Perangkingan Potensi Guru dalam Penentuan Calon Kepala Sekolah Menggunakan Metode TOPSIS

Efforts to increase the value of the quality of education for students as the next generation of the nation require teachers who have competence in providing education to students. The competence of a teacher can be assessed when a teacher has carried out his duties in accordance with the standard provisions he has. The ranking of potential teachers is used to motivate teachers to be active in carrying out each activity and is expected to have a positive effect on their work to face challenges in this era of globalization. The data that is processed for the ranking of teacher potential is the assessment data of elementary school teachers sourced from the korwildik of the Batang kapas sub-district. This ranking is based on several criteria and weights are determined. Furthermore, this ranking is processed using a system created by the researcher. This ranking uses a method called TOPSIS to assist researchers in ranking. The TOPSIS method is a multi-criteria decision support method with the principle that the chosen alternative must have the closest distance from the positive and negative ideal solutions. The results of ranking with the TOPSIS method are able to support the ranking decisions of potential teachers using predetermined criteria. So that the highest value is found in the 5th alternative with a value of 0.7321 and the lowest value is found in the 1st alternative with a value of 0.2218. The ranking of potential teachers has proven to be able to help the South Coast District Education and Culture Office, especially the korwildik of the Batang kapas sub-district in determining prospective school principals.

Sports Policy and Training Decision Support Method Based on Wireless Sensor Network

In recent years, the awareness of sports departments at all levels of society to promote sports through science and has been increasing, and the scientific decision-making and management of sports have been improved to a great extent. With the application of scientific decision-making combined with a real-time sports data monitoring network, the opponent’s advance information can be effectively observed during the game and reasonable decisions can be made to deal with the opponent’s offense. Therefore, high-level athletes appear to be more relaxed and calm in the game. It first requires the application of advanced information collection methods to obtain sports data quickly, in real time and at low cost, and extract information about athletes’ scientific management decision-making from massive data and then make scientific management decisions for sports training. The modern sports method is highly open, and big data mining also profoundly affects the relevant decision-making of sports training. How to design appropriate decision support tools to grasp the key points of the problem in sports information data and make reasonable and correct decisions is a problem that is closely watched by macro decision-makers and coaches at all levels. This article mainly introduces the training decision support method derived from data mining and intends to provide some technical directions for making scientific decisions in sports training. This paper proposes related algorithms of a training decision support method derived from data mining, including training effectiveness prediction model and decision tree algorithm, for the design of the training decision support method derived from data mining. Experimental data shows that the average error between the prediction of the effectiveness of the training method and the actual situation of the training decision support method in this paper is 0.913%, which is helpful for the management or coach to make decisions.

Preventing Return Fraud in Reverse Logistics—A Case Study of ESPRES Solution by Ethereum

With the rapid development of e-commerce services, online retail has evolved from multi-channel to omni-channel in order to provide customers with more services. However, reverse logistics services (returns and exchanges) have become the target of many fraudulent activities, causing a lot of economic losses for many online retail companies. The current challenge of the traditional countermeasure is it requires a lot of manpower and training resources. In this study, we propose ESPRES, a system that adopts blockchain technology to prevent fraudulent behavior in the process of returns and exchanges with the smart contract and multi-attribute decision-support method to help consumers choose a suitable payment program. A practical implication of this study is that by adopting blockchain technology, a great amount of manpower used on determining whether each return or exchange is fraudulent can be reduced since merchants can check the product ownership. In addition, due to the fact that the footprint of goods cannot be forged, it can also prevent counterfeit or parallel imports of goods.

Aplication of The SMARTER Method for The Selection of The Best Ambassador Brand

This study aims to provide convenience for the company's management to solve problems in the process of selecting the best Brand Ambassador in promoting cosmetic tools. The problem identified in this study is the large number of prospective Brand Ambassadors, causing the management to find it difficult to determine the best Brand Ambassador. In this study, the decision support method applied is SMARTER which can determine the ranking results in the final decision using the level of importance of each parameter. The results of this study conclude that the selection of the best Brand Ambassador who is ranked first is A5 (Lucky) with a value of 0.653108466

Perangkingan Potensi Guru dalam Penentuan Calon Kepala Sekolah Menggunakan Metode TOPSIS

Efforts to increase the value of the quality of education for students as the next generation of the nation require teachers who have competence in providing education to students. The competence of a teacher can be assessed when a teacher has carried out his duties in accordance with the standard provisions he has. The ranking of potential teachers is used to motivate teachers to be active in carrying out each activity and is expected to have a positive effect on their work to face challenges in this era of globalization. The data that is processed for the ranking of teacher potential is the assessment data of elementary school teachers sourced from the korwildik of the Batang kapas sub-district. This ranking is based on several criteria and weights are determined. Furthermore, this ranking is processed using a system created by the researcher. This ranking uses a method called TOPSIS to assist researchers in ranking. The TOPSIS method is a multi-criteria decision support method with the principle that the chosen alternative must have the closest distance from the positive and negative ideal solutions. The results of ranking with the TOPSIS method are able to support the ranking decisions of potential teachers using predetermined criteria. So that the highest value is found in the 5th alternative with a value of 0.7321 and the lowest value is found in the 1st alternative with a value of 0.2218. The ranking of potential teachers has proven to be able to help the South Coast District Education and Culture Office, especially the korwildik of the Batang kapas sub-district in determining prospective school principal

