KOMPUTASI BIG DATA_ACT_PERT_4.ipynb

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      "source": [
        "#KUMAL_KBD_ACT_PERT 4"
      ],
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      "source": [
        "### Overview Dataset\n",
        "\n",
        "\"Data Komponen Beton\".\n",
        "\n",
        "Data set ini berisikan beberapa kategori sebagai berikut\n",
        "* cement (kg)\n",
        "* slag (blast furnace slag, kg)\n",
        "* ash (fly ash, kg)\n",
        "* water (kg)\n",
        "* superplastic (superplasticizer, kg)\n",
        "* coarseagg (coarse aggregate, kg)\n",
        "* fineagg (fine aggregate, kg)\n",
        "* age (days, 1-365)\n",
        "* strength (Concrete compressive strength, MPa)"
      ],
      "metadata": {
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    {
      "cell_type": "markdown",
      "source": [
        "# Instruksi Tugas Praktikum FIKTI dan FTI\n",
        "\n",
        "1. Buat univariate dan bivariate analysis untuk data set di atas\n",
        "2. Jelaskan kesimpulan yang bisa di ambil dari analysis yg anda lakukan"
      ],
      "metadata": {
        "id": "vQdynqzDeAkl"
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    },
    {
      "cell_type": "markdown",
      "source": [
        "melakukan import file yang di butuhkan dan file praktikum csv\n",
        "\n",
        "1. Buat univariate dan bivariate analysis untuk data set di atas\n",
        "\n",
        "> # 1. Pengambilan Data:\n",
        "\n"
      ],
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        "id": "Z19gsk2dhxJ4"
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      "source": [
        "import pandas as pd \n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data = pd.read_csv('https://raw.githubusercontent.com/supasonicx/ATA-praktIkum-01/main/concrete.csv')"
      ],
      "metadata": {
        "id": "EE_bsecVin-S"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "menampilkan keseluruhan data"
      ],
      "metadata": {
        "id": "dhqyacd_oSak"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data.head()"
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              "   cement   slag    ash  water  superplastic  coarseagg  fineagg  age  \\\n",
              "0   141.3  212.0    0.0  203.5           0.0      971.8    748.5   28   \n",
              "1   168.9   42.2  124.3  158.3          10.8     1080.8    796.2   14   \n",
              "2   250.0    0.0   95.7  187.4           5.5      956.9    861.2   28   \n",
              "3   266.0  114.0    0.0  228.0           0.0      932.0    670.0   28   \n",
              "4   154.8  183.4    0.0  193.3           9.1     1047.4    696.7   28   \n",
              "\n",
              "   strength  \n",
              "0     29.89  \n",
              "1     23.51  \n",
              "2     29.22  \n",
              "3     45.85  \n",
              "4     18.29  "
            ],
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>cement</th>\n",
              "      <th>slag</th>\n",
              "      <th>ash</th>\n",
              "      <th>water</th>\n",
              "      <th>superplastic</th>\n",
              "      <th>coarseagg</th>\n",
              "      <th>fineagg</th>\n",
              "      <th>age</th>\n",
              "      <th>strength</th>\n",
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              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>141.3</td>\n",
              "      <td>212.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>203.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>971.8</td>\n",
              "      <td>748.5</td>\n",
              "      <td>28</td>\n",
              "      <td>29.89</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>168.9</td>\n",
              "      <td>42.2</td>\n",
              "      <td>124.3</td>\n",
              "      <td>158.3</td>\n",
              "      <td>10.8</td>\n",
              "      <td>1080.8</td>\n",
              "      <td>796.2</td>\n",
              "      <td>14</td>\n",
              "      <td>23.51</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>250.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>95.7</td>\n",
              "      <td>187.4</td>\n",
              "      <td>5.5</td>\n",
              "      <td>956.9</td>\n",
              "      <td>861.2</td>\n",
              "      <td>28</td>\n",
              "      <td>29.22</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>266.0</td>\n",
              "      <td>114.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>228.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>932.0</td>\n",
              "      <td>670.0</td>\n",
              "      <td>28</td>\n",
              "      <td>45.85</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>154.8</td>\n",
