ANALISIS PENGENDALIAN KUALITAS STATISTIK GULA RAFINASI DENGAN PETA KENDALI MULTIVARIAT T-SQUARE (STUDI KASUS: PT. MAKASSAR TENE)

  • Irwan Kasse Universitas Islam Negeri Alauddin Makassar
  • Efita Erianti
  • Muh. Irwan UIN Alauddin Makassar
    (ID)

Abstract

Sugar is a simple carbohydrate that is a source of energy. Sugar consumption in each country are different from Indonesia. Demand for sugar in Indonesia is always changing and increasing along with increasing of the population in Indonesia. If sugar consumption in Indonesia is Increasing, Sugar Production have to be increased. Of course, the company have to guarantee the quality of sugar. There are several factors that affect the quality of sugar. So, the company must always check the quality of sugar to be producted by considering these factors. Therefore, this research used multivariate T2 control chart method. This study aims to determine whether refined sugar products have been statistically controlled using multivariate T-Square control chart. The method used is the Statistical Quality Control method with multivariate T-Square control chart. The results of the study show that all refined sugar products have been statistically controlled by using multivariate T-Square control chart after making several revisions and can be a reference in the analysis control chart.

References

Sugiyanto, C. (2007). Permintaan gula di Indonesia

Direktorat Jenderal Perdagangan Luar Negeri. 2007. Kebijakan Umum di Bidang Impor. Jakarta: Departemen Perdagangan

Gunderson, Michael A. & Johnson, Aaron J. & Salassi, Michael E. & Champagne, Lonnie P. & DeVuyst, Cheryl Sinn, 2009. "Determining the Future for Louisiana Sugar Cane Products, Inc.: A Case Study Analyzing Vertical Coordination Options," Journal of Cooperatives, NCERA-210, vol. 22, pages 1-22

Montgomery, D. C. (2009). Introduction to Statistical Quality Control, Sixth Edition. John Wiley & Sons, Inc. (Vol. 91, pp. 1689–1699). John Wiley and Sons Ltd.

Abtew, M. A., Kropi, S., Hong, Y., & Pu, L. (2018). Implementation of Statistical Process Control (SPC) in the Sewing Section of Garment Industry for Quality Improvement. Autex Research Journal, 18(2), 160–172. https://doi.org/10.1515/aut-2017-0034

Pan. X., Jarrett. J., E. 2005. Vector Autoregression and Monitoring Multivariate Autocorrelated Processes. Journal of Encouraging Creative Research, College of Business Administration University of Rhode Island.

Omekara, C. O., & Kelechi, A. C. Multivariate Analysis of the Performance of Students using Hotelling T 2 Statistic

Baweja, R. (1987). The theory and practlce of industrial pharmacy, Edited by Leon Lachman, Herbert A. Lieberman and Joseph L. Kanig. Lea and Febiger, Philadelphia, PA 19106. 1986. 902 pp. 19× 27 cm. $85.00

Psarakis, S., & Papaleonida, G. E. A. (2007). SPC procedures for monitoring autocorrelated processes. Quality Technology & Quantitative Management, 4(4), 501-540

Sholiha, L., & Syaichu, A. (2015). Analisa Pengendalian Kualitas Produksi Gula Kristal Putih Dengan Metode Seventools. Jurnal Ilmu-ilmu Teknik-Sistem, 13(1)

Goonatilake, R., Bachnak, R., & Herath, S. (2011). Statistical Quality Control Approaches to Network Intrusion Detection. International Journal of Network Security & Its Applications, 3(6), 115–124. https://doi.org/10.5121/ijnsa.2011.3608

Vukelić, Đ., Hodolič, J., Vrečič, T., & Kogej, P. (2008). Development of a system for statistical quality control of the production process. Facta universitatis-series: Mechanical Engineering, 6(1), 75-90.

Okorie, C. E., Adubisi, O., & Ben, O. J. (2017). Statistical Quality Control of, the Production Materials in Line Leag, er Beer

McClave, B. (2010). Sincich. Statistik untuk Bisnis dan Ekonomi.

Breyfogle III, F. W. (2003). Implementing six sigma: smarter solutions using statistical methods. John Wiley & Sons

Woodall, W. H., Spitzner, D. J., Montgomery, D. C., & Gupta, S. (2004). Using control charts to monitor process and product quality profiles. Journal of Quality Technology, 36(3), 309–320. https://doi.org/10.1080/00224065.2004.11980276

Nastiti, H. (2014). Analisis Pengendalian Kualitas Produk dengan Metode Statistical Quality Control. Jurnal Manajemen. Jakarta: Universitas Pembangunan Negeri “Veteran.

Shah, S., Shridhar, P., & Gohil, D. (2010, July). Control chart : A statistical process control tool in pharmacy. Asian Journal of Pharmaceutics. https://doi.org/10.4103/0973-8398.72116

Wahyuningsih, N., & Pusdikarta, D. (2005). Analisis Pengendalian Kualitas Multivariate Air Minum (Studi Kasus di PDAM Gresik). Limits: Journal of Mathematics and Its Applications, 2(1), 47

Mostajeran, A., Iranpanah, N., & Noorossana, R. (2016). A new bootstrap based algorithm for Hotelling’s T2 multivariate control chart. Journal of Sciences, Islamic Republic of Iran, 27(3), 269-278.

Liu, R. Y., & Tang, J. (1996). Control Charts for Dependent and Independent Measurements Based on Bootstrap Methods. Journal of the American Statistical Association, 91(436), 1694–1700. https://doi.org/10.1080/01621459.1996.10476740

Irwan, I., & Haryono, D. (2015). Pengendalian Kualitas Statistik (Pendekatan Teoritis dan Aplikatif). Bandung: Alfabeta

Published
2021-06-29
How to Cite
Kasse, I., Erianti, E., & Irwan, M. (2021). ANALISIS PENGENDALIAN KUALITAS STATISTIK GULA RAFINASI DENGAN PETA KENDALI MULTIVARIAT T-SQUARE (STUDI KASUS: PT. MAKASSAR TENE). Jurnal MSA ( Matematika Dan Statistika Serta Aplikasinya ), 8(1). https://doi.org/10.24252/msa.v8i1.19364
Abstract viewed = 100 times