A Data Mining Application for Classification of Performance Values Under the Conditions of Digitalization of HR Processes

Gözde Katırcıoğlu; Emel Kızılkaya Aydogan; Yılmaz Delice

Makale detayları

A Data Mining Application for Classification of Performance Values Under the Conditions of Digitalization of HR Processes

Yazarlar:

Gözde Katırcıoğlu | Emel Kızılkaya Aydogan | Yılmaz Delice

Yayıncı:

Süleyman Demirel University

Ana Başlıklar:

İnsan Kaynakları Yönetimi

Dergi:

Süleyman Demirel Üniversitesi İnsan Kaynakları Yönetimi Dergisi Vol.2 Issue 2, pp.44-53

Belge Tipi:

Makale

Yayın Tarihi:

12/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001309132

pISSN:

2979-997X

Anahtar kelimeler:

Özet:

 Human resources management is the key to maintaining and developing quality personnel in modern companies. Analyzing the human resources data of institutions, identifying problems, and determining the strategy provide a significant competitive advantage. The topic of digitalization of human resources management in businesses is increasing day by day. With the fourth industrial revolution, also known as Industry 4.0, digitalization also affects human resources management HRM, which is seen as the basis of corporate business and transactions. In this field, more and more businesses are investing in human resources management, which increases efficiency and savings with artificial intelligence and data mining methods. Data mining applications are used to make sense of data and transform it into information and to assist organizations in decision-making processes. The aim of the present study is to examine the impact of digitalization on human resources management practices and to identify trends in this regard. In this context, decision tree and rule extraction algorithms, which are data mining methods, were used. Experiments and comparison studies conducted on real data have revealed that it is quite good at categorizing the available data. The rules obtained enabled the company to have insight into the behavior of potential employee candidates. The importance of this study is to reveal the positive effects of digitalization and artificial intelligence in the business world on human resources management with the developed technique.

 Human resources management is the key to maintaining and developing quality personnel in modern companies. Analyzing the human resources data of institutions, identifying problems, and determining the strategy provide a significant competitive advantage. The topic of digitalization of human resources management in businesses is increasing day by day. With the fourth industrial revolution, also known as Industry 4.0, digitalization also affects human resources management HRM, which is seen as the basis of corporate business and transactions. In this field, more and more businesses are investing in human resources management, which increases efficiency and savings with artificial intelligence and data mining methods. Data mining applications are used to make sense of data and transform it into information and to assist organizations in decision-making processes. The aim of the present study is to examine the impact of digitalization on human resources management practices and to identify trends in this regard. In this context, decision tree and rule extraction algorithms, which are data mining methods, were used. Experiments and comparison studies conducted on real data have revealed that it is quite good at categorizing the available data. The rules obtained enabled the company to have insight into the behavior of potential employee candidates. The importance of this study is to reveal the positive effects of digitalization and artificial intelligence in the business world on human resources management with the developed technique.

 Human resources management is the key to maintaining and developing quality personnel in modern companies. Analyzing the human resources data of institutions, identifying problems, and determining the strategy provide a significant competitive advantage. The topic of digitalization of human resources management in businesses is increasing day by day. With the fourth industrial revolution, also known as Industry 4.0, digitalization also affects human resources management HRM, which is seen as the basis of corporate business and transactions. In this field, more and more businesses are investing in human resources management, which increases efficiency and savings with artificial intelligence and data mining methods. Data mining applications are used to make sense of data and transform it into information and to assist organizations in decision-making processes. The aim of the present study is to examine the impact of digitalization on human resources management practices and to identify trends in this regard. In this context, decision tree and rule extraction algorithms, which are data mining methods, were used. Experiments and comparison studies conducted on real data have revealed that it is quite good at categorizing the available data. The rules obtained enabled the company to have insight into the behavior of potential employee candidates. The importance of this study is to reveal the positive effects of digitalization and artificial intelligence in the business world on human resources management with the developed technique.