              "      <td>183.4</td>\n",
              "      <td>0.0</td>\n",
              "      <td>193.3</td>\n",
              "      <td>9.1</td>\n",
              "      <td>1047.4</td>\n",
              "      <td>696.7</td>\n",
              "      <td>28</td>\n",
              "      <td>18.29</td>\n",
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      "source": [
        "menampilkan jumlah kolom pada shape 1 dan 0"
      ],
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        "id": "ZKAZpohqoU6l"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print('jumlah kolom pada data = ', data.shape[1])\n",
        "print('jumlah kolom pada data = ', data.shape[0])"
      ],
      "metadata": {
        "colab": {
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        },
        "id": "MV-nOOK_jMH6",
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      "outputs": [
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          "name": "stdout",
          "text": [
            "jumlah kolom pada data =  9\n",
            "jumlah kolom pada data =  1030\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "menampilkan data describe"
      ],
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      "cell_type": "code",
      "source": [
        "data.describe()"
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            "text/plain": [
              "            cement         slag          ash        water  superplastic  \\\n",
              "count  1030.000000  1030.000000  1030.000000  1030.000000   1030.000000   \n",
              "mean    281.167864    73.895825    54.188350   181.567282      6.204660   \n",
              "std     104.506364    86.279342    63.997004    21.354219      5.973841   \n",
              "min     102.000000     0.000000     0.000000   121.800000      0.000000   \n",
              "25%     192.375000     0.000000     0.000000   164.900000      0.000000   \n",
              "50%     272.900000    22.000000     0.000000   185.000000      6.400000   \n",
              "75%     350.000000   142.950000   118.300000   192.000000     10.200000   \n",
              "max     540.000000   359.400000   200.100000   247.000000     32.200000   \n",
              "\n",
              "         coarseagg      fineagg          age     strength  \n",
              "count  1030.000000  1030.000000  1030.000000  1030.000000  \n",
              "mean    972.918932   773.580485    45.662136    35.817961  \n",
              "std      77.753954    80.175980    63.169912    16.705742  \n",
              "min     801.000000   594.000000     1.000000     2.330000  \n",
              "25%     932.000000   730.950000     7.000000    23.710000  \n",
              "50%     968.000000   779.500000    28.000000    34.445000  \n",
              "75%    1029.400000   824.000000    56.000000    46.135000  \n",
              "max    1145.000000   992.600000   365.000000    82.600000  "
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>cement</th>\n",
              "      <th>slag</th>\n",
              "      <th>ash</th>\n",
              "      <th>water</th>\n",
              "      <th>superplastic</th>\n",
              "      <th>coarseagg</th>\n",
              "      <th>fineagg</th>\n",
              "      <th>age</th>\n",
              "      <th>strength</th>\n",
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              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>1030.000000</td>\n",
              "      <td>1030.000000</td>\n",
              "      <td>1030.000000</td>\n",
              "      <td>1030.000000</td>\n",
              "      <td>1030.000000</td>\n",
              "      <td>1030.000000</td>\n",
              "      <td>1030.000000</td>\n",
              "      <td>1030.000000</td>\n",
              "      <td>1030.000000</td>\n",
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              "      <th>mean</th>\n",
              "      <td>281.167864</td>\n",
              "      <td>73.895825</td>\n",
              "      <td>54.188350</td>\n",
              "      <td>181.567282</td>\n",
              "      <td>6.204660</td>\n",
              "      <td>972.918932</td>\n",
              "      <td>773.580485</td>\n",
              "      <td>45.662136</td>\n",
              "      <td>35.817961</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>104.506364</td>\n",
              "      <td>86.279342</td>\n",
              "      <td>63.997004</td>\n",
              "      <td>21.354219</td>\n",
              "      <td>5.973841</td>\n",
              "      <td>77.753954</td>\n",
              "      <td>80.175980</td>\n",
              "      <td>63.169912</td>\n",
              "      <td>16.705742</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>102.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>121.800000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>801.000000</td>\n",
