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Penerapan Kombinasi Metode SWARA dan MAUT Dalam Seleksi Penerimaan Calon Guru Wahyudi, Agung Deni; Sulistiyawati, Ari
Jurnal Media Borneo Vol. 1 No. 3 (2024): Volume 1 Number 3 April 2024
Publisher : CV. Keranjang Teknologi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/mediaborneo.v1i3.58

Abstract

The selection process for teacher candidates is a critical step in ensuring the quality of quality education for students. In addition to assessing academic qualifications such as educational background and work experience, selection should also consider aspects such as communication skills, interpersonal skills, ability to manage classes, and dedication to the education profession. The main problem in the selection of teacher candidates is the difficulty in assessing qualitative aspects such as teaching skills, interpersonal communication, and leadership. The purpose of the research on the application of the combination of SWARA and MAUT methods in the selection of teacher candidate admissions is to develop a more effective and comprehensive approach in the selection process for teacher candidate admission. By combining the SWARA and MAUT methods, this study is to improve the objectivity and accuracy of assessment of teacher candidates based on established criteria. In addition, this study is also to understand the implications of the combination of these two methods on the final decision in the selection of teacher candidates, as well as to provide a strong theoretical foundation to improve the HR selection process in the field of education. The ranking results showed that the first highest score of 0.7043 was obtained by GY candidates and was entitled to 1st place, the second highest score of 0.5804 was obtained by AJ candidates and was entitled to 2nd place, and the third highest score of 0.5365 was obtained by MS candidates and was entitled to 3rd place in the selection of teacher candidate admissions. The results of ranking using a combination of SWARA and MAUT methods are recommendations for schools in the selection of teacher candidates.
Penerapan Metode Logarithmic Percentage Change-Driven Objective Weighting dan Multi-Attribute Utility Theory dalam Penerimaan Guru Bahasa Inggris Setiawansyah, Setiawansyah; Sulistiyawati, Ari
Journal of Artificial Intelligence and Technology Information (JAITI) Vol. 2 No. 2 (2024): Volume 2 Number 2 June 2024
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jaiti.v2i2.119

Abstract

The admission of English teachers in private schools is an important process in ensuring the quality of education in the institution. This process involves several stages, from the announcement of job vacancies to the selection of candidates who match the established criteria. Problems in the recruitment of English teachers, namely a selection process that lacks transparency or inadequate evaluation tools, can also be an obstacle. Therefore, addressing the problem of English teacher recruitment requires a holistic approach that pays attention to various aspects, including the development of effective recruitment strategies, the provision of training to improve candidate qualifications, and the improvement of the overall selection process. The research objective of applying the LOPCOW (Logarithmic Percentage Change-Driven Objective) Weighting and MAUT (Multi-Attribute Utility Theory) method is to provide a comprehensive and effective framework in the selection process, where LOPCOW is used to analyze objective data related to teacher performance and qualifications, while MAUT is used to integrate the subjective preferences of stakeholders such as principals and school committees in decision making. Thus, the main objective is to optimize the admission process of English teachers by considering these two aspects holistically. The ranking results show that the final results of English teacher admissions recommend the first rank with a final score of 0.7421 obtained by HR Teacher Candidates. This result is the application of the LOPCOW and MAUT methods in the selection process for English teacher admission, and becomes a recommendation for the English teacher admission process.
Kombinasi Metode Rank Order Centroid dan Operational Competitiveness Rating Analysis Dalam Seleksi Penerimaan Staff Perpustakaan Wahyudi, Agung Deni; Sulistiyawati, Ari
Journal of Artificial Intelligence and Technology Information (JAITI) Vol. 2 No. 4 (2024): Volume 2 Number 4 December 2024
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jaiti.v2i4.136

Abstract

Library staff are personnel who work in libraries and are responsible for managing, organizing, and providing various information services to library users. This selection process usually involves several stages, ranging from meeting administrative requirements to assessing the technical and interpersonal abilities of prospective staff. Problems that occur in the selection that do not have clear assessment guidelines can lead to highly subjective assessments, where decisions are influenced more by personal opinion than objective criteria. The purpose of this study is to apply a more objective, structured, and targeted approach to the selection of library staff admissions through a combination of ROC and OCRA methods that produce a selection model that can be applied to various library institutions, as well as support the improvement of service quality and library management through the selection of qualified staff. The results of the evaluation using the OCRA method, the candidate with the highest final score was Candidate H with a score of 0.9133, which placed him in the first rank as the most suitable candidate for the position of library staff. Candidate E was ranked second with a score of 0.8339, showing almost comparable performance and also very competitive. In third place is Candidate B with a final score of 0.3578. The results of this ranking help in identifying the best candidates and show qualitative differences between each prospective staff, supporting the decision-making process in the admission of library staff.
Penerapan Metode MOORA dan LOPCOW Dalam Seleksi Penerimaan Guru Bimbel Sulistiyawati, Ari
Journal of Artificial Intelligence and Technology Information (JAITI) Vol. 2 No. 4 (2024): Volume 2 Number 4 December 2024
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jaiti.v2i4.139

