Simple Additive Weighting Research Articles

Determining Prospective Recipients of The Indonesia Smart Scholarship Program Using The Support Vector Machine Algorithm and Simple Additive Weighting

Between the period from 2018 to the first semester of 2020, a total of 2.4 million students who owned the Kartu Indonesia Pintar (Indonesia Smart Card) were at risk of not being able to access the Program Indonesia Pintar due to delays in entering recipient data, misdirected targeting, and fund disbursement obstacles. During its implementation, there were issues with inaccurate data of Kartu Indonesia Pintar recipients, resulting in the beneficiaries not being entirely targeted correctly. According to Article 12 of Minister of Education and Culture Regulation No. 10 of 2020, schools, as educational units, are assigned the responsibility of managing the Smart Indonesia Program at the school level. This includes tasks such as proposing eligible student candidates for the Program based on criteria, monitoring and assisting the smooth process of receiving the benefits, and accommodating students who hold the Kartu Indonesia Pintar (KIP). However, schools faced difficulties in obtaining the eligibility data of potential Indonesia Pintar Program recipients through the school proposal format. The objective of this research is to determine the eligibility of potential Indonesia Pintar Program recipients using a combination of Support Vector Machine (SVM) and Simple Additive Weighting (SAW) techniques. The SVM model was trained using kernel tricks and parameter selection (C and gamma) based on data sourced from the DAPODIK application of students in SMK Negeri 1 Kota Bekasi for the academic years 2020/2021 to 2022/2023, with a dataset containing 2499 rows . This dataset was used to determine the eligibility of potential Indonesia Pintar Program recipients. The SAW method was then employed to calculate scores based on the weighting of attributes possessed by the students, which were subsequently ranked from the highest score. The Linear Kernel with parameter values C=0.1 and gamma=0.1 achieved an accuracy of 88.8% during the classification of test data, using 10% of the total dataset, which amounted to 250 rows of data. The combination of SVM and SAW methods resulted in the classification of eligibility for potential Indonesia Pintar Program recipients, ranked based on their scores using the weighted assessment with the SAW method.

Sistem Pendukung Keputusan Pemilihan Rumah Kost menggunakan Metode Simple Additive Weighting (SAW)

Housing development is increasing, one of which is boarding houses, due to the many workers or immigrants wanting to work. However, many workers or local immigrants have difficulty in choosing a boarding house due to the many considerations regarding the aspects of cost, facilities, and location, followed by a large number of boarding houses offering different prices, facilities, and locations, which will make workers or immigrants confused in deciding which place to go. they will stay. Decision Support Systems (DSS) are a type with the capability to solve a problem in semi-systematic and unsystematic terms. This decision support system will later be created using the Simple Additive Weighting (SAW) method to solve problems experienced by workers or immigrants. The author's research technique is determining criteria and alternatives, collecting data, carrying out calculations, and ranking alternatives from the calculation results. The research sample was a boarding house in the Kalibata area, Pancoran, South Jakarta. The results of this research are aimed at making it easier for students or migrant workers who need housing according to their criteria.

ANALISIS KEPUTUSAN MENGGUNAKAN METODE CUT OFF POINT DAN FUZZY SIMPLE ADDITIVE WEIGHTING DALAM MENENTUKAN JENIS LAPTOPTERBAIK PADA MAHASISWA MATEMATIKA FMIPA UNIVERSITAS NEGERI PADANG

The emergence of various types and brands in the laptop industry poses problems for consumers in determining the best type of laptop. To assist consumers in determining the best type of laptop, a Decision Support System is needed. This research is an applied research. The data used is primary data obtained from the distribution of questionnaires through Google Form to students of the Department of Mathematics UNP batch of 2020, 2021, 2022. The variables used are Brand, Operating System, Processor, Solid State Drive, Random Access Memory, Battery, Screen Size, Laptop Weight, Color, Price. The methods used in this study are the Cut Off Point Method and the Simple Additive Weighting method. Based on the results of the problem analysis in determining the best laptop type using the Cut Off Point and Fuzzy Simple Additive Weighting methods, it shows that the Asus zenBook Pro laptop type is recommended as the best type of laptop with a preference value of 0.87

