Uji Kenormalan Berdasarkan Verma Kullback - Liebler dan Penerapannya pada Berat Tanaman Pakcoy Hidroponik
Abstract
Abstract. In solving problems, statistics are divided into 2, namely descriptive statistics and inference. Inferential statistics are generally based on certain distribution assumptions to get conclusions. One of the assumptions that must be met is the normal distribution. Bitaraf. et al (2017) have proposed a new method for the normal distribution suitability test, namely the Verma Kullback-Liebler Test. This test is based on the concept of entropy (Verma Entrophy) and relative entropy (Kullback-liebler Divergence). The material that will be used to apply the method that will be discussed in this skripsi is the weight data of the khazanahturahman hydroponic plant. Samples were taken as many as 20 plants from a total population of 168 plants. Based on the kullback-liebler verma test, it was concluded that the weight sample data of the Khazanahturahman hydroponic pakcoy plant were normally distributed.
Keywords: Alignment test, data normality, kullback-leibler verma test, entropy, hydroponic pakcoy, Khazanahturahman
Abstrak. Dalam peneyelesaian masalah statistika terbagi menjadi 2 yaitu statistika deskriptif dan inferensiStatistika inferensial pada umumnya didasarkan pada asumsi distribusi tertentu untuk mendapatkan kesimpulan. Salah satu asumsi yang harus dipenuhi adalah Distribusi normal. Bitaraf. et al (2017) telah mengusulkan metode baru untuk uji kesesuaian distribusi normal yaitu Uji Verma Kullback-Liebler. Uji ini didasarkan pada konsep entropi (Verma Entrophy) dan relatif entropi (Kullback-liebler Divergence). Bahan yang akan digunakan untuk mengaplikasikan metode yang akan dibahas dalam skripsi ini adalah data berat tanaman pakcoy hidroponik khazanahturahman. Sampel diambil sebanyak 20 tanaman dari jumlah populasi sebanyak 168 tanaman. Berdasarkan uji verma kullback-liebler diperoleh kesimpulan, data sampel berat tanaman pakcoy hidroponik khazanahturahman berdistribusi normal.
Kata Kunci: Uji keselarasan, kernormalan data , uji verma kullback-liebler,entropi, pakcoy hidroponik, Khazanahturahman
24207ÂKeywords
References
Alizadeh, H. (2010). A “new estimator of entropy and its application in testing normalityâ€. Journal of Statistical Computation and Simulation.
Alizadeh H, Arghami N. R. 2012. “ Goodness-of-Fit Tests Based on Correcting Moments of Entropyâ€. Communications in Statistics - Simulation and Computation.
Bitaraf, M. Rezaei, M. Yousefzadeh, F.( 2017). “Goodness Of Fit Tests Based On Verma Kullbackliebler Informationâ€. Department Of Engineering, Maybod Branch, Islamic Azad University Maybod, Iran.
Ebrahimi, N. Pughoeft, K. Soofi, E.( 1994).†Two measures of sample entropy. Statistics and Probability Letters.
Kumar ,V. Taneja, H.(2011) “Some characterization results on generalized cumulative residual entropy measureâ€. Statistics and Probability Letters
Kusdian, R, Didin. Tamin, Ofyar, Z. Ridwan, Agus, Salim. Syafrudin, Ade. (2005).“Penggunaan Distribusi Normal Dalam Memodelkan Sebaran Persepsi Biaya Perjalanan Dan Transformasi Box-Muller Pada Pengambilan Sampel Acak Model Pemilihan Rute Dan Pembebanan Stokastikâ€. Institut Teknologi Bandung. Indonesia
Park ,S. Park, D.(2003) “Correcting moments for goodness-of-fit tests based on two entropy estimatesâ€. Journal of Statistical Computation and Simulation. 2003;73:685-694.
Sudjana, (1989).Metoda Statistika, Tarsito, Bandung,
Suyanto, (2006), “Uji Goodness Of Fit Distribusi Eksponensial Tergenalisir Dengan Metode Anderson Darlingâ€. Skripsi. Fakultas Matematika Dan Ilmu Pengetahuan Alam Universitas Airlangga. Indonesia.
Shannon, Claude. (1948). "A Mathematical Theory of Communication". Bell System Technical Journal.
Renyi A (1961). “On measure of entropy and information.†In: Proceedings of the 4th Berkeley Symposium on Mathematical Statistics and Probability.
Vasicek, O.(1976). “A test for normality based on sample entropyâ€. Journal of the Royal StatisticalSociety.
DOI: http://dx.doi.org/10.29313/.v6i2.24353
   Â