China because this virus was first discovered in Wuhan, China. The spread is very fast. According to the prevention manual, Coronavirus Disease (COVID-19) is clarified into 3, patients under surveillance, people under monitoring and people without symptoms. This virus entered Indonesia on March 2, 2020. In order to reduce the spread of the corona virus-19, the government is expected to be able to form a disciplined and best Covid-19 task force team. To determine the best task force team, it must follow the criteria which have been set with the best performance gets a reward or award. In measuring the performance of the Covid-19 task force towards the predetermined criteria, a decision-making system is used by using a comparison of the simple additive weighting method and the weighted product method, which in this method looks for the weighted summation of the performance branches on each alternative on each criterion on all attributes. The criteria for the productivity aspect describe supervision, socialization, and appeals. The criteria for service quality aspects explain the existence of information disclosure in conducting monitoring. The criteria for the quality aspect of human resources explain the direction and training in developing leadership. Responsiveness aspect criteria explain about the quick handling as well as health services and the provision of social assistance. The responsibility criteria explain the work procedures of the COVID-19 task force. The criteria for the accountability aspect explain the reporting of work and financial evaluations. The management aspect criteria describe project development. Criteria for field operation aspects explain the acceleration of handling and the capacity of health workers. By using these criteria and by using a comparison between the simple additive weighting (saw) and weighted product (wp) methods, it can be seen that the performance weight value of the COVID-19 task force in Pagelaran District, Pringsewu Lampung with the best results according to the specified criteria, is 92 and 0.14.

Review

This paper addresses a highly relevant and timely topic: the performance measurement of a COVID-19 task force, specifically in Pagelaran District. Given the critical role of such task forces in public health crises, evaluating their effectiveness is crucial for accountability and improvement. The study proposes a decision-making system utilizing a comparison of the Simple Additive Weighting (SAW) and Weighted Product (WP) methods to identify the best-performing task force team, offering a practical application of multi-criteria decision analysis in a real-world scenario. A significant strength of this work lies in its systematic approach to performance evaluation. The abstract outlines a comprehensive set of criteria, categorizing them into productivity, service quality, human resources, responsiveness, responsibility, accountability, management, and field operations, each with detailed sub-aspects. This granular breakdown demonstrates a thorough consideration of the various facets contributing to task force effectiveness. The comparison of SAW and WP methods is appropriate for handling multiple criteria and provides a robust framework for ranking or scoring alternatives, suggesting a methodical attempt to derive objective performance assessments. While the abstract effectively establishes the problem and proposed methodology, certain aspects warrant further elaboration in the full paper. The reported final performance values of "92 and 0.14" require clearer contextualization; it is unclear what these numbers represent, how they are derived from the respective SAW and WP methods, and how they contribute to determining the "best task force team" or evaluating a singular task force as implied by the title. Additionally, the process for establishing the weights for each criterion, the nature of the alternatives being compared (e.g., different task force teams, or the entire task force's performance against a benchmark), and the implications of using two different methods should be thoroughly discussed. Addressing these points will enhance the paper's clarity, interpretability, and overall impact.

Full Text

Comments

You need to be logged in to post a comment.