Intelligent Techniques for Decision Support System in Human Resource Management

Jantan, Hamidah; Hamdan, Abdul Razak; Othman, Zulaiha Ali

doi:10.5772/39401

Cited by 19 publications

(8 citation statements)

References 46 publications

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“…Bazen iş zekasına odaklanan sistemler olarak tartışılırlar. Karar Destek Sistemi (KDS), rutin olmayan kararlar almak için üst yönetim tarafından kullanılır (Jantan, 2010). Karar destek sistemleri, iç sistemlerden (işlem işleme sistemleri ve yönetim bilgi sistemleri) ve harici sistemlerden gelen girdileri kullanır.…”

Section: Ybs İçi̇n Başlangiç Noktasi: Hareket İşleme Si̇stemi̇ (Hi̇s)unclassified

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Yenilikçi Endüstri 4.0 Paradigması Kapsamında Kurumsal Kaynak Planlaması ve Yönetim Bilişim Sistemlerinde Yapay Zeka

Efe¹

2021

Pamukkale Üniversitesi İşletme Araştırmaları Dergisi

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Yapay zekâ (YZ), günümüzde iş zorluklarının çoğuna etkililiğin, ekonomikliğin ve verimliliğin şaşırtıcı düzeyde arttırılması noktasında otomatik ve otonom çözümler sunabilmektedir. Örneğin, imalat endüstrisinde YZ tarafından desteklenen otomasyon, otomobil üretim şirketlerini sürücüsüz otomobilleri ve diğer endüstri 4.0 fırsatlarıyla piyasa zirvesine taşıdı. Buna benzer şekilde özellikle kurumsal kaynak planlaması (KKP), akıllı şehir, akıllı bina, yeşil enerji uygulamaları ile ev otomasyon sistemleri inanılmaz hızlı bir şekilde ilerleme göstermiştir. YZ'nin farklı ekonomik, kurumsal süreçler ve teknik alanlarında daha ne kadar ilerleme sağlayabileceğini değerlendirmek ve anlamak önem arz etmektedir. Literatür taraması, endüstriyel raporlar ile kilit sektör aktörlerine ait internet verilerinin analizine dayanan bu çalışma, YZ uygulamasının son on yıl içinde bilişim sistemleri otomasyonunu geliştirip geliştirmediğine, nasıl dönüştüğüne ve tüm yenilikçi YBS ile KKP uygulama ve türlerinde yakın zamanda daha ileriye gitme potansiyeli için genel bir bakış ve öneriler sunmaktadır.Artificial Intelligence (AI) can offer automated and autonomous solutions to most business challenges today, surprisingly increasing efficiency, affordability, and productivity. For example, automation in the manufacturing industry, powered by artificial intelligence, has brought auto manufacturing companies to the top of the market with driverless cars and other industry 4.0 opportunities. Similarly, especially with enterprise resource planning (ERP), smart city, smart building, green energy applications, home automation systems have progressed incredibly rapidly. It is essential to evaluate and understand how much progress can be achieved using artificial intelligence effectively in the economy, corporate processes, and technical aspects. This study depends on a literature survey, analysis of industrial reports, and websites of key actors to provide an overview of whether and how AI implementation has improved and transformed information systems automation over the past decade. Furthermore, it gives suggestions for the potential of going further in all innovative MIS and ERP implementations.

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Section: Ybs İçi̇n Başlangiç Noktasi: Hareket İşleme Si̇stemi̇ (Hi̇s)unclassified

“…• Banka kredi yönetim sistemleri: Kredi başvurusunda bulunan kişinin kredisini doğrulamak ve kredinin geri kazanılma olasılığını tahmin etmek için kullanılır. (Jantan, 2010).…”

Section: Ybs İçi̇n Başlangiç Noktasi: Hareket İşleme Si̇stemi̇ (Hi̇s)unclassified

Yenilikçi Endüstri 4.0 Paradigması Kapsamında Kurumsal Kaynak Planlaması ve Yönetim Bilişim Sistemlerinde Yapay Zeka

Efe¹

2021

Pamukkale Üniversitesi İşletme Araştırmaları Dergisi

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“…Strohmeier and Piazza [15] proposed an improved density-based distributed clustering algorithm, applied the cluster analysis model based on the improved density clustering algorithm of performance evaluation, and developed and implemented a performance evaluation system. Jantan et al studied the application of data mining in talent recruitment selection, using decision tree method and neural network method to deal with network recruitment [16]. Kale and Patil improved and expanded the genetic operator of the standard genetic algorithm, optimized the fuzzy clustering method based on this improved genetic algorithm, and applied it to the human resource management system [17].…”

Section: Introductionmentioning

confidence: 99%

Human Resource Allocation Based on Fuzzy Data Mining Algorithm

Wang

2021

Complexity

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Data mining is currently a frontier research topic in the field of information and database technology. It is recognized as one of the most promising key technologies. Data mining involves multiple technologies, such as mathematical statistics, fuzzy theory, neural networks, and artificial intelligence, with relatively high technical content. The realization is also difficult. In this article, we have studied the basic concepts, processes, and algorithms of association rule mining technology. Aiming at large-scale database applications, in order to improve the efficiency of data mining, we proposed an incremental association rule mining algorithm based on clustering, that is, using fast clustering. First, the feasibility of realizing performance appraisal data mining is studied; then, the business process needed to realize the information system is analyzed, the business process-related links and the corresponding data input interface are designed, and then the data process to realize the data processing is designed, including data foundation and database model. Aiming at the high efficiency of large-scale database mining, database development tools are used to implement the specific system settings and program design of this algorithm. Incorporated into the human resource management system of colleges and universities, they carried out successful association broadcasting, realized visualization, and finally discovered valuable information.

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“…The foundations for the application of intelligent machine systems in human resource management have been laid, however there are still many problem domains where tools are needed to transform uncertain and incomplete data into useful knowledge. In general, the approaches of machine learning and hybrid intelligence show their usefulness and effectiveness [5], but their application is still little studied in relation to talent management.…”

Section: Introductionmentioning

confidence: 99%

Decision Support System for an Art University

Vecherskaya

2021

IJSEPM

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A prototype of an automated decision support system for creative universities has been developed, which will allow assessing the achievements particularly talented students and identifying the needs in the learning process in order to help organize the educational process in accordance with identified capabilities. Use of a decision support system based on the Bayesian classifier is suggested which will allow to evaluate factors contributing to the progress in teaching students particular techniques, and in perspective to assess the possible resources that will be required to make changes to the learning. The list of specific performance indicators is given. The system should contribute to the formation of the learning plan, taking into account the capabilities of both a group art workshop as a whole, and special needs of an individual to develop, if necessary an individual approach.

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Intelligent Techniques for Decision Support System in Human Resource Management

Cited by 19 publications

References 46 publications

Yenilikçi Endüstri 4.0 Paradigması Kapsamında Kurumsal Kaynak Planlaması ve Yönetim Bilişim Sistemlerinde Yapay Zeka

Yenilikçi Endüstri 4.0 Paradigması Kapsamında Kurumsal Kaynak Planlaması ve Yönetim Bilişim Sistemlerinde Yapay Zeka

Human Resource Allocation Based on Fuzzy Data Mining Algorithm

Decision Support System for an Art University

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