A NEW METHODOLOGY FOR TREATING PROBLEMS IN THE FIELD OF TRAFFIC SAFETY: CASE STUDY OF LIBYAN CITIES

Traffic safety is an area of great importance, since there are many traffic accidents every day in which a significant number of people are killed. Defining certain strategies and identifying potentially the most dangerous towns and cities regarding this area are, on the one hand, a necessity, and, on the other hand, a challenge. In this paper, integrated Multi-Criteria Decision-Making (MCDM) model for ranking cities in Libya from the aspect of traffic safety has been proposed. The model implies a set of 8 criteria on the basis of which 5 decision-makers rated the 10 most deprived cities in Libya. The Full Consistency Model (FUCOM) in combination with the rough Dombi aggregator is used to determine the significance of the criteria. The Rough Simple Additive Weighting (R-SAW) method is used to rank the alternatives. The rough Dombi aggregator is also used for averaging in group decision-making while evaluating the alternatives. The stability of the model and the obtained results has been verified by the sensitivity analysis, which implies a 2-phase procedure. In the 1st phase, rough Additive Ratio Assessment (R-ARAS), Rough Weighted Aggregated Sum Product Assessment (R-WASPAS), Rough Complex Proportional Assessment (R-COPRAS) and Rough Multi-Attributive Border Approximation-area Comparison (R-MABAC) methods are applied. The 2nd phase implies changing the parameter ρ in the procedure of rough Dombi aggregator, while the 3rd phase includes the calculation of Spearman’s Correlation Coefficient (SCC) that shows a high correlation of ranks.

Implementation of Maqashid Shariah Principles in the Beauty Salon Business

The beauty industry has become an important part of the modern lifestyle. However, beauty salons often face challenges in aligning their practices with sharia principles. This research discusses the salon concept based on sharia provisions, exploring the implementation of Islamic principles in beauty services. The provisions that beauty salons must have are the use of products that are halal certified. The aim of this research is to explain the level of implementation of maqashid sharia in salons. To find out how far salons consider sharia aspects in their business, this research uses a literature review and the Simple Additive Weighting (SAW) method as research methodology. The research results show that there are still many sharia-based salons but do not meet the maqashid sharia criteria.

Maqashid Sharia-Based Pesantren Development Index

This paper discusses the concept of Pondok Pesantren in terms of its etymology and history, describes its role in Islamic education, and explores the concept of Maqashid al-Syariah as the main objective of sharia law. This concept is applied in the context of Islamic boarding schools with a focus on environmental protection as the main variable. This study uses Simple Additive Weighting (SAW) method to assess the achievement of Maqashid al-Syariah in two Islamic boarding schools, namely Pesantren Miftahul Huda Bogor and Pesantren Hidayatullah Balikpapan. The results of the analysis show that both pesantren have good achievements in protecting religion, soul, mind, offspring, and property, but there are differences in environmental indicators. Pesantren Hidayatullah Balikpapan shows better performance in the environmental aspect, making it close to the full achievement of Maqashid Syariah, while Pesantren Miftahul Huda Bogor has some shortcomings in the health and environmental aspects. This study provides a comprehensive picture of the implementation of Maqashid Syariah in pesantren and provides insights into the role of pesantren in Islamic education and the environment.

Frozen Base Gateway Discovery Algorithm for Mobile Ad-Hock Network with Internet Connectivity Using AODV + Routing Algorithm

