Decision Support System For Selection Research Articles

Sistem Informasi PPDB Dengan Menerapkan Metode Simple Additive Weight (SAW) Dalam Sistem Pendukung Keputusan Pemilihan Sekolah

This research proposes and implements a web-based New Student Admission Information System (PPDB) using the Simple Additive Weight (SAW) method as a decision support system for school selection. The case study was conducted at the Lidah Kulon I/464 Surabaya Elementary School. The background of this research is driven by the significant impact of information technology advancements in the education sector. Lidah Kulon I/464 Surabaya Elementary School, as an educational institution committed to achieving excellence, discipline, faith, science and technology (IPTEK), as well as environmental awareness, strives to reduce paper usage in the new student registration process by transitioning to a more efficient administrative information system. The results of the tests state that the system has succeeded in various aspects, including the use of the Certainty Factor Method, diagnosis menu, information menu, login menu, and others. The conclusion of this research is that the system has been implemented successfully, supporting the efficiency of the PPDB process, and providing easy access to users. System development recommendations for the future include flexibility without hard coding, more comprehensive user management, the development of a more advanced school selection system, more accurate entrance fee calculations, and considerations for seasonal factors and school promotions. Keyword: PPDB Information System, Simple Additive Weight (SAW), Method Student Registration, Efficiency Educational Administration

Developed analytic hierarchy process and multi criteria decision support system for wind farm site selection using GIS: A regional-scale application with environmental responsibility

As determined by empirical analysis, renewable energy sources account for less than 1.73 percent of the developing countries energy market. The western region of Iran, or province of Kermanshah, presents significant opportunities for power exports to neighboring country (Iraq). In this research, an appropriate location for wind farms in Western Iran is determined with the assistance of a combined method of Geographic Information Systems (GIS) and Multi-Criteria Decision Making (MCDM) description. Electrical, techno-economic, environmental, and geo-infrastructure aspects, as well as their respective sub-criteria, were subjected to a comprehensive analysis and weighting in this study. The Analytical Hierarchy Process (AHP) was utilized to achieve this result. The aforementioned conclusions were reached through an extensive examination of insightful interviews conducted with esteemed experts in the domain of wind energy. Significant suitability for the potential installation of large-scale wind turbines or wind farms is evident in six critical areas, encompassing more than 20 % of the evaluated region, according to the findings of this paper. Conversely, it was deduced that precisely 80 % of the areas examined were deemed inappropriate for such endeavors. The assessment yielded four locations that were deemed suitable, denoted as A, B, C, and D. The southern, western, and central regions of the province contain these locations. The proposed total capacity is 216 MW, which is determined by the combined surface areas of these regions (19 km2, 55 km2, 64 km2, and 40 km2, respectively). An anticipated reduction of 1,262,471 tons in greenhouse gas emissions is anticipated as a result of the implementation and substitution of the proposed wind farms for the gas turbine power plants that presently predominate in Iran's thermal power plant sector. The method used in this article can be extended to all cases of other faculties to measure the potential of wind farm resources.

Analysis and Development of a Decision Support System for Selection of Prospective KIP Scholarship Recipients

Global Institute of Technology and Business Campus (Global Institute) is one of the campuses that organizes the KIP (Kartu Indonesia Pintar) scholarship program. This program aims to increase access to education for children from disadvantaged families and provide them with financial support. The research methods used are needs analysis, system design, and prototype implementation. This research collects data from various sources, including personal data of prospective scholarship recipients, academic data, family income data, and other relevant factors. The data collected is then analyzed using appropriate decision making methods, such as the Analytical Hierarchy Process (AHP) and TOPSIS methods. A Decision Support System is an interactive platform that helps make decisions efficiently and effectively in the process by presenting alternatives resulting from data processing, information, and the design of interactive computer-based models or systems. This platform provides support to decision makers in utilizing data and models to overcome unstructured problems.

