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The selection process for accepting new employees is one of the important stages in a company to ensure that the candidates accepted have qualifications that suit the company's needs. At WINMART, the selection process is still carried out manually, so it is less efficient and prone to errors. Therefore, a system is needed that can assist in more objective and efficient decision making. This Decision Support System (DSS) is designed to assist the selection process for recruiting new employees using the Simple Additive Weighting (SAW) method, which can assess several relevant criteria, such as work experience, education, skills and competency tests. This system was built on a web basis, so it can be easily accessed by parties involved in the selection process, such as HRD and managers. The SAW method was chosen because of its ability to convert various subjective criteria into more objective numerical scores, so that selection results can be more transparent and accountable. By using this system, it is hoped that it can increase efficiency, accuracy and transparency in the new employee selection process at WINMART, as well as facilitate decision making in selecting candidates who best suit the desired criteria.

Rice plants (Oryza Sativa L.) are the main staple food commodity in Indonesia, as most of the Indonesian population relies on rice as their primary food. One of the causes of low rice production in Indonesia is that farmers generally cultivate rice improperly, such as in land preparation or land selection. Land suitability in rice cultivation greatly affects crop productivity. A process that can support decisions regarding rice land suitability is the development of a Decision Support System (DSS) website using a combination of the Simple Additive Weighting (SAW) method and the Technique for Order Performance of Similarity to Ideal Solution (TOPSIS). This combination is performed by taking the average (µ) of the final results from the SAW and TOPSIS methods. The final scores of each method are calculated separately, and then the average (µ) of these two results is taken to obtain the final ranking of the alternatives. The data used to determine the suitability of rice land is based on five criteria: soil type, soil pH, rainfall, temperature, irrigation and water supply. The alternative data used in the study includes six alternatives: Sungai Kunjang, Sambutan, Samarinda Utara, Palaran, Loa Janan Ilir, and Samarinda Seberang. The aim of this research is to provide information on alternative solutions to farmers or farmer groups in determining rice land suitability. The results of the combination of the SAW and TOPSIS methods show that the alternative with the highest final score is Samarinda Utara (A3), with a final score of 0.7337. Meanwhile, the alternative with the lowest final score is Sambutan (A2), with a final score of 0.4402.

Career selection is an important process for students at Darussalam Gontor University (UNIDA) because it influences their academic development and future employment. However, many UNIDA students experience difficulties in determining suitable careers due to a lack of understanding of their psychological characteristics. This study aims to build a Decision Support System (DSS) for career recommendations for UNIDA students based on psychological test results using the Simple Additive Weighting (SAW) method. The psychological data used are non-clinical test results collected through a structured questionnaire from six respondents and converted into numerical scores. The research stages include determining criteria and weights, compiling a decision matrix, normalization process, calculating preference values, and ranking career alternatives using SAW. The career alternatives used consist of academics, corporate professionals, entrepreneurs, managers, and social/public services. The results show that the managerial career alternative obtained the highest preference value of 0.861, followed by entrepreneurs at 0.824, corporate professionals at 0.778, social/public services at 0.737, and academics at 0.703. These findings demonstrate that the SAW method is capable of providing objective and systematic career recommendations based on the psychological profiles of UNIDA students. This research is expected to assist UNIDA students and academics in making more informed career decisions tailored to individual characteristics

The Decision Support Sistem (DSS) for selecting exemplary teachers at SMP Negeri 2 Loli aims to assist the school in determining teachers who deserve to be recognized as exemplary teachers. The evaluation of exemplary teachers involves various criteria such as teaching performance, discipline, creativity, and communication skills with students. However, the selection process conducted manually tends to be subjective and time-consuming. Therefore, a sistem is needed to simplify and accelerate the selection process while producing objective and transparent results. This sistem is developed using the Simple Additive Weighting (SAW) method, which is one of the techniques in multi-criteria decision-making. The SAW method works by assigning weights to each predetermined criterion and calculating the weighted scores for each alternative (teacher). These weighted scores are then summed to determine the ranking order of teachers who meet the criteria as exemplary teacher candidates. The results of this study indicate that the implementation of the SAW method can produce a more structured, objective, and efficient exemplary teacher selection process. The sistem facilitates the school in conducting evaluations and decision-making, while also reducing the potential for errors that may occur during manual selection. Thus, this decision support sistem is expected to make a significant contribution to improving the quality and accuracy of exemplary teacher assessments at SMP Negeri 2 Loli.