 İnsan kaynakları yönetimi, modern şirketlerde kaliteli personeli korumanın ve geliştirmenin anahtarıdır. Kurumların insan kaynakları verilerinin analiz edilmesi, sorunların tespit edilmesi ve stratejinin belirlenmesi avantaj sağlamaktadır. İşletmelerde insan kaynakları yönetiminin İKY dijitalleşmesi konusu her geçen gün artmaktadır. Endüstri 4.0 olarak da bilinen dördüncü sanayi devrimiyle birlikte dijitalleşme, kurumsal iş ve işlemlerin temeli olarak görülen insan kaynakları yönetimini de etkilemektedir. Bu alanda giderek daha fazla işletme, yapay zeka ve veri madenciliği yöntemleriyle verimliliği ve tasarrufu artıran insan kaynakları yönetimine yatırım yapmaktadır. Veri madenciliği uygulamaları ise, verileri anlamlandırıp bilgiye dönüştürmek ve kuruluşlara karar verme süreçlerinde yardımcı olmak amacıyla kullanılmaktadır. Bu çalışmanın amacı dijitalleşmenin insan kaynakları yönetimi uygulamaları üzerindeki etkisini incelemek ve bu konudaki eğilimleri tespit etmektir. Bu kapsamda veri madenciliği yöntemlerinden karar ağacı ve kural çıkarma algoritmaları kullanılmıştır. Gerçek veriler üzerinde yapılan deneyler ve karşılaştırma çalışmaları, mevcut verileri kategorize etme konusunda oldukça iyi olduğunu ortaya koymuştur. Elde edilen kurallar, şirketin potansiyel çalışan adaylarının davranışları hakkında fikir sahibi olmasını sağlamıştır. Bu çalışmanın önemi, iş dünyasında dijitalleşmenin ve yapay zekanın insan kaynakları yönetimine olumlu etkilerini geliştirilen teknikle ortaya koymaktır.

Makale detayları

A Data Mining Application for Classification of Performance Values Under the Conditions of Digitalization of HR Processes

Yazarlar:

Gözde Katırcıoğlu | Emel Kızılkaya Aydogan | Yılmaz Delice

Yayıncı:

Süleyman Demirel University

Ana Başlıklar:

İnsan Kaynakları Yönetimi

Dergi:

Süleyman Demirel Üniversitesi İnsan Kaynakları Yönetimi Dergisi Vol.2 Issue 2, pp.44-53

Belge Tipi:

Makale

Yayın Tarihi:

12/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001309132

pISSN:

2979-997X

Human Resources Management (HRM)

Data Mining

Digitalization

Decision Treeİnsan Kaynakları Yönetimi (İKY)

Veri Madenciliği

Dijitalleşme

Karar Ağacı

Sayı

Makale detayları

Yazarlar: Gözde Katırcıoğlu | Emel Kızılkaya Aydogan | Yılmaz Delice

Yayıncı: Süleyman Demirel University

Ana Başlıklar: İnsan Kaynakları Yönetimi

Dergi: Süleyman Demirel Üniversitesi İnsan Kaynakları Yönetimi Dergisi Vol.2 Issue 2, pp.44-53

Belge Tipi: Makale

Yayın Tarihi: 12/2023

Belge Dili: İngilizce

Document ID (Org No.): 2001309132

pISSN: 2979-997X

Sayı

Yazarlar:

Gözde Katırcıoğlu | Emel Kızılkaya Aydogan | Yılmaz Delice

Yayıncı:

Süleyman Demirel University

Ana Başlıklar:

İnsan Kaynakları Yönetimi

Dergi:

Süleyman Demirel Üniversitesi İnsan Kaynakları Yönetimi Dergisi Vol.2 Issue 2, pp.44-53

Belge Tipi:

Makale

Yayın Tarihi:

12/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001309132

pISSN:

2979-997X