Decision Support System for Selection of Outstanding Students Using the AHP and SAW Methods

It is very important for outstanding students to be directed and guided to get coaching related to the development of each student's personal potential so that superior and quality students are created. The process of selecting outstanding students can get wrong decisions because the process of selecting outstanding students is based on subjectivity, this allows many selected outstanding students not to reach the desired standard and do not get the best candidates. Therefore, a decision support system was created that can carry out the calculation process for all selections for the selection of outstanding students. This final project will implement the AHP and SAW methods in forming a system. The stages are carried out by comparing feature weights with the AHP method. Then the next stage is to rank using the SAW method to get selected outstanding students. Of the 72 students who were selected from the school, they were then selected to become 20 outstanding students based on the highest-ranking order. Software testing is done by comparing the results of school calculations with system calculations. Based on the results of the tests carried out, an accuracy value of 80% was obtained.

Decision Support System For New Employee Selection Using AHP And TOPSIS

There are so many prospective workers with the same educational background, but not necessarily in accordance with the required company position and not necessarily they have the same expertise. To minimize the occurrence of errors, it can be done by making a decision-making system (DSS) to provide these recommendations. In this study, the Analytical Hierarchy Process (AHP) and the Technique For Order Preference by Similarity to Ideal Solution (TOPSIS) method were used to provide recommendations for prospective new employees. The steps taken are to compare the importance of each criterion weight with the AHP method. Then the ranking stage is carried out using the TOPSIS method to get recommendations for selected employees. The data used in this study is primary data in the form of 70 data on prospective employees from PT Hutama Jaya Perkasa. From the 70 data then selected to be 36 prospective employees based on the order of the highest ranking. Software testing is done by comparing the results of system calculations and the results of company calculations. Based on the test results obtained an accuracy value of 94.4%.

Decision Making System For Selection Of Prospective Scholarship Recipients Using The Saw (Simple Additive Waighting) Method At Vocational School Bina Negara Gubug

The selection system at Bina Negara Gubug Vocational School Jl. KH. Hasan Anwar No.9 Gubug currently processes data on the criteria for each student for each type of scholarship. It does not yet have a database system but uses a computerized system with Microsoft Excel, so there are often delays in the selection process in preparing the selection report for scholarship recipients. This research uses the Research and Development (R & D) development model by Borg and Gall with 6 steps of development, namely Research and Information Collecting, Planning, Develop Premilinary Form of Product, Premilinary Field Testing, Main Product Revision, Main Field Testing. The scholarship selection decision support system application product uses the SAW (Simple Additive Waighting) method. Visual Basic 6.0 development software and Microsoft Access database. This system can provide a useful solution for the decision-making system for selecting scholarship recipients for schools so that a better and faster selection can be achieved.

Decision Support System for Selection of Internet Services Providers using the ROC and WASPAS Approach

Along with the growth of the internet service provider industry, selecting an Internet Service Provider (ISP) has become an important decision to ensure optimal internet access. However, with so many ISP options available, consumers often face difficulties in choosing the service that best suits their needs. The aim of this research is to produce a decision support system that can help users choose the ISP that best suits their needs and preferences using the ROC (Rank Order Centroid) approach as a weighting technique and the WASPAS (Weighted Aggregated Sum Product Assessment) approach to determine the best alternative. The ROC approach is used to obtain criteria weights based on the ranking order of the importance of the criteria. On the other hand, the WASPAS method is used to determine the best alternative through weighted addition and multiplication, producing a final value that reflects the extent to which each alternative meets the specified criteria. The outcomes of the case study reveal a ranking of alternatives from highest to lowest scores, as follows: First Media (A2) achieving 0.8629, Indihome (A3) at 0.8416, MyRepublic (A5) with 0.7954, Biznet (A1) scoring 0.7844, and Oxygen (A4) at 0.7469. The usability testing yields an average score of 89%, suggesting that the system is apt for utilization, as it aligns with the functionalities users are seeking.

Responsible machine learning for United States Air Force pilot candidate selection

The United States Air Force (USAF) continues to be plagued by a chronic pilot shortage, one that could be exacerbated by an accompanying shortfall in the commercial airlines. As a result, efforts have increased to alleviate this shortage by finding methods to reduce pilot training attrition. We contribute to these efforts by setting forth a decision support system (DSS) for pilot candidate selection using modern machine learning techniques. In view of the recent Responsible Artificial Intelligence Strategy published by the United States Department of Defense, this research leverages interpretable and explainable machine learning methods to create traceable and equitable models that may be responsibly and reliably governed. These models are used to regress candidates’ average merit assignment selection system scores based on information available for selection and prior to training. More specifically, using data provided by the USAF from 2010 to 2018, this paper develops and analyzes multiple interpretable models based on Gaussian Bayesian networks, as well as multiple black-box models rendered explainable by SHAP values and conformal prediction. A preferred pair of interpretable and explainable models is selected and embedded within a DSS for USAF pilot candidate selection boards: the Air Force Pilot Applicant Selection System. The utilization of this DSS is explored, the analyses it enables are discussed, and relevant USAF policymaking issues are examined.