A mobile ad-hoc network (MANET) is a self-organized, auto-configured network and the mobile nodes have been free to move. To enable the MANET to connect to the internet it uses an intermediate bridge called a gateway. The MANET and the internet gateway is a heterogeneous network, which needs a gateway discovery. There are three types of gateway discovery mechanisms: proactive, reactive, and hybrid gateway discovery mechanism. The main challenge in the integration of the MANET and the Internet is, that there are high link disconnection results from node mobility and limited energy. In addition link disconnection, packet drop, and end-to-end delay. This study examines the impact of node mobility and energy in the frozen path from the source node to the destination node of MANET In this study, the Ad-hoc on-demand distance vector routing (AODV) routing protocol is used and modified to examine the gateway selection for MANET and the Internet. Moreover, the AODV+ control message RREQ and RREP and the routing table are improved to store the energy factor, path queue length, and frozen factor of the path. The proposed gateway discovery algorithm is known as frozen-based gateway AODV+ (F_AODV+), The stability factors of the path from the source node to the gateway, are calculated using a simple additive weighting method of the energy factor, average path queue node, and the path with the Maximum energy factor and minimum queue length is the more Frozen to select Frozen gateway from the source node to distension node.A mobile ad-hoc network (MANET) is a self-organized, auto-configured network and the mobile nodes have been free to move. To enable the MANET to connect to the internet it uses an intermediate bridge called a gateway. The MANET and the internet gateway is a heterogeneous network, which needs a gateway discovery. There are three types of gateway discovery mechanisms: proactive, reactive, and hybrid gateway discovery mechanism. The main challenge in the integration of the MANET and the Internet is, that there are high link disconnection results from node mobility and limited energy. In addition link disconnection, packet drop, and end-to-end delay. This study examines the impact of node mobility and energy in the frozen path from the source node to the destination node of MANET In this study, the Ad-hoc on-demand distance vector routing (AODV) routing protocol is used and modified to examine the gateway selection for MANET and the Internet. Moreover, the AODV+ control message RREQ and RREP and the routing table are improved to store the energy factor, path queue length, and frozen factor of the path. The proposed gateway discovery algorithm is known as frozen-based gateway AODV+ (F_AODV+), The stability factors of the path from the source node to the gateway, are calculated using a simple additive weighting method of the energy factor, average path queue node, and the path with the Maximum energy factor and minimum queue length is the more Frozen to select Frozen gateway from the source node to distension node.

Penentuan Nilai Saham Terbaik Dalam Sistem Pendukung Keputusan Dengan Menggunakan Metode Simple Additive Weighting (SAW)

In the current era of information technology, aspects of life have become dependent on the era of globalization, especially for business people. To support the economy, investment is an important step that must be taken. Generally, basic principles are needed to decide on investment steps in the form of shares in order to obtain maximum profits. The value of investing in the capital market requires sufficient information, experience, and business sense to analyze which investments to buy, which to sell, and which to keep. The value of shares is difficult for investors to predict with potential shares, so investors need to carry out investment trend analysis and for companies to first determine their investment policy model so that they make investment decisions in accordance with what is most expected with the level of risk tolerance limits. Analysis of investment information is useful for determining the value of the shares to be selected and to find out the expected rate of return to determine the investment strategy that will be carried out.
 Making decision support using several criteria that will be part of the strategy in determining potential shares. A decision support system is a decision that can help, speed up and simplify the decision making process.
 Fuzzy Multi-Attribute Decision Making (FMADM) with the Simple Additive Weighting (SAW) method is a method that can assist in making decisions regarding several alternative decisions that must be taken with several criteria that will be taken into consideration.

MANAGING THE PRODUCTION PROCESSES - OPTIMIZATION OF THE TECHNOLOGICAL PROCESS OF BANANA RIPENING BY APPLYING THE SIMPLE ADDITIVE WEIGHTING METHOD

The realization of company goals is greatly influenced by the manager’s decisions in the activities of managing production processes. To make decisions, managers use different decision-making methods, taking into account different criteria on the basis of which they choose the best alternative. The paper presents the optimization of the technological process of banana ripening using the simple additive weighting (SAW) method. The research monitored temperature correction, ripening gas dosage concentration, duration of treatment, commodity loss, including correction of accompanying factors of green banana fruit ripening. By applying the SAW method on 400 performed ripenings in the period from 2017 to 2020, the best results were achieved at a temperature of 18.5 °C, with an ethylene concentration of 840 ppm, process time of 112 h and achieved kalo of 233 kg. The total cost of ripening based on the examined parameters is 250.12 € which can save 81.42 € and meet the finishing standards.

