Phân tích các yếu tố ảnh hưởng đến mức độ nghiêm trọng của tai nạn nghề nghiệp trong ngành dệt may bằng cách sử dụng thuật toán cây quyết định

Eurostat-NACE, Rev.2: Statistical Classification of Economic Activities in the European Community. Eurostat Methodologies and Working Papers. European Commission (2008). https://ec.europa.eu/eurostat/documents/3859598/5902521/KS-RA-07-015-EN.PDF. Accessed 20 May 2020 Karupannan, K.P., Arularasu, M., Devadasan, S.R.: Modern safety and training method implementation in different type of textile sectors. Int. J. Appl. Bus. Econ. Res. 14(14), 799–816 (2016) Kassaneh, T.C., Tadesse, A.A. (Fasikaw Atanaw Zimale): Evaluation of workplace environmental ergonomics and method development for manufacturing industries. In: International Conference on Advances of Science and Technology, Bahir Dar, Ethiopia, October 2018, pp. 102–112. https://doi.org/10.1007/978-3-030-15357-1_8 TISDAP: Turkish Textile Industry Strategy Document and Action Plan (2015–2018). TISDAP (2015). https://www.resmigazete.gov.tr/eskiler/2015/06/20150625-6-1.pdf. Accessed 14 Feb 2020 TEER: Textile Exporters Evaluation Report. TEER (2018–2019). https://www.ithib.org.tr/tr/bilgi-bankasi-raporlar-donemsel.html. Accessed 4 Feb 2020 Uyanık, S., Çelikel, D.C.: The general situation of textile industry in Turkey. J. Technol. Sci. 9(1), 32–41 (2019) Marmo, L., Ferri, A., Danzi, E.: Dust explosion hazard in the textile industry. J. Loss Prev. Process Ind. 62, 103935 (2019). https://doi.org/10.1016/j.jlp.2019.103935 Shaikh, M.A., Weiguo, S., Shahid, M.U., Ayaz, H., Ali, M.: An assessment of hazards and occupational health and safety practices for workers in the textile industry: a case study. J. Acad. Res. Bus. Soc. Sci. 8(12), 333–347 (2018). https://doi.org/10.6007/IJARBSS/v8-i12/5016 Yilmaz, F., Alp, S.: Underlying factors of occupational accidents: the case of Turkey. Open J. Saf. Sci. Technol. 6(1), 1–10 (2016). https://doi.org/10.4236/ojsst.2016.61001 Nag, P.K., Nag, A., Vyas, H.: Nonfatal accident analyses in the textile industry in India. In: Ergonomics in Developing Regions, pp. 281–290. CRC Press, Boca Raton (2009) Rasmussen, J.: Risk management in a dynamic society: a modelling problem. Saf. Sci. 27(2–3), 183–213 (1997). https://doi.org/10.1016/S0925-7535(97)00052-0 Kökten, M., Avinç, O.: Responsibility of an employer according to the Occupational Health and Safety Law No. 6331 and a glance for the textile industry. J. Text. Eng. 21(93), 33–47 (2014). https://doi.org/10.7216/130075992014219305 SSI Annual Statistics, 2013–2019. http://www.sgk.gov.tr/wps/portal/sgk/tr/kurumsal/istatistik/sgk_istatistik_yilliklari. Accessed 15 Dec 2020 Kjellén, U.: Prevention of Accidents Through Experience Feedback. CRC Press, Boca Raton (2000) Parvin, N., Prova, A.A., Tabassum, M.: Casualty reduction intelligent system based on classified prediction and comparative analysis of industrial mishaps. In: 2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC), December 2017, pp. 474–480. IEEE, Bangladesh (2017). https://doi.org/10.1109/R10-HTC.2017.8289002 Carrillo-Castrillo, J.A., Rubio-Romero, J.C., Onieva, L.: Causation of severe and fatal accidents in the manufacturing sector. Int. J. Occup. Saf. Ergon. 19(3), 423–434 (2013). https://doi.org/10.1080/10803548.2013.11076999 Güllüoğlu, E.N., Taçgın, E.: Analysis of employment and work accidents in Turkish textile sector. J. Text. Eng. 25(112), 344–354 (2018). https://doi.org/10.7216/1300759920182511208 Serinken, M., Türkçüer, İ, Dağlı, B., Karcıoğlu, Ö., Zencir, M., Uyanık, E.: Work-related injuries in textile industry workers in Turkey. Ulus. Travma Acil Cerrahi Derg. 18(1), 31–36 (2012). https://doi.org/10.5505/tjtes.2012.54376 Lee, K.S., Jeong, B.Y.: Characteristics and prevention of occupational accidents in the small-sized textile industry. J. Ergon. Soc. Korea 28(4), 101–107 (2009). https://doi.org/10.5143/JESK.2009.28.4.101 Nag, P.K., Patel, V.G.: Work accidents among shift workers in industry. Int. J. Ind. Ergon. 