Decision Support System for Selection of The Best Doctor at Ahmad Brahim Hospital Using the Simple Additive Weighting (SAW) Method

The selection of the best doctors at the Ahmad Brahim hospital was not only done once, but the selection of the best health workers at the Ahmad Brahim hospital was also carried out, but the selection of the best health workers was still done manually by the health department. Therefore, to help speed up the research process, a website-based decision support system was created to select the best doctors to provide rewards with several methods that can be used. One of the methods used in making decisions is simple additive weighting (SAW) which is done by weighting each of the criteria used. Decision support website created using the PHP and MYSQL programming languages for data storage. This study has criterion 3, namely absence, attitude and diligence then have 7 alternatives, the 7 alternatives have 4 ratings 1 where the average assessment is the same as the absence score 0.45, the attitude value is 0.35 and the diligence value is 0.12 with a total value of 1 so those who get the first rank score are dr. Audi Pirade, dr. Kesatria Putra Abadi, dr. Nurfitri Rahmani Awaliyah and dr. Riska Ruswanti. Then the second rank is dr. Christi Angelia Arung Labi with an absence score of 0.45, an attitude value of 0.35 and a diligence value of 0.12 with a total of 0.92

Decision support system for selection of the best teacher at SD Muhammadiyah 18 Medan using the analytical hierarchy process method

Decision support system for selection of the best teacher at SD Muhammadiyah 18 Medan using the analytical hierarchy process method

Sistem Pendukung Keputusan Pemilihan Debt Collector Berprestasi Di PT. Wahana Ottomitra Multiartha Medan Menerapkan Metode SMARTER

An outstanding debt collector must have presence, honesty, teamwork and achievement to improve the debt collector's performance. Problems in selecting outstanding debt collectors at PT. Wahana Ottomitra Multiartha Medan is an election team that finds it difficult to carry out elections quickly and accurately. The decision making technique in the SMARTER (Simple Multi-Attribute Rating Technique Exploiting Ranks) method is based on the theory that each alternative consists of a number of criteria that have values ​​and each criterion has a weight that describes how important it is compared to other criteria. Application of the Simple Multi-Attribute Rating Technique Exploiting Rank method for selecting outstanding debt collectors at PT. Wahana Ottomitra Multiartha Medan provides an accuracy of 23% using the relative standard deviation formula. It is hoped that to overcome this, a Decision Support System for Selection of Outstanding Debt Collectors at PT was built. Wahana Ottomitra Multiartha Medan Implements the SMARTER Method which will be designed using Visual Basic 2008 and using MySQL. In the Visual Basic design, a calculation and ranking process will be produced

Penerapan Metode Simple Additive Pada Sistem Pendukung Keputusan Untuk Pemilihan Handphone

The choice of mobile phone is an important decision in today's information technology era. In this context, the application of the Simple Additive method in the decision support system (DSS) becomes relevant to assist users in choosing a mobile phone that suits their needs and preferences. The Simple Additive method provides a simple yet effective framework for combining diverse criteria for evaluating mobile options. This study aims to develop SPK based on the Simple Additive method to improve accuracy and efficiency in the decision-making process of mobile phone selection. Through data analysis and system testing, it is hoped that the results of this research can make a positive contribution to the development of decision support systems for mobile phone selection. The purpose of this study is to implement an Android-based decision support system to assist users in choosing a mobile phone that suits their needs. Data collection is in the form of interviews and literature studies. This Mobile Selection Decision Support System was built with the help of Simple Additive Weighting in choosing mobile phones based on user needs and MySQL as a data storage. This Decision Support System for Mobile Selection was tested using black box testing successfully and system validation got results that were in accordance with the brand and specifications of the Mobile Phone. This Mobile Selection Decision Support System is expected to make it easier for users to choose the mobile phone needed.