Abstract

The selection of the right tutor admission is important to ensure that each teacher has strong pedagogical competence, communication skills, and material understanding, as well as the ability to manage the classroom and motivate students. However, the selection of ideal teachers based on these criteria is often a challenge due to the limitations of objective and transparent assessment methods. The combination of MOORA and LOPCOW in multi-criteria decision-making offers a robust and objective approach to ranking alternatives based on relevant criteria. The combination of these two methods is expected to be able to provide more accurate, efficient, and in accordance with the needs of tutoring institutions in recruiting qualified teachers. This research aims to provide a comprehensive solution in the selection process, but also contributes to the development of a selection method based on multi-criteria analysis in the context of education. The ranking results show an alternative ranking for tutoring teacher admissions based on the scores obtained by each prospective teacher. From these results, Yusuf Hakim is ranked first with the highest score of 0.3715, which shows that he is the strongest candidate to be accepted. The second place was occupied by Siti Zahra with a score of 0.3635, followed by Intan Permata who had a score of 0.3622 in third place. From this data, it can be concluded that Yusuf Hakim is the most recommended candidate to be accepted as a tutor, while Fajar Pratama has the lowest score in this assessment.
Sistem Pendukung Keputusan Berbasis Multi-Attributive Border Approximation Area Comparison dan Entropy Weighting untuk Pemilihan Siswa Berprestasi di Sekolah Menengah Atas Sulistiyawati, Ari
Jurnal Pendidikan dan Teknologi Indonesia Vol 4 No 10 (2024): JPTI - Oktober 2024
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.466

Abstract

Pemilihan siswa berprestasi merupakan proses seleksi untuk menentukan siswa yang memiliki pencapaian terbaik di bidang akademik maupun non-akademik. Pemilihan ini bertujuan untuk memberikan penghargaan kepada siswa yang telah menunjukkan dedikasi luar biasa, sekaligus memotivasi siswa lain untuk terus berusaha mencapai prestasi maksimal. Pemilihan siswa berprestasi sering menghadapi berbagai permasalahan yang dapat memengaruhi keadilan dan akurasi hasil seleksi. Salah satu masalah utama adalah kurangnya standar penilaian yang jelas dan terukur untuk mencakup berbagai aspek, baik akademik maupun non-akademik, sehingga menimbulkan potensi bias dalam proses penilaian. Penelitian ini bertujuan untuk menerapkan SPK dalam pemilihan siswa berprestasi dengan mengintegrasikan pendekatan MABAC dan entropy weighting. Tujuan utama dari penelitian ini adalah untuk menentukan kriteria penilaian yang relevan dan tepat dalam menilai siswa, sehingga meningkatkan objektivitas dalam pemilihan siswa berprestasi dengan meminimalkan elemen subjektivitas, sehingga menghasilkan keputusan yang adil dan transparan, serta memberikan rekomendasi untuk pengembangan lebih lanjut dari sistem ini. Hasil perankingan siswa berprestasi menggunakan metode MABAC yang dikombinasikan dengan metode entropy. Siswa dengan nilai tertinggi adalah Siswa 8 (0,5709), diikuti oleh Siswa 4 (0,5701) dan Siswa 13 (0,5638), yang mencerminkan performa mereka yang paling unggul.
Combination of Response to Criteria Weighting Method and Multi-Attribute Utility Theory in the Decision Support System for the Best Supplier Selection Ulum, Faruk; Wang, Junhai; Megawaty, Dyah Ayu; Sulistiyawati, Ari; Aryanti, Riska; Sumanto, Sumanto; Setiawansyah, Setiawansyah
J-INTECH ( Journal of Information and Technology) Vol 13 No 01 (2025): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v13i01.1810

Abstract

Choosing the right supplier is a strategic factor in supporting operational efficiency and a company's competitive advantage. This process requires a decision support system that is able to assess various alternatives objectively and in a structured manner. This study aims to develop a decision support system in the selection of the best supplier by combining the Response to Criteria Weighting (RECA) and Multi-Attribute Utility Theory (MAUT) methods. The RECA method is used to objectively determine the weight of each criterion based on the variation of data between alternatives, so as to reduce subjectivity in the weighting process. Meanwhile, the MAUT method functions to calculate the total utility value of each supplier based on the normalization value and weight that has been obtained. The results of the RECA method show the objective weight of each criterion, which is then used in the MAUT calculation process. The results of the analysis, obtained in the best supplier selection based on the total score of each candidate, it can be seen that PT Global Niaga Mandiri ranks first with the highest score of 0.6512, this shows that this company is the best choice in the supplier selection process. In second place is UD Anugrah Bersama with a score of 0.399, followed by PT Indo Logistik Prima in third place with a score of 0.3451. The combination of the RECA and MAUT methods has been proven to be able to produce accurate, rational, and accountable decisions. This system provides a measurable approach in filtering supplier alternatives efficiently and is relevant to be applied to various other multi-criteria decision-making contexts.
Hybrid Logarithmic Percentage Change-Driven Objective Weighting and Grey Relational Analysis Method in Employee Contract Renewal Setiawansyah, Setiawansyah; Rahmanto, Yuri; Aldino, Ahmad Ari; Yudhistira, Aditia; Palupiningsih, Pritasari; Sulistiyawati, Ari
TIN: Terapan Informatika Nusantara Vol 4 No 12 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v4i12.5121