Penggunaan Metode Saw Dalam Mendukung Pengambilan Keputusan Penentuan Pemberian Pinjaman (Studi Kasus : Koperasi Hening Rahayu)

This research aims to implement the SAW (Simple Additive Weighting) method in supporting decision making for granting money loans to Savings and Loans Cooperatives. Hening Rahayu Savings and Loans Cooperative in Tabanan, Bali is the subject of this research. In this context, cooperatives face challenges in selecting customers who are worthy of loan services. The SAW method was chosen because of its ease of implementation and its ability to consider various relevant criteria. This method has advantages in terms of usability, error, interpretability, and computational efficiency. This research will involve collecting data on the profile of potential borrowers, loan eligibility, credit risk, and repayment capacity. This data will be analyzed using the SAW method to produce a final score for each prospective borrower. This score will be used as a basis for making decisions about granting loans. By using the SAW method, it is hoped that the Hening Rahayu Cooperative can speed up and simplify the decision-making process regarding granting loans. It is hoped that the results of this research can contribute to the development of technology in the savings and loan cooperative sector. Further research could involve developing other methods to support decision making or making the SAW method a system that can support decision making in different savings and loan cooperative contexts.

Modified Analytic Hierarchy Process in Formulating Health Index Model for Substation Equipment

The level of electricity consumption per capita in Indonesia has increased by 6.6% per year on average within 2009 to 2019 and is predicted to grow until 2060. Therefore, the importance of transmission system reliability has been escalated to secure the fulfillment of electrical energy needs. A good maintenance strategy needs to be carried out in order to ensure the reliability of transmission system, one of which is through implementation of asset health index. This research aims to propose a framework that combines the Failure Mode Effect Analysis (FMEA), Analytic Hierarchy Process (AHP), and Simple Additive Weighting (SAW) methods to obtain a mathematical model of asset health index. Case study was conducted at PLN UIP3B Sulawesi in order to formulate health index model for medium voltage cubicle through quantifying the opinions of experts and practitioners in the field of 20 kV cubicle maintenance. The conclusions obtained are: 1) the use of framework based on FMEA, AHP, and SAW is able to produce multicriteria decision making model through objective quantitative approach; 2) the framework can be used as a tool to convert qualitative opinions into a series of quantitative weighting factors; 3) the framework was successfully applied to the case study of formulating cubicle health index model in UIP3B Sulawesi; 4) the framework has a good level of scalability so that in can accommodate further addition of other expert opinion in the future.

A Comparison of Product Weight Method and Simple Addition Weight Method in Employee Selection System

Tegar Mandiri Steam Ironing Service is a business operating in the steam ironing service industry, located in the Boyolali area, specifically in Dlingo Village, Mojosongo Subdistrict, Boyolali Regency, Central Java. "Tegar Mandiri" still employs conventional methods in the selection and recruitment of employees without leveraging technology. Although the implementation of conventional employee recruitment has been smooth, several issues have arisen. For instance, prospective applicants must visit in person to find out about job vacancies. Furthermore, the registration process for potential employees is still manually executed, requiring individuals to physically visit the site. Consequently, the administrative staff must record each applicant's details individually, leading to an ineffective data collection process and vulnerability to data loss or damage in physical records. The implementation phase was conducted through coding in PHP, adopting the Simple Additive Weighting (SAW) and Weight Product (WP) methods. Although both methods exhibit minor differences in their comparison, the results tend to favor the SAW method. The accuracy level of the SAW method reaches 96% as it has advantages over the WP method in terms of data normalization. The SAW method can address issues related to scale and unit differences among various criteria. Therefore, the SAW method is more accurate and dominant in determining the priority of employee recruitment

Decision Support System for Determining Character Education Values

The 2013 curriculum is an effort made by the government in improving the curriculum according to the needs of the current generation. This 2013 curriculum is a curriculum that does not only focus on academic competence, but also includes aspects of student character and skills. However, in its implementation, the 2013 curriculum makes teachers feel confused, especially in the assessment of attitudes and character. The assessment carried out with Rubik and observation sheets has indicators that are not appropriate so that character assessment becomes inappropriate. This research will design a system to conduct student character assessment at SDN Butuh 1 Magelang. In this research, a system will be designed to help teachers conduct student character assessment with SPK character assessment in Indonesia. The method applied in this research is the Simple Additive Weighting (SAW) method. The result of this research is a system to support the decision of students' character education value.