Decision Support System for Major Selection in Higher Education for Multimedia Graduate Students using Fuzzy Mamdani Logic

Students at the vocational high school level are indeed prepared to be able to work directly, but it does not rule out the possibility that vocational high school students can continue higher education such as universities. But the problem that will be faced again if students who graduate from vocational high schools choose to continue their education in college is what major they will take. One of the vocational high school majors, namely Multimedia, has a wide scope, so grade 3 vocational high school students who want to go to college have a dilemma in deciding on a major. This research applies the fuzzy logic mamdani to help make decisions for majors in higher education. This study is based on 5 input parameters, namely Komputer dan Jaringan Dasar, Desain Grafis Percetakan, Dasar Desain Grafis, Teknik Audio Visual, and Animasi. There are outputs of 5 majors in Teknik Komputer, Desain Komunikasi Visual, Animasi, TV dan Film, and Fotografi. The results of this research can make it easier and can provide support for grade 3 vocational high school students, especially the Multimedia department in choosing a major in higher education. The results of the decision support system with the highest student score data in Animasi will appear a recommendation score of 79.8 in the Animasi department, and on the highest student score data on the Komputer dan Jaringan Dasar, a recommendation score of 79.8 will appear in the Teknik Komputer major in accordance with the major taken and lived by the current student.

Application of Analytic Hierarchy Process and Simple Additive Weighting in Designing The Best Employee Selection Decision Support System at PT Pos Indonesia

The purpose of this study is to compare the best employee evaluation outcomes using the analytical hierarchy process (AHP) technique and simple additive weighting (SAW) method as a support system for best employee suggestions. The author employed four different approaches for gathering data for this study: literature studies, interviews, observation, and similar literature studies. The RAD paradigm is being used in the development of this decision support system (DSS). The unified modeling language, or UML, tool is used in this system development methodology. It's time to put the system into action after it has been designed and analyzed. The black box testing methodology will be used for the experiments. Based on the research results, it was found that this system was able to assist decision makers in providing employee assessments quickly and precisely according to the predetermined time, whereas previously managers were always late and exceeded the time limit when assessing employees. The output of this system is that it can provide direct reports to the employees being assessed to find out the results of the scores obtained and make decisions about selecting the best employees. A decision support system for employee performance assessment uses the PHP and MySQL programming languages as the database. AHP and SAW methods, rapid application development (RAD) system development methods, and system testing with black box testing.

Decision Support System Analysis of School Promotion Media Selection using MABAC, OCRA And CODAS Methods

School promotion is an activity to communicate educational products to consumers or prospective students. Promotional activities require strategic policies in order to maximize promotional results, therefore analysis of the selection of appropriate promotional media needs to be done. Multi-Attributive Border Approximation area Comparison, Operational Competitiveness Rating Analysis, COmbinative Distance-based Assessment in decision support system with case study at SMK Airlangga Balikpapan. MABAC, OCRA and CODAS are used in the calculation process that produces output in the form of promotional media ranking to be recommended to the school promotion team as a consideration for selecting the right promotional media. Alternative promotional media used in this research are brochures, posters, billboards, banners and newspaper advertisements. Based on the results of the research, the MABAC, OCRA and CODAS methods can be applied to the school promotion media selection decision support system and can produce output in the form of a priority ranking of school promotion media

The Application of Financial Management Concepts in Cafe Selection Decision Support Systems Using the SAW Method

A Cafe is a place to eat and gather with a more comfortable atmosphere, there are many cafes that exist and are developing in Seruyan district, giving rise to an increase in the economy and the government is expected to be able to help cafes in the Seruyan area, most cafes are managed by young people so that it can have a positive impact if they are in provide support from the government.
 Therefore the researcher created a decision support system to help related parties to choose the best cafe. This decision support system is designed to provide an objective picture of the cafes in Seruyan.
 The method used in this study is the SAW (Simple Additive Weighting) method, which is an SPK method used to select various objects that are used as the best alternative from the many existing alternatives, with the criteria used namely location, atmosphere, menu, price, service and cleanliness.
 With this decision-making system, it is hoped that it can help several parties, such as the tourism office and also the UMKM and industry cooperative services to become a source of reference if you want to develop SMEs and businesses in Seruyan District

Sistem Pendukung Keputusan Pemilihan Sampah Tempat Sementara di Kota Kupang menggunakan Metode Topsis

