Journal of Artificial Intelligence and Technology Information https://ejournal.techcart-press.com/index.php/jaiti <p align="justify"><strong>Journal of Artificial Intelligence and Technology Information (JAITI)</strong> is a peer-review journal focusing on Artificial Intelligence and Technology Information issues. <strong>Journal of Artificial Intelligence and Technology Information (JAITI) </strong>invites academics and researchers who do original research in artificial intelligence and technology 1nfromation.<strong>Journal of Artificial Intelligence and Technology Information (JAITI)</strong> is published by <strong>Tech Cart Press</strong> in <strong>March</strong>, <strong>June</strong>, <strong>September</strong>, and <strong>December</strong> every year. <strong>Journal of Artificial Intelligence and Technology Information (JAITI)</strong> accept articles in Bahasa Indonesia and English.</p> <p align="justify"><strong>Journal of Artificial Intelligence and Technology Information (JAITI)</strong> has ISSN&nbsp;<a title="ISSN Online" href="https://issn.brin.go.id/terbit/detail/20230119380863209" target="_blank" rel="noopener"><strong>2985-6396 (Online)</strong></a> in accordance with the letter of Statement Number <strong>29856396/II.7.4/SK.ISSN/02/2023</strong>, and ISSN <a title="ISSN Print" href="https://issn.brin.go.id/terbit/detail/20230119280869503" target="_blank" rel="noopener"><strong>2985-5306 (Print</strong>)</a> in accordance with the letter of Statement Number<strong> 29855306/II.7.4/SK.ISSN/02/2023</strong>.</p> PT. Tech Cart Press en-US Journal of Artificial Intelligence and Technology Information 2985-5306 IT Personnel Recruitment Decision Support System: Combination of TOPSIS and Entropy Weighting Methods https://ejournal.techcart-press.com/index.php/jaiti/article/view/131 <p>IT personnel recruitment is an important process that aims to get the best talent in the field of information technology to support operations and innovation in an organization. IT personnel recruitment faces several key challenges that often make it difficult for companies to find the right candidates. One of the main problems is that the recruitment process can also be constrained by difficulties in assessing a candidate's cultural and interpersonal fit, where high technical skills are not necessarily balanced by good communication and teamwork skills. The purpose of this study is to apply DSS that integrates the TOPSIS and entropy weighting methods in the IT recruitment process, so that it can help companies select the best candidates effectively and objectively. The system is designed to improve the accuracy of candidate identification through multi-criteria analysis. An IT personnel recruitment decision support system that combines TOPSIS and entropy methods is an innovative approach designed to increase effectiveness in selecting the best candidates based on relevant criteria. The results of Candidate G ranking were ranked highest with a score of 0.932, followed by Candidate A with a score of 0.7069, Candidate C with a score of 0.645, and Candidate E with a score of 0.6443. Furthermore, Candidate I in the middle position with a score of 0.5023, followed by Candidate D with a score of 0.3417. Candidate B and Candidate H are in a lower position with values of 0.2188 and 0.1817, respectively. Candidate F ranked at the bottom with a score of 0.0519.</p> Setiawansyah Setiawansyah Copyright (c) 2024 Setiawansyah Setiawansyah https://creativecommons.org/licenses/by-sa/4.0 2024-09-30 2024-09-30 2 3 118 130 10.58602/jaiti.v2i3.131 Kombinasi Metode Rank Reciprocal dan MARCOS Dalam Pemilihan Kinerja Guru Terbaik https://ejournal.techcart-press.com/index.php/jaiti/article/view/132 <p>Problems in teacher performance evaluation often include several aspects that can hinder effectiveness and fairness in the process, especially in subjectivity in assessment. Many evaluation methods still rely on subjective judgments from superiors or peers, which can result in bias and unfairness. The purpose of this study is to develop a more objective and transparent teacher performance evaluation system by combining the reciprocal and MARCOS rank methods. In addition, this research is also to provide effective recommendations in the selection of the best teachers based on relevant criteria, in order to improve the quality of education in related institutions. The combination of the reciprocal rank and MARCOS methods in selecting the best teacher performance is an innovative approach to evaluate and rank teachers based on predetermined criteria, such as pedagogical competence, material mastery, communication skills, and managerial ability. The results of the ranking of the best teacher performance show that Dian Lestari ranks highest with a score of 1.8959, followed by Fitria Sari with a score of 1.8559 and Andi Santoso in third place with a score of 1.8523. These results show that Dian Lestari has the most superior performance compared to her peers in various aspects of the assessment applied.