21(3–4), 275–281 (1998). https://doi.org/10.1016/S0169-8141(97)00050-4 Mutlu, N.G., Altuntas, S.: Hazard and risk analysis for ring spinning yarn production process by integrated FTA–FMEA approach. Text. Appar. 29(3), 208–218 (2019). https://doi.org/10.32710/tekstilvekonfeksiyon.482167 Mutlu, N.G., Altuntas, S.: Risk analysis for occupational safety and health in the textile industry: integration of FMEA, FTA, and BIFPET methods. Int. J. Ind. Ergon. 72, 222–240 (2019). https://doi.org/10.1016/j.ergon.2019.05.013 Efe, Ö., Efe, B.: Evaluation of ergonomics risks belong to formation of work accidents in the textile sector. J. Eng. Sci. Des. 3(3), 623–629 (2015). https://doi.org/10.29137/umagd.798215 Roger, B.L.: Safety and Health for Engineers, p. 26. Wiley, Tolono (2006) Hussain, N., Kadir, M.M., Nafees, A.A., Karmaliani, R., Jamali, T.: Needs assessment regarding occupational health and safety interventions among textile workers: a qualitative case study in Karachi, Pakistan. J. Pak. Med. Assoc. 69(1), 87 (2019) Kabakulak, T.: Risk assessment application in a textile company: 5 × 5 matrix and HAZOP. Karaelmas J. Occup. Health Saf. 3(2), 97–111 (2019). https://doi.org/10.33720/kisgd.581677 Lee, J., Hahm, M., Huh, D.A., Byeon, S.H.: Prioritizing type of industry through health risk assessment of occupational exposure to dimethylformamide in the workplace. Int. J. Environ. Res. Public Health 15(3), 503 (2018). https://doi.org/10.3390/ijerph15030503 Menegon, L.D.S., Menegon, F.A., Maeno, M., Kupek, E.: Incidence and time trend of occupational accidents in the textile and clothing industry: analysis of Santa Catarina, Brazil, between 2008 and 2017. Rev. Bras. Epidemiol. (2021). https://doi.org/10.1590/1980-549720210005 Mberikunashe, J., Banda, S., Chadambuka, A., Gombe, N.T., Shambira, G., Tshimanga, M., Matchaba-Hove, R.: Prevalence and risk factors for obstructive respiratory conditions among textile industry workers in Zimbabwe, 2006. Pan Afr. Med. J. (2010). https://doi.org/10.4314/pamj.v6i1.69063 Nafees, A.A., De Matteis, S., Kadir, M.M., Burney, P., Coggon, D., Semple, S., Cullinan, P.: MultiTex RCT—a multifaceted intervention package for protection against cotton dust exposure among textile workers—a cluster randomized controlled trial in Pakistan: study protocol. Trials 20(1), 1–10 (2019). https://doi.org/10.1186/s13063-019-3743-3 Manimaran, S., Rajalakshmi, R., Bhagyalakshmi, K.: A model of Occupational Safety and Health Management System (OSHMS) for promoting and controlling health and safety in textile industry. Technol. Health Care 23(1), 1–8 (2015). https://doi.org/10.3233/THC-140866 Turkalj, I., Mikov, I., Jovanovic, M., Brkic, S., Mikov, A., Petrovic, V.: Occupational skin diseases in Autonomous Province of Vojvodina. HealthMED 6(2), 531–536 (2012) Jung, M., Lim, S., Chi, S.: Impact of work environment and occupational stress on safety behavior of individual construction workers. Int. J. Environ. Res. Public Health 17(22), 8304 (2020). https://doi.org/10.3390/ijerph17228304 Mutlu, N.G., Altuntas, S.: Assessment of occupational risks in Turkish manufacturing systems with data-driven models. J. Manuf. Syst. 53, 169–182 (2019). https://doi.org/10.1016/j.jmsy.2019.09.008 Kirin, S., Vučinić, J., Štedul, I.: Results of application of basic workplace safety rules on the reduction of work-related injuries. Sigurnost časopis za sigurnost u radnoj i životnoj okolini 51(3), 223–228 (2009) Shirali, G.A., Noroozi, M.V., Malehi, A.S.: Predicting the outcome of occupational accidents by CART and CHAID methods at a steel factory in Iran. J. Public Health Res. 7(2), jphr-2018 (2018). https://doi.org/10.4081/jphr.2018.1361 Amiri, M., Ardeshir, A., Soltanaghaei, E.: Analysis of high risk occupational accidents in construction industry using data-mining methods. Iran Occup. Health 11(4) (2014). http://ioh.iums.ac.ir/article-1-1002-en.html Sarkar, S., Raj, R., Vinay, S., Maiti, J., Pratihar, D.K.: An optimization-based decision tree approach for predicting slip–trip–fall accidents at work. Saf. Sci. 118, 57–69 (2019). https://doi.org/10.1016/j.ssci.2019.05.009 Fiskin, R., Cakir, E., Sevgili, C.: Decision tree and logistic regression analysis to explore factors contributing to harbour tugboat accidents. J. Navig. 