The verification and validation process for land application data at the Southwest Sumba Regency Land Office has been carried out manually, which often results in delays, data inconsistencies, and the potential for errors in decision-making. These problems impact the low efficiency of public services and the accuracy of managed data. Therefore, this study aims to develop a Decision Support Sistem (DSS) that can assist the verification and validation process for land application data sistematically, quickly, and objectively. This sistem is built using the Simple Additive Weighting (SAW) method, which functions to determine the level of eligibility of an application based on several criteria, namely completeness of documents, land status, legality of ownership, suitability of applicant data, and dispute history. The sistem design process is carried out through several stages, including needs analysis, design, implementation, testing, and evaluation. The results show that the implementation of a SAW-based DSS can increase the efficiency of the verification process by up to 65%, and increase the accuracy of validation results by up to 90% compared to manual methods. This sistem provides automatic decision recommendations, thus assisting officers in assessing the eligibility of land applications in a transparent and consistent manner. Thus, this sistem has the potential to be an effective solution to support the digitalization of public services in the land sector in Southwest Sumba Regency.

The selection of recipients of the Single Tuition Fee (UKT) assistance at universities must be carried out with the principles of fairness, openness, and efficiency to ensure that the assistance is distributed appropriately. However, the manual selection process is often subjective and prone to error. Therefore, this study developed a decision support system based on the Simple Additive Weighting (SAW) method to assist the selection process of students eligible for UKT assistance more systematically and accurately. The SAW method was chosen because of its ability to process data involving various criteria to produce objective decisions. In this study, the criteria used for the selection of UKT assistance recipients include several aspects, such as the Cumulative Grade Point Average (GPA), parental income, number of dependents, non-academic achievements, distance of the student's residence from campus, active student status, and involvement in student organizations. Data from each criterion is then processed through a normalization stage to ensure uniformity of values and weighting based on their level of importance. After the normalization and weighting process, the next step is to calculate the preference value for each student. The results of the implementation of this system show that the SAW method can accurately rank student priorities, with a student named Selly receiving the highest preference score, 0.673. This indicates that the student in question meets the selection criteria with the best score. This developed system can support the UKT assistance selection process to be fairer and more efficient. By using the SAW method, subjective and manual errors in decision-making can be reduced, resulting in more objective and accurate decisions. In addition, this system also allows universities to evaluate UKT assistance recipients more transparently and precisely, which ultimately can increase public trust in the management of educational assistance at universities.

The problem of decision making for admitting new students at SMK Fajar Bogor is that they still use Microsoft Excel so they experience several obstacles and a lack of systematicity in decision making regarding new students at SMK Fajar Bogor.  This research aims to design an application to make the processing of prospective new students' grades easier and to design a more systematic decision-making application regarding the admission of new students to SMK Fajar Bogor. This research identifies the criteria for diploma grades, test scores, psychological test scores and zoning. The Simple Additive Weighting (SAW) method was used to design, develop and test a decision support system at the SMK Fajar Bogor school. This system is designed using the PHP programming language and MYSQL database. The results of the research are that the process of processing the grades of prospective new students becomes easier, decision making regarding the acceptance of new students at SMK Fajar Bogor becomes more systematic.

The problem faced by Kelurahan Kebagusan is that there is no structured system in determining the allocation of aid funds to the community, so the distribution process is often uneven and less targeted. So far, the determination of aid recipients is only based on subjective observations and manual assessments that have the potential to cause ineffectiveness in decision making. Therefore, a decision support system was designed to assist the kelurahan in prioritizing beneficiaries objectively and transparently. This system uses the Simple Additive Weighting (SAW) method, which allows the assessment process to be carried out based on the weights of several predetermined criteria, such as economic conditions, number of dependents, employment status, and home ownership. The result of this system development is a desktop-based application using the Java programming language, which is expected to help the kelurahan in managing data and performing calculations quickly and accurately, so that the allocation of aid funds can be more targeted and fair.   Keywords: Decision Support System, Simple Additive Weighting, Fund Allocation, Kebagusan Village.

The problem faced by PT. Dinda Holding Company (DHC) is that it has difficulty in determining the best employees from a number of employees with varying performance qualities. Until now, the selection process has been carried out manually, taking into account the subjective assessments of the owner or store manager, without a structured evaluation system. As a result, employee selection tends to be inconsistent and leads to dissatisfaction among both employees and the business owner. Additionally, selected employees do not always demonstrate optimal performance, which impacts service quality and the operational sustainability of the store. Therefore, a decision support system was designed to assist PT. Dinda Holding Company (DHC) in selecting the best employees objectively, quickly, and accurately. Employees are human resources used as a driving force in the business operations of a company. The company faces the challenge of maintaining its competitive edge, which requires data on the performance of employees with good performance. This system applies the Simple Additive Weighting (SAW) method to perform calculations and evaluations based on predetermined criteria. The result of this system development is a desktop-based application using the Java programming language and a MySQL database, which is expected to assist management in making more measurable and structured decisions.

