RISK PERCEPTION AND DATA MINING IN THE IRON AND STEEL INDUSTRY

Year 2021, Volume: 5 Issue: 2, 313 - 325, 31.08.2021

Taner Ersöz Bennur Bulut

https://doi.org/10.46519/ij3dptdi.958712

Cited By: 1

Abstract

Risk is the possibility of threat, that is, potential harm. There may be risks like price fluctuations, exchange rate changes, demand and request changes, and inaccessibility of the material for an enterprise. The biggest mistake is to consider the risk as a possibly harmful circumstance that should only be avoided. When the risk is successfully managed, it empowers the formation of exceptionally imperative vital steps for businesses. Businesses have to show serious patterns to understand, anticipate, prevent, reduce and manage risk correctly and avoid the conceivable loss of life and property. A culture of trust is created in companies that understand the risk correctly and manages it with the right steps. The culture of trust prevents workers from getting distracted, as well as enabling workers to embrace the job and do their job lovingly. Thus, productivity increases in the long run. The purpose of this study is to determine the risk perception of the employees of a firm operating in the iron and steel industry. Possible risks are always high as the enterprise operates as a heavy industry. The questionnaire applied to the employees consists of two parts. The first part consists of demographic features, and the second part consists of questions regarding employees' perceptions of risk. According to the findings which will be obtained with the help of the research, the effect levels of the demographic characteristics of the employees on the employees will be determined and improved findings will be presented to the business management. According to the socio - demographic status of the employees in the enterprise, it is pointed to uncover the risk discernment levels by cluster analysis.

Keywords

Perception of risk, risk concept, iron and steel industry, work safety, data mining

RISK PERCEPTION AND DATA MINING IN THE IRON AND STEEL INDUSTRY

Abstract

Risk is the possibility of threat, that is, potential harm. There may be risk price fluctuations, exchange rate changes, demand and request changes, and inaccessibility of the material for an enterprise. The biggest mistake is to consider the risk as a possibly harmful circumstance that should only be avoided. Since, when the risk is successfully managed, it empowers the formation of exceptionally imperative vital steps for businesses. Businesses have to show serious patterns to understand, anticipate, prevent, reduce and manage risk correctly and avoid the conceivable loss of life and property. A culture of trust is created in companies that understand the risk correctly and manage it with the right steps. The culture of trust prevents workers from getting distracted, as well as enabling workers to embrace the job and do their job lovingly. Thus, productivity increases in the long run. The purpose of this study is to determine the risk perception of the employees of a firm operating in the iron and steel industry. Possible risks are always high as the enterprise operates as heavy industry. The questionnaire applied to the employees consists of two parts. The first part consists of demographic features and the second part consists of questions regarding employees' perceptions of risk. According to the findings which will be obtained with the help of the research, the effect levels of the demographic characteristics of the employees on the employees will be determined and improved findings will be presented to the business management. According to the socio-economic and demographic status of the employees in the enterprise, it is pointed to uncover the risk discernment levels by cluster analysis.

Keywords

Perception of risk, risk concept, iron and steel industry, work safety, data mining