74(1), 79–104 (2021). https://doi.org/10.1017/S0373463320000363 Çakir, E.: Determinants of medical evacuations from merchant cargo ships: evidence from Telemedical Assistance Service of Turkey data. Ocean Coast. Manag. 211, 105797 (2021). https://doi.org/10.1016/j.ocecoaman.2021.105797 de Oña, J., López, G., Abellán, J.: Extracting decision rules from police accident reports through decision trees. Accid. Anal. Prev. 50, 1151–1160 (2013). https://doi.org/10.1016/j.aap.2012.09.006 Eurostat European Commission: European Statistics on Accidents at Work (ESAW)—Summary Methodology. Eurostat Methodologies and Working Paper. European Commission (2013). ISBN: 978-92-79-28419-9 Al-Behadili, H.N.K., Ku-Mahamud, K.R., Sagban, R.: Genetic-based pruning technique for ant-miner classification algorithm. Int. J. Adv. Sci. Eng. Inf. Technol. 11(1), 304 (2021) Revathy, V.R., Pillai, A.S.: Binary emotion classification of music using deep neural networks. In: International Conference on Soft Computing and Pattern Recognition, December 2021, pp. 484–492. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-96302-6_45 Khalifa, R.M., Yacout, S., Bassetto, S.: Developing machine-learning regression model with Logical Analysis of Data (LAD). Comput. Ind. Eng. 151, 106947 (2021). https://doi.org/10.1016/j.cie.2020.106947 Rokach, L., Maimon, O.: Supervised learning. In: Data Mining and Knowledge Discovery Handbook, pp. 133–147. Springer, Boston (2010a). https://doi.org/10.1007/978-0-387-09823-4 Stallard, T., Levitt, K.: Automated analysis for digital forensic science: semantic integrity checking. In: 19th Annual Computer Security Applications Conference, 2003. Proceedings, December 2003, pp. 160–167. IEEE (2003). https://doi.org/10.1109/CSAC.2003.1254321 Hur, J., Lee, H., Baek, J.G..: An intelligent manufacturing process diagnosis system using hybrid data mining. In Industrial Conference on Data Mining, July 2006, pp. 561–575. Springer, Berlin (2006). https://doi.org/10.1007/11790853_44 Sadic, S., Kayakutlu, G.: Integrating decision trees and cognitive maps for market segmentation in service sector. In: PICMET'07—2007 Portland International Conference on Management of Engineering and Technology, August 2007, pp. 2748–2754. IEEE (2007). https://doi.org/10.1109/PICMET.2007.4349612 Lin, J.: A web forensic system based on semantic checking. In: 2008 International Symposium on Computational Intelligence and Design, October 2008, vol. 1, pp. 99–102 (2008) Liu, H., Liu, J.: Female employment data analysis based on decision tree algorithm and association rule analysis method. Sci. Program. (2022). https://doi.org/10.1155/2022/8994349 Han, J., Kamber, M.: In: J. Gray (Series Editor) Data Mining: Concepts and Techniques, The Morgan Kaufmann Series in Data Management Systems, p. 5. Morgan Kaufmann Publishers (2000). Accessed 10 April 2020 Maimon, O., Rokach, L.: Data Mining and Knowledge Discovery Handbook, p. 165. Springer, New York (2005) Hoenigsberger, F., Saranti, A., Angerschmid, A., Retzlaff, C.O., Gollob, C., Witzmann, S., et al.: Machine learning and knowledge extraction to support work safety for smart forest operations. In: International Cross-Domain Conference for Machine Learning and Knowledge Extraction, 2022, pp. 362–375. Springer, Cham (2022) Gholizadeh, P., Onuchukwu, I.S., Esmaeili, B.: Trends in catastrophic occupational incidents among electrical contractors, 2007–2013. Int. J. Environ. Res. Public Health 18(10), 5126 (2021). https://doi.org/10.3390/ijerph18105126 Kahraman, M.M.: Analysis of mining lost time incident duration influencing factors through machine learning. Min. Metall. Explor. 