Peramalan Metode Winter’s untuk XC7

Tabel 5.9. Perhitungan Kesalahan Metode Winter’s untuk XC7 T Xt Ft Xt-Ft Xt-Ft 2 [Pet] 1 65488900 67847295.39 -2358395.39 5.56203E+12 3.601214 2 77963000 103270167.2 -25307167.2 6.40453E+14 32.46048 3 84200000 88807974.05 -4607974.05 2.12334E+13 5.472653 4 72765000 66979958.61 5785041.39 3.34667E+13 7.950308 5 43659300 41591086.78 2068213.22 4.27751E+12 4.737165 6 51973400 45129388.43 6844011.57 4.68405E+13 13.1683 7 75884000 98593960.33 -22709960.3 5.15742E+14 29.92721 8 62370400 49335527.8 13034872.2 1.69908E+14 20.89913 9 83160600 93467618.97 -10307019 1.06235E+14 12.39411 10 107277100 54252629.84 53024470.16 2.81159E+15 49.42758 11 85239600 100275434.6 -15035834.6 2.26076E+14 17.63949 66 809981300 809551042 430258 4.58139E+15 197.6776 SEE : 13816337.64 MAPE : 17.97069 f n Ft Xt SEE − − = ∑ 2 24 809551042 809981300 2 − = = 13816337.64 N PE MAPE N t t ∑ = Ι Ι = 1 = 24 197.6776 = 17.97069 5.2.2.1. Peramalan Metode Dekomposisi untuk XC7 Perhitungan peramalan untuk jenis obat XC7 menggunakan metode Dekomposisi dapat dilihat pada Tabel 5.10. Tabel 5.10. Peramalan dengan Metode Dekomposisi untuk XC7 Bulan Xt Periode Moving Average MA Center Moving Average CMA indeks musiman Deseasonalized Data Tren F Jun-09 56133300 1 0.75 74511665.4 58108281.82 43775824.9 Jul-09 62370400 2 1.05 59383708.6 58896811.43 61859014.42 Aug-09 93555750 3 1.24 75509646.1 59696041.39 73962840.71 Sep-09 83160500 4 1.31 63311325.7 60506116.9 79475810.68 Oct-09 62371000 5 1.08 57515172.1 61327185.14 66504849.44 Nov-09 37423300 6 0.62 60493382.2 62159395.28 38453953.37 Dec-09 39502300 7 61920179.17 61530366.67 0.64 61530366.7 63002898.51 40447660.77 Jan-10 82121000 8 61140554.17 61270491.67

1.34 61270491.7 63857848.09 85588840.57

Feb-10 42411900 9 61400429.17 60750731.25 0.7 60750731.3 64724399.33 45186036.37 Mar-10 74844500 10 60101033.33 60144345.83 1.24 60144345.8 65602709.68 81636967.48 Apr-10 43659300 11 60187658.33 60620741.67

0.72 60620741.7

66492938.7 47888479.73 May-10 65488900 12 61053825 61313658.33

1.07 61313658.3 67395248.14

71984624.4 Jun-10 46777800 13 61573491.67 62093120.83 0.75 62093120.8 68309801.92 51461131.43 Jul-10 65488900 14 62612750 62352875 1.05 62352875 69236766.19 72719015.08 Aug-10 77963000 15 62093000 62924604.17 1.24 62924604.2 70176309.38 86947795.39 Sep-10 84200000 16 63756208.33 64102712.5 1.31 64102712.5 71128602.17 93428625.24 Oct-10 72765000 17 64449216.67 67099958.33 1.08 67099958.3 72093817.57 78180475.31 Nov-10 43659300 18 69750700 70573645.83 0.62 70573645.8 73072130.96 45204949.38 Dec-10 51973400 19 71396591.67 0.64 80955852.2 74063720.06 47548673.08 Jan-11 75884000 20

1.34 56617064.9 75068765.02 100614861.8