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Gauss Method.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Enter the number of unknowns: 4\n",
+      "Masukkan augmented matrix coefficients: \n",
+      "matrix[0][0] = 1\n",
+      "matrix[0][1] = -1\n",
+      "matrix[0][2] = 1\n",
+      "matrix[0][3] = -2\n",
+      "matrix[0][4] = 8\n",
+      "matrix[1][0] = 2\n",
+      "matrix[1][1] = -1\n",
+      "matrix[1][2] = 2\n",
+      "matrix[1][3] = -1\n",
+      "matrix[1][4] = 5\n",
+      "matrix[2][0] = -1\n",
+      "matrix[2][1] = 1\n",
+      "matrix[2][2] = 2\n",
+      "matrix[2][3] = -1\n",
+      "matrix[2][4] = 4\n",
+      "matrix[3][0] = 1\n",
+      "matrix[3][1] = 2\n",
+      "matrix[3][2] = 4\n",
+      "matrix[3][3] = 1\n",
+      "matrix[3][4] = 5\n",
+      "\n",
+      "Ketik Y untuk mengetahui hasilnya: Y\n",
+      "\n",
+      "Gauss Elimination\n",
+      "inisiasi matrix:\n",
+      " [[ 1. -1.  1. -2.  8.]\n",
+      " [ 2. -1.  2. -1.  5.]\n",
+      " [-1.  1.  2. -1.  4.]\n",
+      " [ 1.  2.  4.  1.  5.]]\n",
+      "\n",
+      "Transformation 1: \n",
+      "baris2 = row2 - 2.0 * baris1\n",
+      "baris3 = row3 - -1.0 * baris1\n",
+      "baris4 = row4 - 1.0 * baris1\n",
+      "Hasil:\n",
+      " [[  1.  -1.   1.  -2.   8.]\n",
+      " [  0.   1.   0.   3. -11.]\n",
+      " [  0.   0.   3.  -3.  12.]\n",
+      " [  0.   3.   3.   3.  -3.]]\n",
+      "\n",
+      "Transformation 2: \n",
+      "baris3 = row3 - 0.0 * baris2\n",
+      "baris4 = row4 - 3.0 * baris2\n",
+      "Hasil:\n",
+      " [[  1.  -1.   1.  -2.   8.]\n",
+      " [  0.   1.   0.   3. -11.]\n",
+      " [  0.   0.   3.  -3.  12.]\n",
+      " [  0.   0.   3.  -6.  30.]]\n",
+      "\n",
+      "Transformation 3: \n",
+      "baris4 = row4 - 1.0 * baris3\n",
+      "Hasil:\n",
+      " [[  1.  -1.   1.  -2.   8.]\n",
+      " [  0.   1.   0.   3. -11.]\n",
+      " [  0.   0.   3.  -3.  12.]\n",
+      " [  0.   0.   0.  -3.  18.]]\n",
+      "\n",
+      "Solusi: \n",
+      "x1 = 5.00\n",
+      "x2 = 7.00\n",
+      "x3 = -2.00\n",
+      "x4 = -6.00\n"
+     ]
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import sys\n",
+    "\n",
+    "class Gauss:\n",
+    "\n",
+    "    #Inisiasi Matrix\n",
+    "    def start(self):  #self variabel yg mewakili turunan dari objek itu sendiri\n",
+    "        self.n = int(input(\"Enter the number of unknowns: \")) #memasukkan baris\n",
+    "        self.A = np.zeros((self.n,self.n+1)) #pembuatan matriks #np zeros adalah fungsi mengembalikan larik baru dengan bentuk dan tipe tertentu, dengan nol #pembuatan kolom=baris+ 1\n",
+    "        self.R = np.zeros((self.n,self.n+1)) #Matriks perkalian untuk kolom\n",
+    "        self.x = np.zeros(self.n) #Solution array-nya\n",
+    "\n",
+    "        print(\"Masukkan augmented matrix coefficients: \")\n",
+    "        for i in range(self.n): #pengulangan baris\n",
+    "            for j in range(self.n+1): #pengulangan kolom\n",
+    "                self.A[i][j] = input(\"matrix[\"+ str(i) +\"][\"+ str(j) +\"] = \")\n",
+    "    \n",
+    "    #Gauss Elimination\n",
+    "    def gaussProg(self):\n",
+    "        print(f\"\\nGauss Elimination\\ninisiasi matrix:\\n {self.A}\")\n",
+    "        for i in range(self.n-1): #loop kolom\n",
+    "            if self.A[i][i] == 0:\n",
+    "                sys.exit(\"Dibagi dengan 0(proses tidak dilanjutkan...)\") #kondisi system ketika membagi dengan 0\n",
+    "            print(f\"\\nTransformation {i+1}: \")\n",
+    "\n",
+    "            #Menghitung perkalian untuk kolom saat ini\n",
+    "            for j in range(i+1, self.n):\n",
+    "                self.R[j][i] = self.A[j][i] / self.A[i][i]\n",
+    "                print(f\"baris{j+1} = row{j+1} - {self.R[j][i]} * baris{i+1}\")\n",
+    "\n",
+    "            #Terapkan transformasi ke submatrix yang tersisa\n",
+    "            for k in range(self.n+1):\n",
+    "                for j in range(self.n):\n",
+    "                    self.A[j][k] = self.A[j][k] - self.R[j][i] * self.A[i][k]\n",
+    "\n",
+    "            print(f\"Hasil:\\n {self.A}\")\n",
+    "    \n",
+    "    #Substitusi kembali\n",
+    "    def Subs(self):\n",
+    "        self.x[self.n-1] = self.A[self.n-1][self.n] / self.A[self.n-1][self.n-1]\n",
+    "        for i in range(self.n-2,-1,-1):\n",
+    "            self.x[i] = self.A[i][self.n]\n",
+    "            for j in range(i+1, self.n):\n",
+    "                self.x[i] = self.x[i] - self.A[i][j] * self.x[j]\n",
+    "            self.x[i] = self.x[i] / self.A[i][i]\n",
+    "\n",
+    "    #Tampilan/pemecahan\n",
+    "    def display(self):\n",
+    "        print(\"\\nSolusi: \")\n",
+    "        for i in range(self.n):\n",
+    "            print(\"x%d = %0.2f\" %(i+1, self.x[i]))\n",
+    "\n",
+    "g = Gauss() #manggil class\n",
+    "g.start() #mulai jalankan class\n",
+    "choice = input(\"\\nKetik Y untuk mengetahui hasilnya: \")\n",
+    "if choice == 'Y':\n",
+    "    g.gaussProg() #jalankan fungsi gauss\n",
+    "else:\n",
+    "    print(\"Anda menghentikan program\")\n",
+    "    quit()\n",
+    "g.Subs() #jalankan fungsi subtitusi kembali\n",
+    "g.display() #jalankan fungsi tampilan"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
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