C4.5 Classification Data Mining for Inventory Control

  • Authors

    • Robbi Rahim
    • Ilka Zufria
    • Nuning Kurniasih
    • Muhammad Yasin Simargolang
    • Abdurrozzaq Hasibuan
    • Dian Utami Sutiksno
    • Ricardo Freedom Nanuru
    • Jusuf Nikolas Anamofa
    • Ansari Saleh Ahmar
    • Achmad Daengs GS
    2018-03-08
    https://doi.org/10.14419/ijet.v7i2.3.12618
  • Classification, C4.5 Algorithm, Data Mining

  • Abstract

    Data Mining is a process of exploring against large data to find patterns in decision making. One of the techniques in decision-making is classification. Classification is a technique in data mining by applying decision tree method to form data, algorithm C4.5 is algorithm that can be used to classify data in tree form. The system has been built that shows the results of good performance and minimal error in view of the system that is able to distinguish the anomaly traffic with normal traffic. Data mining inventory system applications can facilitate the control of inventory in the company to reduce production costs.

     

  • References

    1. [1] D. Siregar, D. Arisandi, A. Usman, D. Irwan, and R. Rahim, “Research of Simple Multi-Attribute Rating Technique for Decision Support,†J. Phys. Conf. Ser., vol. 930, no. 1, p. 012015, Dec. 2017.

      [2] E. Buulolo, N. Silalahi, Fadlina, and R. Rahim, “C4.5 Algorithm To Predict the Impact of the Earthquake,†Int. J. Eng. Res. Technol., vol. 6, no. 2, pp. 10–15, 2017.

      [3] J. Suyono, A. Sukoco, M. I. Setiawan, S. Suhermin, and R. Rahim, “Impact of GDP Information Technology in Developing of Regional Central Business (Case 50 Airports IT City Development in Indonesia),†in Journal of Physics: Conference Series, 2017, vol. 930, no. 1.

      [4] Ep. E.P. and S. R, “Big data management with machine learning inscribed by domain knowledge for health care,†Int. J. Eng. Technol., vol. 6, no. 4, p. 98, Sep. 2017.

      [5] G. Nivedhitha and N. Rupavathy, “Data mining in personalized service of digital library,†vol. 7, no. 1.7, pp. 51–53, 2018.

      [6] A. S. Ahmar, “A Comparison of α-Sutte Indicator and ARIMA Methods in Renewable Energy Forecasting in Indonesia,†Int. J. Eng. Technol., vol. 7, no. 1.6, pp. 9–11, 2018.

      [7] A. S. Ahmar et al., “Modeling Data Containing Outliers using ARIMA Additive Outlier (ARIMA-AO),†J. Phys. Conf. Ser., vol. 954, no. 1, 2018.

      [8] A. S. Ahmar, A. Rahman, A. N. M. Arifin, and A. A. Ahmar, “Predicting movement of stock of ‘Y’ using sutte indicator,†Cogent Econ. Financ., vol. 5, no. 1, 2017.

      [9] A. Rahman and A. S. Ahmar, “Forecasting of primary energy consumption data in the United States: A comparison between ARIMA and Holter-Winters models,†in AIP Conference Proceedings, 2017, vol. 1885.

      [10] P. He, L. Chen, and X. H. Xu, “Fast C4.5,†in Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007, 2007, vol. 5, pp. 2841–2846.

      [11] B. HSSINA, A. MERBOUHA, H. EZZIKOURI, and M. ERRITALI, “A comparative study of decision tree ID3 and C4.5,†Int. J. Adv. Comput. Sci. Appl., vol. 4, no. 2, 2014.

      [12] S. Sharma and S. Bhatia, “A study of frequent itemset mining techniques,†Int. J. Eng. Technol., vol. 6, no. 4, p. 141, Oct. 2017.

      [13] R. Rahim, Nurjamiyah, and A. R. Dewi, “Data Collision Prevention with Overflow Hashing Technique in Closed Hash Searching Process,†J. Phys. Conf. Ser., vol. 930, no. 1, p. 012012, Dec. 2017.

      [14] P. harliana and R. Rahim, “Comparative Analysis of Membership Function on Mamdani Fuzzy Inference System for Decision Making,†J. Phys. Conf. Ser., vol. 930, no. 1, p. 012029, Dec. 2017.

      [15] R. Rahim, I. Zulkarnain, and H. Jaya, “Double hashing technique in closed hashing search process,†IOP Conf. Ser. Mater. Sci. Eng., vol. 237, no. 1, p. 012027, Sep. 2017.

      [16] R. Rahim, I. Zulkarnain, and H. Jaya, “A review: search visualization with Knuth Morris Pratt algorithm,†in IOP Conference Series: Materials Science and Engineering, 2017, vol. 237, no. 1, p. 012026.

      [17] B. Singh and H. K. Singh, “Web Data Mining Research : a Survey,†Computer (Long. Beach. Calif)., vol. 2, no. 1, pp. 1–10, 2010.

      [18] Y. U. Zheng, “Trajectory Data Mining : An Overview,†ACM Trans. Intell. Syst. Technol., vol. 6, no. 3, pp. 1–41, 2015.

      [19] M. J. C. M. Belinda, R. Umamaheswari, and S. A. David, “Study of high yielding crops cultivation in India using data mining techniques,†vol. 7, no. 1.7, pp. 121–124, 2018.

      [20] J. H. Ku and Y. S. Jeong, “A study on social big data analysis using text clustering,†vol. 7, no. 2, pp. 1–4, 2018.

      [21] K. Madadipouya, “A Survey on Data Mining Algorithms and Techniques in Medicine,†JOIV Int. J. Informatics Vis., vol. 1, no. 3, pp. 61–71, 2017.

      [22] Y. Mardi, “Klasifikasi Menggunakan Algoritma C4.5,†J. Edik Inform., vol. 2, no. 2, pp. 213–219, 2017.

      [23] A. P. Muniyandi, R. Rajeswari, and R. Rajaram, “Network anomaly detection by cascading k-Means clustering and C4.5 decision tree algorithm,†in Procedia Engineering, 2012, vol. 30, pp. 174–182.

      [24] K. Sreenivasa Rao, N. Swapna, and P. Praveen Kumar, “Educational data mining for student placement prediction using machine learning algorithms,†vol. 7, no. 1.2, pp. 43–46, 2018.

  • Downloads

  • How to Cite

    Rahim, R., Zufria, I., Kurniasih, N., Yasin Simargolang, M., Hasibuan, A., Utami Sutiksno, D., Freedom Nanuru, R., Nikolas Anamofa, J., Saleh Ahmar, A., & Daengs GS, A. (2018). C4.5 Classification Data Mining for Inventory Control. International Journal of Engineering & Technology, 7(2.3), 68-72. https://doi.org/10.14419/ijet.v7i2.3.12618

    Received date: 2018-05-09

    Accepted date: 2018-05-09

    Published date: 2018-03-08