38(2), 1031–1039 (2021). https://doi.org/10.1007/s42461-021-00396-w Lee, J.Y., Yoon, Y.G., Oh, T.K., Park, S., Ryu, S.I.: A study on data pre-processing and accident prediction modelling for occupational accident analysis in the construction industry. Appl. Sci. 10(21), 7949 (2020). https://doi.org/10.3390/app10217949 Sanmiquel, L., Rossell, J.M., Vintró, C.: Study of Spanish mining accidents using data mining techniques. Saf. Sci. 75, 49–55 (2015). https://doi.org/10.1016/j.ssci.2015.01.016 Mistikoglu, G., Gerek, I.H., Erdis, E., Usmen, P.M., Cakan, H., Kazan, E.E.: Decision tree analysis of construction fall accidents involving roofers. Expert Syst. Appl. 42(4), 2256–2263 (2015). https://doi.org/10.1016/j.eswa.2014.10.009 Nenonen, N.: Analysing factors related to slipping, stumbling, and falling accidents at work: application of data mining methods to Finnish occupational accidents and diseases statistics database. Appl. Ergon. 44(2), 215–224 (2013). https://doi.org/10.1016/j.apergo.2012.07.001 Xiao, D., Xu, X., Kang, S.: Paving the way for evaluation of connected and autonomous vehicles in buses—preliminary analysis. IEEE Access 8, 6162–6167 (2020). https://doi.org/10.1109/ACCESS.2019.2963457 Zhao, D., McCoy, A.P., Kleiner, B.M., Du, J., Smith-Jackson, T.L.: Decision-making chains in electrical safety for construction workers. J. Constr. Eng. Manag. 142(1), 04015055 (2016) Rengarasu, T.M., Hagiwara, T., Hirasawa, M.: Effects of road geometry and cross-section variables on traffic accidents: study using homogeneous road segments. Transp. Res. Rec. 2102(1), 34–42 (2009). https://doi.org/10.3141/2102-05 Jiang, Y., Zhang, J., Fujiwara, A., Tomitaka, H., Matsushita, T.: Effects of dynamic travel information on drivers' heterogeneous adaptation behavior to traffic accidents on expressways. In: 20th ITS World Congress, ITS Japan, 2013 (2013) Bevilacqua, M., Ciarapica, F.E., Giacchetta, G.: Data mining for occupational injury risk: a case study. Int. J. Reliab. Qual. Saf. Eng. 17(04), 351–380 (2010). https://doi.org/10.1142/S021853931000386X Jha, A.N., Chatterjee, N., Tiwari, G.: A performance analysis of prediction techniques for impacting vehicles in hit-and-run road accidents. Accid. Anal. Prev. 157, 106164 (2021). https://doi.org/10.1016/j.aap.2021.106164 Yaman, T.T., Bilgiç, E., Esen, M.F.: Analysis of traffic accidents to identify factors affecting injury severity with fuzzy and crisp techniques. In: International Conference on Intelligent and Fuzzy Systems, July 2020, pp. 625–633. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-51156-2_72 Sarkar, S., Pramanik, A., Maiti, J., Reniers, G.: Predicting and analyzing injury severity: a machine learning-based approach using class-imbalanced proactive and reactive data. Saf. Sci. 125, 104616 (2020). https://doi.org/10.1016/j.ssci.2020.104616 Huang, C.S., Lin, Y.J., Lin, C.C.: Implementation of classifiers for choosing insurance policy using decision trees: a case study. WSEAS Trans. Comput. 7(10), 1679–1689 (2008) Bramer, M.: Avoiding overfitting of decision trees. In: Principles of Data Mining, pp. 119–134. Springer, London (2007) Kerdprasop, N., Kerdprasop, K.: Discrete decision tree induction to avoid overfitting on categorical data. In: Proceedings of the Mamectis/Nolasc/Control/Wamus, 2011, p. 11 (2011) Lee, D.H., Yang, J.K., Lee, C.H., Kim, K.J.: A data-driven approach to selection of critical process steps in the semiconductor manufacturing process considering missing and imbalanced data. J. Manuf. Syst. 52, 146–156 (2019). https://doi.org/10.1016/j.jmsy.2019.07.001 