Temporary waste management in the city of Kupang is an urgent problem to ensure a clean and healthy environment. Selecting the right location for a temporary waste bin is an important step in efficient waste management. In this context, Decision Support Systems (DSS) can provide valuable assistance in the decision-making process. This research proposes a Decision Support System for Selection of Temporary Waste Bins using the TOPSIS Method. The TOPSIS method (Technique for Order of Preference by Similarity to Ideal Solution) is an effective method for overcoming multi-criteria decision-making problems. This system will integrate various factors such as distance to settlements, population density, accessibility, and other environmental factors to evaluate and select optimal temporary waste bins. This decision support system will provide stakeholders, including city governments, waste management authorities, and the community, with tools that can be used to make more informed decisions in determining the location of temporary waste bins. The results of the Decision Support System analysis will provide recommendations based on the level of preference for the specified criteria, enabling stakeholders to make more informed and sustainable decisions in city waste management. It is hoped that this research can help improve efficiency in temporary waste management in Kupang City and has the potential to become a model for other cities that face similar challenges in waste management.

Decision Support System for Student Exchange Selection in Support of Independent Campus using the MAUT and ROC Methods

Independent campus is an off-campus learning activity as an opportunity for students to hone skills in preparation for entering the world of work. One of the programs held is the exchange of students to be able to study on campuses or companies that join the Ministry of Education and Culture, Research and Technology. With the current independent campus program, almost all universities open up opportunities for students to register. However, because there are too many students who register, the campus has difficulty in choosing some students who can be accepted according to the criteria set by the party. For this reason, a Decision Support System is needed that applies the MAUT method along with the use of ROC to produce the best preference value. The calculation of several data samples resulted in the best final utility value in the selection of independent campus student exchanges in Alternative A2 with the best final utility value of 0.9700

SISTEM PENDUKUNG KEPUTUSAN SELEKSI CALON PENERIMA BEASISWA DI SEKOLAH TINGGI PENDIDIKAN ISLAM BINA INSAN MULIA YOGYAKARTA MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING (SAW)

Bina Insan Mulia Yogyakarta College of Islamic Education offers a scholarship program for underprivileged and outstanding students. To determine the prospective scholarship recipients, the Islamic Education College of Bina Insan Mulia Yogyakarta still uses the manual method by comparing the criteria data one by one that must be adjusted to the predetermined criteria, this causes the selection process to experience difficulties and data errors due to the number of registrants many.
 This research aims to build a Scholarship Recipient Selection Decision Support System by applying the Simple Additive Weighting (SAW) method in it. The research method used is the study of literature which aims to study and understand the basic theories of decision support systems and the theory of Simple Additive Weighting (SAW). To find out the problem under study is the interview method, to find out information data relating to the problem under study is a method of collecting data and to study documents related to the object of research is the method of documentation.
 The results of testing the performance of the Decision Support System application using the Simple Additive Weighting (SAW) method stated that this system is able to provide a ranking of scholarship recipients' recommendations in accordance with the criteria used. The conclusion of this study is that this system was built to help the Islamic Education College of Bina Insan Mulia Yogyakarta to select prospective scholarship recipients. The method applied in this system is able to provide a solution to the problem of selection of prospective scholarship recipients with a ranking model that matches the applicable criteria and the weights of those criteria.

Mobile Apps-Based Cosmetic Equipment Selection Decision Support System Use Simple Additive Weighting (SAW) Method

Currently, more and more types of cosmetic products are appearing on the market, thus making cosmetic users confused in choosing cosmetics that suit their skin type and usage. Not a few people who use cosmetics wrongly which has a lot of bad effects on their face and has to be touched up repeatedly. This application facilitates users with 5 types of skin types, lip types and types of use that can be selected to make it easier for users to choose cosmetics that suit their skin type and usage. The application was built with a Decision Support System (DSS) using the Simple Additive Weighting (SAW) method to make calculations for selecting the most appropriate Make Over cushion and lipstick product for the user. In this application, the user can enter their skin type and then the system will calculate using the SAW method to get the Make Over cushion and lipstick that is most suitable for the user. The final result of the system will display the Make Over cushion and lipstick and their description with the highest calculated value to the user. Based on testing, this application is able to display cushion and lipstick products whose compatibility with users reaches 98%.