SISTEM IDENTIFIKASI SAMPAH ANORGANIK BERBASIS IOT (Internet of Things) MENGGUNAKAN METODE SAW (Simple Additive Weighting)

Inorganic waste is one of the environmental issues that needs to be effectively managed. An Internet of Things (IoT)-based system using the Simple Additive Weighting (SAW) method is implemented to provide a solution for the more efficient management of inorganic waste. This system utilizes sensors connected to the IoT network to detect and identify the types of inorganic waste entering a specific area. The SAW method is employed to assign weights to each criterion applied in the identification process of inorganic waste, such as type, weight, and physical condition. The system assesses based on the predefined criteria weights, enabling high-accuracy categorization of inorganic waste. Identification results can be accessed in real-time through the IoT platform Thingspeak, allowing for quick monitoring and analysis. Implementing this system is expected to positively contribute to the management of inorganic waste, facilitating more efficient collection, categorization, and overall waste handling. Moreover, adopting IoT technology and the SAW method in this system is envisioned to provide sustainable solutions in waste management efforts to support environmental sustainability.

Implementation of Simple Additive Weighting to Decide a Fund Proposal

One of Indonesian micro financial services is Baitul Maal Wat Tamwil (BMT) provides services such as savings, financing and zakat activities. Financing service determine qualifying status based on consideration of customer files before carried out in company discussions. This decision support system aims to provide officers to decide whether or not to admit funding. The research used Simple Additive Weighting (SAW) by finding the prejudiced sum of the performance ratings for each alternative from all criteria. The method used 7 criteria including income, outstanding loans, amount of financing, collateral, nature/environment, track record of financing and monthly expenses. Customers were declared acceptable if they had a preference value above the minimum limit of 16.1. The BMT officer can adjust the minimum limit value according to customer performance. To develop the system used waterfall method and to verify system performance used a black box test which shows the results that the system works according to its function and the validity test results obtained 100% accurate. It means the system is ready and suitable for use. The existence of this decision support system is able to assist officers in making decisions to qualify for financing objectively.

Application of The Simple Additive Weighting Method in Developing Employee Assessment Decision Support System in Marketplace Company Bukalapak

The purpose of this study is to investigate how managers, team leaders, and supervisors can evaluate top performers with the aid of simple additive weighting in decision support systems. In this study, interviews, observation, and related literature reviews were employed as data collection techniques. This system employs fuzzy simple additive weighted (FSAW) as its approach. Two techniques, AHP and WP, were used to develop the system. Rapid Application Development, or RAD, is the system development methodology employed in this study. The findings of the study led to the following deductions: The results of this application calculation do not directly determine when assessing the best employee; you must wait for a decision from the team leader, supervisor, manager or meeting. The results provided by the best employee assessment decision support system method can be implemented using dynamic or changeable criteria to determine the best alternative. There are seven criteria used for research on evaluating the best employees in this application, namely: average process. Processes include: quantity; quality; on time; and teamwork. Productivity, which includes days in and days out/holidays. These criteria are only a basis for research in writing about the best employees, but to add or subtract criteria, you can add or subtract them in the best employee assessment application system using SAW.

IMPLEMENTASI METODE SAW (SIMPLE ADDITIVE WEIGHTING) untuk MENENTUKAN PRIORITAS KEBERSIHAN TOILET SEKOLAH BERBASIS Internet of Things

This research proposes the implementation of the Simple Additive Weighting (SAW) method as an approach to determine priorities for school toilet cleanliness based on IoT. The system integrates temperature, humidity, and ammonia gas sensors as key indicators to measure the cleanliness condition of toilets. The SAW method is employed to calculate the relative weight of each parameter, which is then used to assign priority scores. The system operates by utilizing temperature sensors to identify the toilet's environmental temperature, humidity sensors to measure humidity levels, and ammonia gas sensors to detect ammonia concentration, a crucial indicator of toilet cleanliness. Data from these sensors are collected and processed using the SAW method, enabling the automatic determination of toilet cleanliness priorities. The success of this implementation is tested through simulations and field testing. Experimental results demonstrate that the system is capable of providing priority scores with high accuracy, allowing for more efficient management of toilet cleanliness. Other advantages include the system's ability to provide real-time notifications to relevant parties through the IoT platform, facilitating prompt corrective actions. This research contributes to the development of intelligent solutions for school toilet cleanliness management, integrating IoT technology and the SAW method to provide a measurable and effective approach. With the adoption of this system, it is expected to enhance the quality of school toilet sanitation, support student health, and optimize school facility management.