Zhang, H., Zhou, J., Jahed Armaghani, D., Tahir, M.M., Pham, B.T., Huynh, V.V.: A combination of feature selection and random forest techniques to solve a problem related to blast-induced ground vibration. Appl. Sci. 10(3), 869 (2020). https://doi.org/10.3390/app10030869 Uyanık, S., Oğulata, R.T.: The current situation and development of textile industry and apparel industry in Turkey. J. Text. Eng. 20(92), 59–78 (2013). https://doi.org/10.7216/130075992013209206 Azam, M., Arshad, A., Aslam, M., Gulzar, S.: Application of classification methods to analyze chemicals in drinking water quality. Accredit. Qual. Assur. 24(3), 227–235 (2019). https://doi.org/10.1007/s00769-018-01369-1 Bansode, S.S., Hiremath, R.B.: A study of problems faced by textile industry in India. Psychol. Educ. J. 57(9), 7292–7297 (2020) Popov, G., Lyon, B.K., Hollcroft, B.: Risk Assessment: A Practical Guide to Assessing Operational Risks. Wiley, Hoboken (2016) Robson, L.S., Stephenson, C.M., Schulte, P.A., Amick, B.C., III., Irvin, E.L., Eggerth, D.E., et al.: A systematic review of the effectiveness of occupational health and safety training. Scand. J. Work Environ. Health 38(3), 193–208 (2012). https://doi.org/10.5271/sjweh.3259 Gao, Y., Gonzalez, V.A., Yiu, T.W.: The effectiveness of traditional tools and computer-aided technologies for health and safety training in the construction sector: a systematic review. Comput. Educ. 138, 101–115 (2019). https://doi.org/10.1016/j.compedu.2019.05.003 Meng, X., Zhai, H., Chan, A.H.: Development of scales to measure and analyse the relationship of safety consciousness and safety citizenship behaviour of construction workers: an empirical study in China. Int. J. Environ. Res. Public Health 16(8), 1411 (2019). https://doi.org/10.3390/ijerph16081411 Karaguven, U.H.M.: The relationship between work accident, educational backgrounds and stress levels of textile workers. In: Paper presented at the European Conference on Educational Research, Lahti, Finland, 22–25 September 1999 (1999) Sousa, V., Almeida, N.M., Dias, L.A.: Risk-based management of occupational safety and health in the construction industry—Part 1: background knowledge. Saf. Sci. 66, 75–86 (2014). https://doi.org/10.1016/j.ssci.2014.02.008 Salminen, S.: Occupational safety in Finland. Curr. Polit. Econ. Eur. 26(2), 197–211 (2015) OHSTE: The Regulation on the Principles and Procedures of the Occupational Health and Safety Training for Employees. OHSTE (2013) https://www.mevzuat.gov.tr/mevzuat?MevzuatNo=18371&MevzuatTur=7&MevzuatTertip=5. Accessed 11 April 2020 PPEW: Regulation on the Use Personal Protective Equipment in the Workplace. PPEW (2013). https://www.mevzuat.gov.tr/mevzuat?MevzuatNo=18540&MevzuatTur=7&MevzuatTertip=5. Accessed 14 April 2020 Erden, S., Ertekin, M.: Mechanical evaluation of a composite overshoe protector. Text. Appar. 27(4), 414–420 (2017) Ertekin, M.: Investigation of dexterity, mechanical properties, and burning behavior of protective gloves produced with high performance yarns. Text. Appar. 27(4), 400–407 (2017) Hanvold, T.N., Kines, P., Nykänen, M., Thomée, S., Holte, K.A., Vuori, J., et al.: Occupational safety and health among young workers in the Nordic countries: a systematic literature review. Saf. Health Work 10(1), 3–20 (2019). https://doi.org/10.1016/j.shaw.2018.12.003 HSRWE: The Regulation of Health and Safety Requirements for Use of Work Equipments. Offıcial Gazette No. 28628. HSRWE (2013). https://www.mevzuat.gov.tr/Metin.Aspx?MevzuatKod=7.5.18318&MevzuatIliski=0. Accessed 8 April 2020 ISO 12100: ISO (2010). https://www.iso.org/standard/51528.html. Accessed 8 April 2020 FLSPT: Analysis of Female Labor Statistics Profile in Turkey. FLSPT (2014). ailevecalisma.gov.tr/uploads/ksgm/uploads/pages/dagitimda-olan-yayinlar/turkiye-de-kadin-isgucu-profili-ve-istatistiklerinin-analizi-nihai-rapor.pdf. Accessed 12 April 2020