</p> Sandi Badiwibowo Atim Copyright (c) 2024 Sandi Badiwibowo Atim https://creativecommons.org/licenses/by-sa/4.0 2024-09-30 2024-09-30 2 3 131 142 10.58602/jaiti.v2i3.132 Penerapan Metode Simple Additive Weighting dan Pembobotan Entropy Untuk Penentuan Teknisi Terbaik https://ejournal.techcart-press.com/index.php/jaiti/article/view/133 <p>Determining the best technicians in a company is often a challenge due to a variety of factors that need to be considered. Each technician has different advantages and disadvantages, making objective performance measurement difficult. This problem is often exacerbated by the subjectivity of assessments, especially if the evaluation is based solely on the subjective assessment of the supervisor or management team without considering in-depth performance data. The application of the SAW method with entropy weighting for the determination of the best technician is an approach that combines a simple calculation process with objective criterion weighting, based on the degree of variability of data between technicians. The combined application of SAW and entropy provides a fair, objective, assessment system in determining the best technicians, which is able to help companies to identify the technicians with the most superior performance. The results of the analysis of the selection of the best technician using the SAW method show that Technician E is ranked at the top with a final score of 0.8619, making it the best choice based on the criteria that have been assessed. The next ranking was filled by Technician A with a score of 0.8381, and Technician C who obtained a score of 0.8310, showing their excellent performance.</p> Aditia Yudhistira Copyright (c) 2024 Aditia Yudhistira https://creativecommons.org/licenses/by-sa/4.0 2024-09-30 2024-09-30 2 3 143 152 10.58602/jaiti.v2i3.133 Analisis Pemilihan Pemasok Bahan Baku Menggunakan Metode Rank Order Centroid dan SMART https://ejournal.techcart-press.com/index.php/jaiti/article/view/134 <p>Peran pemasok bahan baku sangat krusial dalam memastikan kelancaran produksi, karena kualitas dan ketersediaan bahan baku yang stabil akan memengaruhi efisiensi dan hasil akhir produksi. Pemilihan pemasok bahan baku adalah proses krusial dalam manajemen rantai pasok yang bertujuan untuk menentukan pemasok terbaik berdasarkan kriteria yang relevan bagi kebutuhan produksi. Permasalahan utama dalam pemilihan pemasok bahan baku biasanya mencakup beberapa aspek kritis, seperti kualitas yang tidak konsisten, ketidakpastian pasokan, harga yang berfluktuasi, dan ketepatan waktu pengiriman. Masalah lainnya sering kali mencakup beberapa tantangan utama, seperti kesulitan dalam menentukan kriteria evaluasi yang objektif, kompleksitas pembobotan kriteria, dan keterbatasan data yang akurat. Tujuan penelitian ini adalah untuk mengidentifikasi dan memilih pemasok bahan baku terbaik dengan menerapkan metode rank order centroid dan SMART, yang memberikan pembobotan objektif pada setiap kriteria yang relevan. Penelitian ini juga untuk meningkatkan akurasi dan konsistensi dalam proses pengambilan keputusan pemilihan pemasok, sehingga dapat mendukung efisiensi rantai pasok perusahaan. Hasil peringkat pemasok bahan baku terbaik berdasarkan skor yang diperoleh masing-masing pemasok. Pemasok E menempati peringkat tertinggi dengan skor 0,928, diikuti oleh Pemasok M dengan skor 0,814 dan Pemasok A dengan skor 0,789, yang menunjukkan bahwa ketiga pemasok ini memiliki performa terbaik dalam memenuhi kriteria evaluasi.</p> Puspa Citra I Wayan Sriyasa Copyright (c) 2024 Puspa Citra, I Wayan Sriyasa https://creativecommons.org/licenses/by-sa/4.0 2024-09-30 2024-09-30 2 3 153 162 10.58602/jaiti.v2i3.134 Sistem Pendukung Keputusan Pemilihan Pelanggan Terbaik Menggunakan Metode SD-MOORA https://ejournal.techcart-press.com/index.php/jaiti/article/view/135 <p>Selecting the best customer is an important process in business that aims to recognize high-value customers for the company based on factors such as purchase frequency, transaction value, loyalty, and long-term business potential. However, this process often faces challenges, especially when it comes to objective and consistent measurements. One of the main problems is the complex and dynamic variation of customer data, making it difficult for companies to determine the right metrics to comprehensively assess customers. SPK for selecting the best customers using the SD-MOORA method is a system designed to assist companies in evaluating and selecting the best customers based on various criteria. With the SD-MOORA method, the system can automatically consider changes in data or variability between criteria, making the evaluation process more dynamic and adaptive to data fluctuations. The results of the ranking of the best customers using the SD-MOORA method, Customer 8 occupies the first position with the highest optimization value of 0.39079, followed by Customer 4 who obtained a score of 0.3734. Furthermore, Customer 2 is in third place with a value of 0.35515. These results show that Customer 8 is the best based on optimization value, while Customer 5 is ranked at the bottom.</p> Yuri Rahmanto Copyright (c) 2024 Yuri Rahmanto https://creativecommons.org/licenses/by-sa/4.0 2024-09-30 2024-09-30 2 3 163 172 10.58602/jaiti.v2i3.135