https://journal.its.ac.id/index.php/ijbmts <p><strong>International Journal of Business and Management Technology in Society (IJBMTS)</strong> is a peer-reviewed, open-access journal published by the Scientific Publication Center (PPI) under the Directorate of Research and Community Service at the Institut Teknologi Sepuluh Nopember Surabaya. The journal publishes original research articles, review articles, and case studies in the fields of business, management, and management of technology. The journal is published twice a year in May and November and all articles submitted are in English. The papers submitted to IJBMTS should not have been published or be under consideration for publication elsewhere.</p> en-US sri.yayu@its.ac.id (Sri Yayu Ninglasari) prahardika@its.ac.id (Prahardika Prihananto) Wed, 14 May 2025 05:48:17 +0000 OJS 3.2.1.3 http://blogs.law.harvard.edu/tech/rss 60 https://journal.its.ac.id/index.php/ijbmts/article/view/1341 <p><strong>Purpose</strong> – This study aims to optimize delivery operations by implementing a flexible clustering method to handle demand uncertainty and improve logistics efficiency.</p> <p><strong>Methodology</strong> – This study develops a clustering algorithm using a two-dimensional time-warping approach to group demand points based on spatial proximity and demand characteristics. The methodology consists of three stages: 1) processing data on point distances, 2) clustering using two-dimensional time warping, and 3) validating through silhouette analysis.</p> <p><strong>Findings</strong> – This study resulted in optimal and efficient demand clustering through location clustering with a Silhouette coefficient value of 0.7 or an accuracy and feasibility level of 70%. The algorithm also shows improved computational efficiency compared to traditional approaches, making it suitable for practical applications in uncertain and dynamic environments.</p> <p><strong>Practical implications </strong>– This study holds significant importance for businesses in the logistics and retail sectors. Through demand clustering, businesses can effectively group customer demands and utilize this information to optimize inventory management and delivery solutions.</p> Prita Meilanitasari, Iwan Vanany, Mochamad Nizar Palefi Ma'ady, Nisa Isrofi Copyright (c) 2025 International Journal of Business and Management Technology in Society https://creativecommons.org/licenses/by/4.0 https://journal.its.ac.id/index.php/ijbmts/article/view/1341 Fri, 16 May 2025 00:00:00 +0000 https://journal.its.ac.id/index.php/ijbmts/article/view/1023 <p><strong>Purpose</strong> – This research aims to show research trends in the field of AI implementation in the human resources realm and its relationship with human resource productivity</p> <p><strong>Methodology </strong>– This research combines bibliometric analysis with content analysis methods. Bibliometric analysis is carried out by quantitative and statistical analysis of a set of data that is linked using bibliometric indicators that represent a set of topics that are the research area in this study. Then the findings from the bibliometric method are supported by content analysis from various studies in this research area, so that it can produce output with a clearer perspective.</p> <p><strong>Findings </strong>– This research show that Artificial Intelligence (AI) can have significant effect on productivity in some case, but it must also be acknowledged that companies must also be wise in ensuring that the work to be adapted with the help of AI is appropriate, because the implementation of AI has not yet reached the point where all human work can be assisted or replaced by AI.</p> <p><strong>Research Limitation</strong> – This research was conducted only through the findings on several previous research, articles, and the data obtained from Scopus only.</p> <p><strong>Practical Implications </strong>– Based on the bibliometric analysis of recent trends in AI technology and its impact on human resource productivity, it is recommended that organizations invest in AI-based HR tools and systems to improve their productivity and efficiency. The study highlights the need for HR professionals to stay up to date with the latest AI trends and technologies to remain competitive in the job market.</p> Zahril Maulana Jilham Al'ula, Astra Savero Qomara, Tyassatrio Kuncorowibowo, Syarifa Hanoum Copyright (c) 2025 International Journal of Business and Management Technology in Society https://creativecommons.org/licenses/by/4.0 https://journal.its.ac.id/index.php/ijbmts/article/view/1023 Fri, 16 May 2025 00:00:00 +0000