Combining Parcel Lockers with Staffed Collection and Delivery Points: An Optimization Case Study Using Real Parcel Delivery Data (London, UK)

Delivering parcels to collection and delivery points (CDPs) is often seen as a better option compared with home delivery. However, if the demand is inhomogeneous, either the parcel locker utilization or the service level (i.e., the number of parcels that can be delivered) is low. Either situation would reduce the financial viability. This paper compares two options to increase the utilization, namely: (i) modular lockers (i.e., numbers of lockers adjusted periodically depending on demand) and (ii) combining parcel lockers with staffed CDPs. The latter has the advantage of a low investment cost of staffed CDPs and a low cost per parcel of parcel lockers. Secondly, the paper calculates the optimal number of lockers at a staffed CDP, assuming that all parcels are placed in the staffed CDP if the parcel locker is full. This method was applied to data collected by a parcel delivery company in London. The advantage of using real world data over one year is that it includes seasonal and daily changes in the parcel demand. The decision support method accounts for parcels not being picked up by customers on the delivery day, returned deliveries, and the net present value (NPV) of the investment. This paper shows that having enough lockers for 100% of all parcels compared with 80% doubles the number of required parcel lockers because of the inhomogeneity of the demand. In addition, combining fixed lockers with staffed CDPs offers greater financial benefits compared with modular lockers in this case study.

An Improved Decision Support Method for Resilience Assessment Based on Multi-Viewpoint Modeling and Functional Analysis of Interconnected Systems

Critical infrastructures provide services that are essential to the functioning and well-being of society. Failure to provide these services is unacceptable. This is a problem when considering the unpredictable nature of the environment (leading to crisis, natural disasters, terrorist attacks) and internal failures. The concern is even greater due to the interconnected and interdependent nature of critical infrastructures, which might lead to failure propagation, causing domino and cascade effects. The resilience of a system is the ability to reduce the magnitude and/or duration of disruptive events or their consequences, allowing a satisfactory level of performance and quality of services. Improving critical infrastructures' resilience before any disruption occurs can reassure society's vital needs. The goal of the paper is to define an improved decision support method for resilience by combining resilience assessment and multi-viewpoint modeling methods.

Decision Support System Based on Fuzzy Logic for Assessment of Expected Corporate Income Performance

This study presents a decision-support method to estimate the next year performance of corporate Operating Income Margin (OIM). It is based on a unique combination of cross-section model and the rules-based evaluation mechanism. The estimate is done in terms of broad categories, and not precise numerical values. The model is constructed as follows: its dependent variable (OIM) is one year ahead vs. the corresponding explanatory variables. This structure of the model allows us to view explanatory variables as reflecting financial potential of corporations. The evaluation component consists of a set of rules designed to identify the companies whose “potential” clearly points to an opportunity to invest. For the method presented here to succeed, it is necessary to utilize a highly reliable modeling method, even if it is “Fuzzy”. We apply Soft Regression (SR), which is a Soft Computing modeling tool based on Fuzzy Logic, and utilize all available proxy variables by creating intervals of values. Advantages of utilizing SR, and the intervals’-based modeling are extensively discussed. Modeling results for five consecutive years are consistent and stable, thus indicating high degree of reliability. Testing indicates very high success rate for the stock market related domain, the lowest being 87.9%.

A Tool for the Evaluation of Energy-Environmental Retrofit Interventions on Opaque Walls Using ETICS

Buildings in Europe are the largest consumers of energy, since they are responsible for 40% of energy consumption and 36% of pollutant gas emissions. The energy efficiency, the consequential economic savings and the reduction of environmental impacts must necessarily consider the design of improvements that affect the opaque vertical envelope of a building. The vertical envelope generally constitutes the largest dispersing surface. In this paper, a comparative evaluation of different ETICS (External Thermal Insulation Composite System) solutions through the application of a multicriteria decision support method is proposed. The criteria at the basis of the procedure relate to the energy, environmental, indoor comfort, and economic aspects. Through the application to the case study, consisting of two types of vertical walls with reference to three different climate zones, the ETICS alternative that achieves the best compromise between the various evaluation criteria is highlighted and the solidity of the method itself is tested. The potential of the methodology in the analysis of the alternatives in adherence to individual subcriteria and the possibility of implementation with additional indicators as the needs change are also highlighted. The social impact is undoubtedly one of the expected effects of the application of the method, since a better performance of the building envelope leads to an increase in comfort and liveability of indoor spaces. Moreover, all studies aimed at increasing the performance of the building or parts of it, consequently, lead to greater accessibility by the most vulnerable members of society, in line with the principles of sustainability and inclusiveness of the United Nations 2030 Agenda.