Renewable Energy Transition Task Solution for the Oil Countries Using Scenario-Driven Fuzzy Multiple-Criteria Decision-Making Models: The Case of Azerbaijan

The renewable energy transition of oil- and gas-producing countries has specific peculiarities due to the ambivalent position of these countries in the global energy market, both as producers and consumers of energy resources. This task becomes even more challenging when the share of oil and gas in the country’s GDP is very high. These circumstances pose serious challenges for long-term energy policy development and require compromising decisions to better align the existing and newly created energy policies of the country. The scale, scope, and pace of changes in the transition process must be well balanced, considering the increasing pressure of economic and environmental factors. The objective of this paper is to develop models that allow the selection of the most appropriate scenario for renewable energy transition in an oil- and gas-producing country. The distinguishing feature of the proposed model is that alternatives in the decision matrix are presented as scenarios, composed of a set of energy resources and the level of their use. Linguistic descriptions of the alternative scenarios are formalized in the form of fuzzy statements. For the problem solution, four different Multiple-Criteria Decision-Making (MCDM) methods were used: the fuzzy simple additive weighting (F-SAW) method, the distance-based fuzzy TOPSIS method (Technique of Order Preference Similarity to the Ideal Solution), the ratio-analysis-based fuzzy MOORA method (Multi-Objective Optimization Model Based on the Ratio Analysis), and the fuzzy multi-criteria optimization and compromise solution method VIKOR (Serbian: VIekriterijumsko Kompromisno Rangiranje). This approach is illustrated using the example of the energy sector of Azerbaijan. The recommended solution for the country involves increasing natural gas (NG) moderately, maintaining hydro, and increasing solar notably and wind moderately.

Application of SAW method for finding best input factors for CBN grinding Al6106 T6

The outcomes of a multi-criteria decision-making (MCDM) study in CBN grinding Al6061 T6 to determine the optimal input process parameters to achieve both low surface roughness (Ra) and maximum material removal speed (MRS) are described in this study. The MCDM problem was addressed using the simple additive weighting (SAW) method, and the weights of the criterion were computed using the MEREC (Method based on the Removal Effects of criterion) technique. In addition, four process input factors were investigated: wheel speed (WS), feed rate (Fe), depth of cut (aed), and down feed (Df). The experiment was designed with the 2-level 1/2 fraction type in mind. The experimental output outcomes, including the SR and MRS, were measured and entered into the MCDM issue. Based on the study's findings, the ideal input parameters for CBN grinding Al6061 T6 were identified.

IMPLEMENTASI METODE SIMPLE ADDITIVE WEIGHTING (SAW) UNTUK SISTEM REKOMENDASI SELEKSI PESERTA PELATIHAN CEMPOR DISPORA KOTA BANDUNG

The utilization of information technology has become a positive trend. Its usefulness is not only as a medium of information or concerning business, but information technology has also been used by agencies or organizations. An agency or organization has begun to use technology as a tool that can help management in making a decision where the decision is very important to do. The CEMPOR Dispora Bandung City organization when selecting trainees still uses a manual method by filling in the criteria filled in by the committee. This method only relies on assessments made in the field. A recommendation system must be created to assist the Cempor Dispora committee in determining the selected trainees for the next training session in a more systematic and structured manner. This will help the company make decisions. This research recommendation system selects trainees using the Simple Additive Weighting (SAW) method to evaluate the accuracy of the method. Calculating the number of participants' average scores for this training activity and speeding up the participant selection process are the capabilities of this web-based trainee selection recommendation system. As a result of Confusion Matrix Testing, the system has an accuracy of 95.00%.