Abstract

Contract employees are individuals who are hired for a specific period of time within a company or organization for a specific purpose. They usually do not have permanent employee status and are bound by work contracts that govern their tenure, salary, and other obligations. Despite not having long-term job security, contract employees often bring specialized skills or experience needed for specific projects. They are often instrumental in handling temporary projects, fulfilling temporary company needs, or filling temporary vacancies. One of the main problems in determining employee contract renewal is the lack of transparency and clear communication from the company. Employees often feel confused or uncertain about the criteria used by management in determining whether or not their contract will be renewed. Lack of clear information can cause anxiety and uncertainty among employees, and impair their performance and motivation. Hybrid Logarithmic Percentage Change-Driven Objective Weighting and Grey Relational Analysis (HLOPCOW-GRA) is an approach that combines two analysis methods, namely LOPCOW and GRA to improve accuracy and reliability in decision making. HLOPCOW-GRA provides an advantage in combining LOPCOW's advantage in handling dynamic data fluctuations with GRA's advantage in analyzing relative relationships between criteria, this approach allows decision makers to gain a deeper understanding of the factors that affect the final outcome. The results of alternative ranking showed that the first place with a GRA final value of 0.1406 was obtained by EM alternatives, second place with a GRA final value of 0.1366 was obtained by SVR alternatives, third place with a GRA final value of 0.1366 was obtained by SVR alternatives, third place with a GRA final value of 0.1406 was obtained by EM alternatives. The final GRA value of 0.1245 obtained alternative ASR.
Program Sekolah Binaan : In House Training Peningkatan Kompetensi Public Speaking Dalam Kepemimpinan Siswa Di SMAN 2 Gedong Tataan Sulistiyawati, Ari; Yulianti, Tien; Rahmanto, Yuri; Fitratullah, M.; Priandika, Adhie Thyo
Journal of Social Sciences and Technology for Community Service (JSSTCS) Vol 4, No 2 (2023): Volume 4, Nomor 2, September 2023
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jsstcs.v4i2.3199

Abstract

Kegiatan Pengabdian kepada Masyarakat ini dilakukan pada mitra sekolah binaan di SMA Negeri 2 Gedong Tataan. Program yang dilakukan adalah In house training peningkatan kompetensi public speaking yang melibatkan semua pengurus OSIS dan perwakilan siswa kelas X dan XI sesuai program kerja yang disetujui oleh pihak sekolah.  Permasalahan yang dialami oleh mitra yaitu: belum optimalnya kemampuan public speaking untuk menunjang kepemimpinan yang berkualitas dalam organisasi di sekolah. Solusi yang diusulkan untuk mengatasi permasalahan tersebut adalah peningkatan softskill bagi siswa terpilih untuk mengikuti bimbingan dan pelatihan public speaking dalam keterampilan berbicara. Target luaran dari kegiatan PKM Sekolah Binaan ini adalah 1) peningkatan kemampuan siswa yang diukur melalui kuesioner, 2) artikel publikasi di jurnal ABDIMAS terakreditasi nasional, 3) artikel berita kegiatan yang dishare di media massa online,  dan 4) video kegiatan di link youtube LPPM Teknokrat
Combination of MOORA and ITARA Methods in Decision Support Systems for Measuring the Performance of Quality Control Teams Hendrastuty, Nirwana; Wang, Junhai; Sulistiyawati, Ari; Darwis, Dedi; Setiawansyah, Setiawansyah; Jumaryadi, Yuwan; Sumanto, Sumanto
TIN: Terapan Informatika Nusantara Vol 6 No 6 (2025): November 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i6.8382

Abstract

The problems that often arise in evaluating the performance of the Quality Control team are the subjectivity in determining the weight of criteria and the limitations of traditional methods in producing objective and consistent rankings. To address this issue, this research integrates the Indifference Threshold-based Attribute Ratio Analysis (ITARA) and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) methods within a decision support system. The ITARA method is used to determine the weights of criteria based on data variation, making them more representative of real conditions, with the result that Accuracy of Product Defect Identification becomes the most dominant criterion with a weight of 0.3999, followed by Response Speed to Issues at 0.1877, while other criteria have lower weights. Furthermore, the MOORA method is used to calculate the preference of alternatives, resulting in a final ranking. The analysis results indicate that the Quality Assurance Team ranks first, followed by the Quality Improvement Team in second place, while the Quality Inspection Team is in the last position. To test the reliability of the model, a sensitivity analysis was conducted by varying the weights of the main criteria. The results show that the ranking structure is relatively stable, with changes only occurring in the positions of the first and second ranks when the accuracy weight is reduced by 0.2. In conclusion, the combination of ITARA-MOORA proves to be capable of producing objective, robust, and reliable performance evaluations as a basis for strategic decision-making in enhancing the quality of the quality control teams.