https://esajournals.com/index.php/JDDDSS <p><em>Journal of Data-Driven Decision Support Systems</em> is an international scientific peer-reviewed open-access journal on the data science and technology of Decision Support Systems published biannually.</p> <p>JDDDSS is a research journal publishing original full-length research papers, reviews, and Letters to the Editor. The Journal is devoted to the advancement and dissemination of knowledge concerning wide scope by covering the engineering and science applications of soft computing and decision support systems.</p> en-US Journal of Data-Driven Decision Support Systems https://esajournals.com/index.php/JDDDSS/article/view/26 <p>The panel's output efficiency decreases daily due to the increase in pollution on the surface of the PV panel, which can affect the loads connected to it. For better operation and maintenance, the PV module needs continuous monitoring. Several methods are used for monitoring and continuous monitoring of PV panels, and based on the monitoring results, operators and users can get great help in the maintenance field. This article includes a comparative evaluation between clean and polluted PV panels, which has calculated the loss of their output efficiency in the presence of dust and pollution. In this evaluation, the condition of the solar panel in clean and polluted conditions has been subjected to a helpful review. The primary motivation for this evaluation is to obtain the minimum acceptable output current as the boundary current with the current limit, which can be used to design multiple applications to improve the solar panel's efficiency. In this evaluation, the difference in the intensity of the sun's radiation has been considered, and its effects on the board's output have been practically tested. The total efficiency loss has been calculated using mathematical relationships based on the maximum output power.</p> Abira Anzurat Sayor Rezeta Noroloh Darvazi Copyright (c) 2023 Journal of Data-Driven Decision Support Systems 2022-05-28 2022-05-28 2 001 https://esajournals.com/index.php/JDDDSS/article/view/27 <p>Today, with the advancement of technologies, especially technologies related to information and communication, a massive amount of data is being produced in communication and information networks. One of the necessities for the success of businesses, even on a small scale, is the ability to use from this information and data; managers of different enterprises know that collecting information and data from customers and audiences of a company is one of the factors needed for the growth and development of these companies. But this is only halfway; If the data is only collected and remains unused, the primary purpose of collecting this information has yet to be fulfilled. An important step that must be taken after collecting data and information is extracting knowledge from the news and making the data more tangible. Assembled, it helps derive rules and practical results. In this article, an attempt has been made to compare two widely used algorithms in the field of data mining, Bayes and Meta, which are in Weka Explorer data mining software, and to conclude which algorithm can have better results and performance in data mining.</p> Antone David Diama Katherine Copyright (c) 2022 Journal of Data-Driven Decision Support Systems 2022-05-28 2022-05-28 2 001