The problem faced by Baking Daily Store is that there is no system that can be used to optimize supplier selection, which has only been done based on intuition and relationships. This has the potential to cause inefficiencies in supplier selection which have an impact on the availability of raw materials, product quality, and timeliness of delivery. Therefore, a decision support system was designed to help Baking Daily Store in choosing the best supplier objectively, quickly, and accurately. This system applies the Simple Additive Weighting (SAW) method to perform calculations and assessments based on predetermined criteria. The result of this system development is a desktop-based application using the Java programming language, which is expected to help management in making decisions in a more measurable and structured manner.

Quality health services are an important factor in increasing patient trust in medical facilities and health workers. One of the crucial aspects is accuracy in providing drug recommendations that suit the patient's needs. Drug recommendations are influenced by various criteria, including effectiveness, safety, price, availability, and potential side effects. However, in practice, there is often a gap between the patient's expectations and the reality of the treatment received. This can affect patient satisfaction and perception of health services. To overcome these challenges, a Decision Support (SPK) is needed that is able to provide drug recommendations in a more objective, measurable, and structured manner. This study uses the Simple Additive Weighting (SAW) method because of its advantages in processing various complex and diverse criteria. SAW works by giving weight to each attribute, normalizing the data, and then calculating the preference value to determine the best alternative from several available drug options. The results of the study show that the SAW method is able to produce more structured and consistent recommendations than manual determination. In this study, the drug with the highest preference value, which is 92.00, was recommended as the top choice. These findings confirm that SPK and SAW-based approaches can be an effective solution in supporting medical personnel, especially in the selection of external drugs. In addition to improving decision accuracy, this SPK also has the potential to be further developed, for example by integrating into an electronic medical record (EMR) or based on a mobile application, so that its use becomes more practical and accessible. Thus, the implementation of the SAW method in SPK not only provides benefits on the technical aspect, but also contributes to improving the quality of health services as a whole.

Some schools currently still use manual methods for assessment in determining the best teachers.  Giving grades to teachers is sometimes still subjective, so the risk of conflict is high due to inaccurate and non-transparent assessments, making it a problem for teachers in teaching. For this reason, an information system is needed to get accurate calculation results to get the best teacher ranking. In answering the problems found, the author developed a decision support system using the Simple Additive Weighting method to obtain accurate ranking results so that it can provide maximum decision results through faster, more accurate and precise classification and evaluation. And this research uses a prototype method as an addition to make system development easier. The results of calculations using the SAW method can determine the ranking for the best teachers. Based on a comparison between the pretest and posttest results, it was found that the conformity level was 60% for appropriate data from the 10 data used and 40% for inappropriate data.

This study analyzes e-commerce platform preferences for digital marketing strategies among Generation Z students at the Institut Teknologi dan Bisnis Semarang using the Simple Additive Weighting (SAW) method. By evaluating four platforms (Tokopedia, Lazada, Shopee, TikTok) based on ease of use (25%), user experience (25%), promotions (15%), transaction security (15%), and product completeness (15%), the results show that Shopee leads (0.9333) with the best interface and features. TikTok (0.9080) excels in promotions but lacks security, Tokopedia (0.8820) remains consistent, while Lazada (0.8084) needs UX improvements. The implications suggest that platforms should optimize mobile interfaces, collaborate with influencers, and enhance visual search features to meet Gen Z’s demand for interactive experiences and economic value..

In order for students to actively develop their potential for religious spiritual strength, self-control, personality, intelligence, morality, life sciences, general knowledge, and the skills they need for society based on the law, education is a planned basic effort to create a learning atmosphere and learning process. Invite. Although it can also be autodidactic, education frequently takes place with the assistance of other people as well as biological parents. Preschool, elementary school, middle school, high school, and finally college, university, or apprenticeship are the typical phases of education. Another important factor in a region's development is education. Therefore, a decision support system that can make suggestions for choosing state institutions and study programs is required for West Sumba Regency SMA/Vocational Schools. The Analytical Hierarchy Process (AHP) approach is used to weight the value of each criterion, and the Simple Additive Weighting (SAW) method is used to calculate the weighted total or to order the alternatives from best. The weights of each alternative—a state university or study program—along with all of its features are added up to determine recommendations for selecting one. The chosen option will be indicated by a higher value. This system generates a report on the outcomes of management decisions, which includes the management's selections based on all options arranged from greatest to smallest SAW value. MySQL and Microsoft Visual Studio 2008 were used to develop the decision support system suggestions for choosing state colleges and study programs for the database.    

