Algoritma dan Pemrograman : Implementasi Metode Fitting (Regresi Linear Sederhana)

Berikut ini adalah flowchart dari metode fitting :


Implementasi dengan pemrograman java : 
/**
 *
 * @author ABD. CHARIS FAUZAN
 */
public class FittingRegresi {
        double matrik[][] = {
        {3.5, 1000000,4, 80,90},
        {3, 500000,3, 70,65},
        {2.7, 500000,1, 70,65},
        {3.4, 600000,2, 80,90},
        {3.2, 700000,1, 75,85},
        {3.1, 800000,2, 80,75},
        {3, 450000,3, 75,75},
        {3.3, 750000,4, 80,80},
        {2.9, 600000,2, 75,85},
        {3.7, 1000000,4, 85,90}
    };
    int row = matrik.length;
    int col = matrik[0].length;
    double Y[] = new double[row];
    double uangSaku[] = new double[row];
    double lamaBelajar[] = new double[row];
    double fasilitas[] = new double[row];
    double caraNgajar[] = new double[row];

    private void init() {
        double X[][] = new double[row][col];
        double XTrans[][] = new double[col][row];
        for (int i = 0; i < row; i++) {
            X[i][0] = 1;
            Y[i] = matrik[i][0];
            lamaBelajar[i] = matrik[i][1];
            uangSaku[i] = matrik[i][2];
            fasilitas[i] = matrik[i][3];
            caraNgajar[i] = matrik[i][4];
            
            for (int j = 1; j < col; j++) {
                Y[i] = matrik[i][0];
            }
            
            for (int j = 1; j < col; j++) {
                X[i][j] = matrik[i][j];
            }
        }
        printMatrix(Y, "Matriks Y :");
        printMatrix(X, "Matriks X :");
        XTrans = Transpose(X);
        printMatrix(XTrans, "X Transpose :");

        double XTrans_mul_X[][] = MMULT(XTrans, X);
        printMatrix(XTrans_mul_X, "X'X :");
        double InversXTrans_mul_X[][] = invers(XTrans_mul_X);
        printMatrix(InversXTrans_mul_X,"[X'X]-1 :");
        double XTransMY[] = MMULT(XTrans, Y);
        printMatrix(XTransMY,"(X'Y) :");

        double BMult[] = MMULT(InversXTrans_mul_X, XTransMY);
        printMatrix(BMult,"B^=[X'X]-1 X'Y :");
        
        double IPK[] = new double[Y.length];
        double E[]=new double[Y.length];

        for (int i = 0; i < IPK.length; i++) {
            IPK[i] = BMult[0] + (BMult[1] * lamaBelajar[i]) + (BMult[2] * uangSaku[i]) + (BMult[3] * fasilitas[i]) + (BMult[4] * caraNgajar[i]);
            E[i]=Y[i]-IPK[i];
        }
        printMatrix(IPK,"Y^ :");
        printMatrix(E, "E=Y-Y^ :");
    }

    private void printMatrix(double[][] A, String Title) {
        System.out.println(Title );
        for (int i = 0; i < A.length; i++) {
            for (int j = 0; j < A[0].length; j++) {
                System.out.print(A[i][j] + ", ");
            }
            System.out.println("");
        }
        System.out.println("");
    }

    private void printMatrix(double[] A, String Title) {
        System.out.println(Title );
        for (int i = 0; i < A.length; i++) {
            System.out.println(A[i]);
        }
        System.out.println("");
    }

    double[][] Transpose(double A[][]) {
        int row = A.length;
        int col = A[0].length;
        double ATrans[][] = new double[col][row];
        for (int i = 0; i < row; i++) {
            for (int j = 0; j < col; j++) {
                ATrans[j][i] = A[i][j];
            }
        }
        return ATrans;
    }

    private double[][] MMULT(double A[][], double x[][]) {
        int m, n, p;
        m = A.length;
        n = A[0].length;
        p = x[0].length;
        double[][] result = new double[m][p];

        for (int i = 0; i < m; i++) {
            for (int j = 0; j < p; j++) {
                result[i][j] = 0;
                for (int k = 0; k < n; k++) {
                    result[i][j] += A[i][k] * x[k][j];
                }
            }
        }
        return result;
    }

    private double[] MMULT(double A[][], double x[]) {
        int m = A.length;
        double[] result = new double[m];

        for (int i = 0; i < m; i++) {
            result[i] = 0;
            for (int k = 0; k < x.length; k++) {
                result[i] += A[i][k] * x[k];
            }
        }
        return result;
    }

    private double[][] invers(double[][] A) {
        int n = A.length;
        double I[][] = {
            {1, 0, 0, 0, 0},
            {0, 1, 0, 0, 0},
            {0, 0, 1, 0, 0},
            {0, 0, 0, 1, 0},
            {0, 0, 0, 0, 1}
        };
        for (int row = 0; row < n; row++) {
            double tampung = A[row][row];
            for (int col = 0; col < n; col++) {
                A[row][col] /= tampung;
                I[row][col] /= tampung;
            }

            for (int i = 0; i < n; i++) {
                if (i != row) {
                    double m = A[i][row];
                    for (int col = 0; col < n; col++) {
                        A[i][col] -= m * A[row][col];
                        I[i][col] -= m * I[row][col];
                    }

                }
            }
        }
        return I;
    }

    public static void main(String[] args) {
        FittingRegresi Reg = new FittingRegresi();
        Reg.init();
    }
}
Tampilan ketika dijalankan :

lanjutan
lanjutan 


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