References

• [1] Ersöz F. Veri Madenciliği Teknikleri ve Uygulamaları, Seçkin Yayıncılık, Ankara. 2019. s303.
• [2] Dolgui A, Bakhtadze N, Pyatetsky V, Sabitov R, Smirnov G, Elpashev D, Zakharov E. Data Mining-Based Prediction of Manufacturing Situations. Science Direct. 2018: 316-321.
• [3] Parmaksız A, Ersöz T, Özseven T, Ersöz F. Çalışanların İş Memnuniyeti, İş Stresi ve Ergonomik Koşullarının Değerlendirilmesi. Gaziosmanpaşa Bilimsel Araştırma Dergisi. 2013: 82-99
• [4] Bilgin B. Ankara’da Araç Kullanan Sürücülerin Risk Algısı, Kişilik ve Trafik Güvenliği Unsurlarına Karşı Tutumlarının Riskli Sürüş Davranışları-Kaza Riski Üzerine Etkisi İle İlgili Çalışma (Yüksek Tezi). Ankara 2016. http://hdl.handle.net/11727/2642
• [5] Altunkaynak B. A Statistical Study of Occupational Accidents in The Manufacturing Industry in Turkey, International Journal of Industrial Ergonomics. 2018: 101-109.
• [6] [Geçer C. Adana’da İş Yükü, İklim ve Güvenliğin Risk Algısı Üzerine Etkileri için Bir Uyulama. Afyon 2019.
• [7] Ayanoğlu C, Kurt M. Metal Sektöründe Veri Madenciliği Yöntemleri ile bir İş Kazası Tahmin Modeli Önerisi. Ergonomi. 2019: 78-87.
• [8] Çelenk Kaya E, Ölmezoğlu İri N. Ahşap ve Mobilya İmalatı Yapan Bir İşyerinde Risklerin Belirlenmesi ve Örnek Risk Analiz Çalışması. Gümüşhane Üniversitesi Sağlık Bilimleri Dergisi. 2020: 25-35.
• [9] Bilgin E, Esen F. Endüstri 4.0 Işığında Veri Madenciliği ve Pazarlama: Son Gelişmeler, Yeni Trendler. 2018: 21-29.
• [10] Farzad G. Human Incidents Analysis by Knowledge Discovery Method in a Steel Maker Company. 2014: 327-333.
• [11] Ecemiş O, Irmak S. Paslanmaz Çelik Sektörü Satış Tahmininde Veri Madenciliği Yöntemlerinin Karşılaştırılması. Kilis 7 Aralık Sosyal Bilimler Dergisi. 2018: 148-169.
• [12] Ciarapica E. F, Giacchetta G. Classification and Prediction of Occupational Injury Risk Using Soft Computing Techniques: An Italian Study. Safety Science. 2009: 36-49
• [13] Gliowar R. Kemeny, Nemeth Z, Matyas T, Monostori K, L. & Sihn, W. A Holistic Approach to Quality-Focused Maintenance Planning Supported by Data Mining Methods,” Procedia Corp. 2016: 259-264.
• [14] Topaloğlu G, Koç A, Yağlı H, Adil Öztürk N. Yüksek Fırınların İşletilmesinde Risk Değerlendirilmesinin Yapılması ve Geliştirilmesi,” Mühendis ve Makine. 2015: 55-63.
• [15] Güler İ, Kutay Karaçor E. Yer Bağlılığı ve Risk Algısı Kavramları Arasındaki İlişki. Düzce Üniversitesi Bilim ve Teknoloji Dergisi. 2018: 1377-1390. [16] Newman L, Rose C, Eddy, Bresnitz A. American Journal of Respiratory and Critical Care Medicine. 2004: 1327-1330.
• [17] Comberti L, Baldissone G, Demichela M. Workplace Accidents Analysis with a Coupled Clustering Methods: S.O.M. and K-means Algorithms. Chemical Engineering Transactions. 2015: 1261- 1266.
• [18] Kocabaş M. Ağır ve Tehlikeli İşlerde Çalışan İş Görenlerde Zorlanmaya Neden Olan Çalışma Duruşlarının Analizi. Selçuk Üniversitesi. 2009.
• [19] Gül M, Güneri A.F, Yılmaz F, Çelebi O. Analysis of The Relation Between the Characteristics of Workers and Occupational Accidents Using Data Mining. The Turkish Journal of Occupational / Environmental Medicine and Safety. 2016: 102-118.
• [20] Ersöz T. Demir Çelik Sektöründe İş Kazalarının Analizi, Ekin Yayınevi. Bursa. 2019. s124.
• [21] Ersöz T , Sarız K ,Ersöz F . Demir-Çelik Üretim Hattında Yalın Üretim . Düzce Üniversitesi Bilim ve Teknoloji Dergisi , 8 (1) , 2020: 801-826