Village development includes village funding, and the community takes the lead in developing and initiatives that advance village welfare are developed through cooperation with the community. Village development is an important instrument that must be used because it directly improves the welfare of the village community. Village communities are the focus of development, and each village is given the authority by the government to carry out its own development according to its capacity. Thus, the government supports the improvement of village development and empowerment. Village funds are used to provide or improve village public services, reduce poverty, advance the village economy, and reduce tandem between villages. This study uses a weighted summation approach of alternative rankings on all attributes, which is often known as the Simple Additive Weighting method. To determine which residents receive social assistance, the system can calculate the value of the multi-criterion preference index, preference value, outflow, inflow, and net flow for each alternative and sub-criterion.  

The selection of campus ambassadors at Politeknik Negeri Bengkalis is one of the activities carried out annually. The selection of campus ambassadors aims to prepare the best students to become student representatives in internal and external campus activities. The campus ambassador assessment process is carried out in three stages, namely pre-quarantine, quarantine and grand final. A websitebased Decision Support System for campus ambassador finalist candidates is needed to help the committee and judges in the finalist selection process to be faster and more accurate. This system uses the Simple Additive Weighting (SAW) method which has weights on each criterion. The result of applying the SAW method to the system is to display rankings that can help in determining the campus ambassador finalist champion. From 31 field data, the application of the SAW method on this system has an accuracy of 96,6%. The software development method used is the Rational Unified Process (RUP).

The Bengkalis Regency Education Office (Disdik) provides Local Children's Scholarships to students in an effort to help students to alleviate the dependents of the Single Tuition Fee (UKT) in pursuing education. In determining the recipient of the Tempatan Children's Scholarship, the Education Office government carries out several stages manually such as collecting all the files of students who register, after which the Education Office checks the completeness of the student files one by one, gives a value for each predetermined criterion and manually calculates the value of the criteria. A decision support system for recipients of web-based Local Children's Scholarships is needed to help determine recipients of Local Children's Scholarships to be faster and more accurate. This system is made using the Simple Additive Weighting (SAW) method and Multi Attributive Border Approximation Area Comparison (MABAC) to facilitate the calculation and comparison of the value of each alternative in the system, by determining the ranking based on the largest value as the best alternative. The result of the application of the SAW and MABAC methods in the system is that the system displays alternative data sequentially based on rankings that can help in determining the recipient of the Local Children Scholarship. From 60 field data, the application of SAW and MABAC methods on this system has an accuracy of 83.3%. The development method used is the Extreme Programming method.

This study aims to find the highest value of criteria, sub-criteria and alternatives in prioritizing K3 strategies at PLN NP UP Muara Tawar to ensure and protect the workforce. Using the 5M approach (Money, Man, Machine, Methods and Milieu), 21 sub-criteria and 5 alternatives in order to prevent, overcome and minimize the occurrence of work accidents and their impacts by identifying, analyzing and controlling appropriately to improve K3 in the workplace. The Simple Additive Weighting (SAW) mixed method is used to calculate criteria and sub-criteria and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) calculates alternatives. The results of the analysis show that the highest criterion is man (M) with a score of 0.2113 and the highest sub-criteria are K3 Infrastructure Investment (MO1) and Fire Protection System Infrastructure Investment (MO2) with a score of 0.29577. The highest alternative is with a score of 0.7900 on maintenance of equipment and facilities (A2).    

This study develops a Decision Support System (DSS) for selecting outstanding students at SDN Kedunglumbu using the Simple Additive Weighting (SAW) method. The main goal of this DSS is to help the school determine outstanding students more objectively and efficiently. The SAW method was chosen for its ability to provide weighted sums of relevant criteria, ensuring accurate and fair decisions. The system development follows a waterfall approach, with structured stages from planning to implementation. The evaluation criteria include PPKN, Indonesian Language, Science, Social Studies, and Mathematics, with seven students as the evaluated alternatives. The implementation of the DSS successfully displays information about outstanding students clearly, with Natasha Cahya Putri Ayu selected as the outstanding student with the highest preference score of 0.786. System testing using the blackbox testing method confirms that the system operates as expected, and calculations using the SAW method are consistent with manual calculations. Overall, the developed DSS successfully facilitates the selection process of outstanding students efficiently and objectively, while the SAW method proves effective in providing reliable results and supporting better decision-making in the educational environment.      

This article discusses the development of a decision support system (DSS) for selecting the best tourist attractions in Surakarta City using the Simple Additive Weighting (SAW) method. The background of the research is the importance of choosing the right tourist attractions to enhance visitor satisfaction and support regional development. The SAW method was chosen for its ability to provide structured assessments based on multiple criteria. This study uses an Agile approach in system development, involving planning, analysis, design, implementation, and testing stages. The results show that the developed decision support system can effectively manage the criteria and alternatives for tourist attractions. The calculations using the SAW method indicate that Sheikh Zayed Mosque has the highest preference value, making it the best tourist attraction according to this system. Testing shows that the system functions as expected, with consistent calculation results between manual and automated methods.