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Teacher performance evaluation is a crucial factor in improving educational quality, but many schools still conduct it manually and subjectively, resulting in less transparent, time‑consuming, and error‑prone outcomes. This study aims to design and develop a web‑based decision support system using the Simple Additive Weighting (SAW) method for selecting the best teacher at MTs Mambaul Ulum. The system was developed using the Waterfall model with the Laravel 12 framework and MySQL database, incorporating two evaluator roles: the principal (assessing 5 criteria: teaching hours, responsibility, mastery of material, personality, and attendance) and the vice principal (assessing 4 criteria excluding personality). Data were collected through observation, interviews, and document review. System testing employed Black Box Testing and accuracy validation by comparing system outputs with manual Excel calculations. The results show that the SAW method effectively ranks teachers objectively, with Kusyanti achieving the highest score of 0.9450. The system attained 100% accuracy, as no difference was found between manual and system calculations. Moreover, the system reduced evaluation time from days to seconds and provides well‑documented results, thus supporting more transparent and accountable decision‑making. Therefore, this system proves to be reliable, objective, and efficient in assisting school administrators in evaluating teacher performance in a structured and fair manner.

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.

Pemilihan siswa berprestasi di sekolah seringkali dilakukan secara manual dan berpotensi menimbulkan subjektivitas dalam pengambilan keputusan. Penelitian ini bertujuan untuk menerapkan Sistem Pendukung Keputusan (SPK) menggunakan metode Simple Additive Weighting (SAW) guna meningkatkan objektivitas, transparansi, dan efisiensi dalam proses seleksi siswa berprestasi. Penelitian dilakukan pada satu sekolah dengan melibatkan 20 alternatif siswa dan empat kriteria penilaian yang telah ditentukan bobotnya, yaitu C1 (0,4), C2 (0,2), C3 (0,3), dan C4 (0,1). Tahapan penelitian meliputi normalisasi nilai, pembobotan, serta perhitungan nilai preferensi untuk menentukan peringkat akhir. Hasil penelitian menunjukkan bahwa metode SAW mampu menghasilkan pemeringkatan siswa secara sistematis dan terukur, dengan alternatif terbaik memperoleh nilai preferensi tertinggi sebesar 0,99. Proses perhitungan berbasis pembobotan memberikan kontribusi signifikan terhadap peningkatan objektivitas dibandingkan metode manual yang hanya menggunakan rata-rata nilai tanpa mempertimbangkan tingkat kepentingan kriteria. Selain itu, evaluasi pengguna menunjukkan bahwa sistem dinilai mudah digunakan, transparan, dan membantu dalam pengambilan keputusan yang lebih rasional. Dengan demikian, penerapan SPK berbasis metode SAW terbukti efektif dalam mendukung proses seleksi siswa berprestasi secara lebih adil dan akuntabel. Penelitian ini merekomendasikan pengembangan lebih lanjut melalui integrasi dengan sistem informasi akademik serta eksplorasi metode pengambilan keputusan multikriteria lainnya untuk meningkatkan akurasi dan fleksibilitas sistem.

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

Penelitian ini bertujuan untuk mengembangkan sebuah Sistem Pendukung Keputusan (SPK) yang digunakan dalam menentukan Sekolah Menengah Pertama berprestasi di wilayah Kabupaten Serang, Provinsi Banten. Pengembangan SPK ini diharapkan mampu membantu pihak terkait, seperti dinas pendidikan atau pengawas sekolah, dalam melakukan proses penilaian sekolah secara lebih sistematis, objektif, dan terstruktur. Dengan adanya sistem ini, proses evaluasi sekolah dapat dilakukan dengan lebih mudah dan cepat tanpa harus melakukan kunjungan langsung ke setiap sekolah, sehingga lebih efisien dari segi waktu dan biaya. Metode yang diterapkan dalam penelitian ini adalah Simple Additive Weighting (SAW), yang dipilih karena mampu memberikan perhitungan berdasarkan pembobotan kriteria secara jelas dan terukur. Pengumpulan data dilakukan melalui wawancara dengan pengawas sekolah sebagai sumber data primer, serta observasi data sekolah yang diperoleh dari Dapodik dan dokumentasi sebagai data sekunder. Hasil penelitian menunjukkan bahwa metode SAW mampu menghasilkan penilaian yang akurat dan efisien, di mana Sekolah Menengah Pertama Terpadu Bismilah menempati peringkat tertinggi sebagai sekolah berprestasi. Kesimpulannya, penerapan SPK ini dapat meningkatkan kualitas pengambilan keputusan dalam penilaian sekolah berprestasi di Kabupaten Serang.

Penelitian ini bertujuan untuk membangun sebuah sistem pendukung keputusan berbasis website guna membantu proses seleksi beasiswa berprestasi di SMAN 17 Bungo secara lebih objektif, efisien, dan transparan. Metode yang digunakan dalam sistem ini adalah Simple Additive Weighting (SAW), yang berfungsi untuk melakukan perhitungan dan pemeringkatan calon penerima beasiswa berdasarkan beberapa kriteria yang telah ditentukan, seperti nilai rapor, kehadiran, penghasilan orang tua, dan prestasi siswa. Pengujian sistem dilakukan menggunakan metode Black Box Testing untuk memastikan bahwa setiap fitur berfungsi sesuai dengan yang diharapkan, seperti login admin, pengelolaan data siswa dan kriteria, input penilaian, serta hasil keputusan akhir. Hasil pengujian menunjukkan bahwa seluruh fungsi sistem berjalan dengan baik. Sistem ini telah diimplementasikan dengan dukungan perangkat keras (hardware), perangkat lunak (software), dan sumber daya manusia (brainware) yang sesuai, serta diuji dalam lingkungan lokal menggunakan XAMPP. Dengan adanya sistem ini, proses seleksi beasiswa di SMAN 17 Bungo menjadi lebih cepat, akurat, dan mendukung digitalisasi administrasi sekolah.

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.

Pemilihan jurusan di Sekolah Menengah Kejuruan (SMK) merupakan tahap penting yang mempengaruhi arah pendidikan dan karier siswa di masa depan. Di SMK XYZ Kabupaten Tegal, pemilihan jurusan masih dilakukan secara konvensional dengan mempertimbangkan nilai rapor dan saran dari guru atau orang tua, yang cenderung bersifat subjektif dan tidak sepenuhnya memperhatikan potensi serta minat individual siswa. Untuk itu, penelitian ini bertujuan mengembangkan sistem pendukung keputusan (SPK) yang dapat memberikan rekomendasi jurusan secara objektif dan sistematis menggunakan dua metode, yaitu Naive Bayes dan Simple Additive Weighting (SAW). Naive Bayes, yang berbasis pada algoritma probabilistik, telah terbukti efektif dalam memprediksi ketuntasan belajar siswa, sementara SAW banyak digunakan dalam pengambilan keputusan multikriteria dengan memperhitungkan beberapa aspek kriteria seperti nilai rapor, hasil psikotes, dan minat siswa. Penelitian ini mengkomparasi kedua metode tersebut untuk menentukan mana yang lebih optimal dalam memberikan rekomendasi jurusan yang akurat dan sesuai dengan karakteristik siswa di SMK XYZ. Hasil penelitian diharapkan dapat memberikan solusi alternatif bagi sekolah dalam proses pemilihan jurusan yang lebih objektif, efisien, dan minim subjektivitas, serta dapat diterapkan pada proses pendidikan di SMK lainnya.

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.

CINDI INDRIANI (2102021004) PERANCANGAN SISTEM INFORMASI PENILAIAN KINERJA KARYAWAN MENGGUNAKAN METODE  SIMPLE ADDITIVE WEIGHTING (SAW)  PADA PT DJAMBI WARAS JUJUHAN. Dengan bahasa pemograman  PHP  dan database  MySQL. Skripsi :  Program Studi S1 Sistem Informasi, Fakultas Ilmu Komputer, Universitas Dharmas Indonesia. Tahun 2025. Sistem informasi penilaian kinerja karyawan menggunakan metode  Simple Additive Weighting (SAW)  dirancang untuk membantu PT Djambi Waras Jujuhan dalam menentukan penilaian kinerja karyawan berdasarkan kriteria yang telah ditentukan. Sistem ini menggunakan bahasa pemograman  PHP dan MySQL sebagai basis data. Penelitian ini difokuskan pada karyawan bagian produksi dan non-staf, dan sistem ini dapat diakses oleh admin dan pengguna tertentu, seperti bagian kepala kantor dan staf personalia. Sistem ini dapat membantu dalam menentukan penilaian kinerja karyawan dengan lebih akurat dan efisien. Hasil penelitian menunjukkan bahwa sistem ini dapat meningkatkan kualitas penilaian kinerja karyawan. Sistem ini dapat dikembangkan lebih lanjut untuk mencakup lebih banyak kriteria penilaian dan metode penilaian lainnya. Penelitian ini dapat menjadi contoh bagi perusahaan lain yang ingin mengembangkan sistem penilaian kinerja karyawan yang lebih efektif. Kata Kunci : Sistem Informasi Penilaian Kinerja Karyawan, Metode Simple Additive Weighting (SAW),  Penilaian Kinerja Karyawan PT Djambi Waras Jujuhan.  

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 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.

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.

One of the important factors in quality human resources in a company to be able to run the business process properly in accordance with the vision and mission that has been set by the company. CV. Lestari Indojaya is one of the companies engaged in procurement and education which was founded in 2000. In order to encourage the creation of increasing performance productivity, CV. Lestari Indojaya carries out the selection of the best employees. Decision support systems can help decision makers to get recommendations for the best employees using the SAW (Simple Additive Weighting) method. In this study, the data used came from internal data and external data. There are several criteria needed to help decision makers choose the best employees, namely discipline, quality of work, cooperation and behavior. Based on all the criteria and alternatives in this study, Darwansyah was the best employee at CV. Lestari Indojaya with a total preference value of 2.875. The SAW method is an effective and practical method in calculating the best employee recommendations at CV. Lestari Indojaya so that decision makers can consider these recommendations according to the specified priorities.

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.

For prospective students, SMK Harapan Stabat offers five main subjects with a specialization system that does not require exams. The number of students majoring in office administration has increased, and majoring procedures have shifted from conventional assessments to skills-based assessments. The current method, however, is challenging, especially for the Assistant Curriculum Director because it relies on exam results reports. To solve this problem, this research creates a web-based application that uses the simple additional reduction (SAW) method. This application is intended to help school principals determine student majors more efficiently. The implementation results show that this application was well received by the students of SMK Harapan Stabat and can help them make decisions about their major. Currently, determining majors at SMK Harapan Stabat is not ideal because prospective students tend to choose majors according to their own wishes. In addition, schools only look at test scores without considering students' interests and talents as well as other factors that influence acceptance in certain majors. Collecting data on students' aptitudes, interests, and test scores is critical to improving this process. Therefore, to carry out more accurate calculations, the Simple Additive Weighting (SAW) method is needed. Schools can use this decision support system to make better decisions about the majors their students will take. Therefore, the choice of major is expected to be more appropriate to students' abilities and interests to support their future success.