              "      <td>594.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>2.330000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>192.375000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>164.900000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>932.000000</td>\n",
              "      <td>730.950000</td>\n",
              "      <td>7.000000</td>\n",
              "      <td>23.710000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>272.900000</td>\n",
              "      <td>22.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>185.000000</td>\n",
              "      <td>6.400000</td>\n",
              "      <td>968.000000</td>\n",
              "      <td>779.500000</td>\n",
              "      <td>28.000000</td>\n",
              "      <td>34.445000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>350.000000</td>\n",
              "      <td>142.950000</td>\n",
              "      <td>118.300000</td>\n",
              "      <td>192.000000</td>\n",
              "      <td>10.200000</td>\n",
              "      <td>1029.400000</td>\n",
              "      <td>824.000000</td>\n",
              "      <td>56.000000</td>\n",
              "      <td>46.135000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>540.000000</td>\n",
              "      <td>359.400000</td>\n",
              "      <td>200.100000</td>\n",
              "      <td>247.000000</td>\n",
              "      <td>32.200000</td>\n",
              "      <td>1145.000000</td>\n",
              "      <td>992.600000</td>\n",
              "      <td>365.000000</td>\n",
              "      <td>82.600000</td>\n",
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              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-ca916124-ff81-4be8-9023-0d71aec49ac9 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-ca916124-ff81-4be8-9023-0d71aec49ac9');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "menampilkan info dari data"
      ],
      "metadata": {
        "id": "-j3bp71Nocre"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8m5J9QTHjcKe",
        "outputId": "5f5d93e4-17a3-4167-9a54-b972a21a0449"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 1030 entries, 0 to 1029\n",
            "Data columns (total 9 columns):\n",
            " #   Column        Non-Null Count  Dtype  \n",
            "---  ------        --------------  -----  \n",
            " 0   cement        1030 non-null   float64\n",
            " 1   slag          1030 non-null   float64\n",
            " 2   ash           1030 non-null   float64\n",
            " 3   water         1030 non-null   float64\n",
            " 4   superplastic  1030 non-null   float64\n",
            " 5   coarseagg     1030 non-null   float64\n",
            " 6   fineagg       1030 non-null   float64\n",
            " 7   age           1030 non-null   int64  \n",
            " 8   strength      1030 non-null   float64\n",
            "dtypes: float64(8), int64(1)\n",
            "memory usage: 72.5 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "menampilkan data jumlah"
      ],
      "metadata": {
        "id": "8I25FwufofBu"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7_Smd_PFjgJ6",
        "outputId": "29e6c9fe-31cb-4964-81d1-d49aa7cdd559"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "cement          0\n",
              "slag            0\n",
              "ash             0\n",
              "water           0\n",
              "superplastic    0\n",
              "coarseagg       0\n",
              "fineagg         0\n",
              "age             0\n",
              "strength        0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "menduplicate data dan di jumlah kan ada brp"
      ],
      "metadata": {
        "id": "RWZE2-ifohO2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data.duplicated().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RbsIZpVNjmLp",
        "outputId": "09145378-157b-41b0-da85-ef39afaf72fb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "25"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "mengapus data duplicate"
      ],
      "metadata": {
        "id": "-sHVJM9Kol9L"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data.drop_duplicates(inplace=True)"
      ],
      "metadata": {
        "id": "uOsUmYkcjsyR"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data.duplicated().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Q7uBbqOnj0wd",
        "outputId": "492cc7a0-edea-44f8-c06d-cbc2425770f9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "menampilkan heatmap dari data\n",
        "\n",
        "\n",
        "> # Buat diagram di sini\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "DdY1Ea1AopRr"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.set({'figure.figsize':(8,6)})\n",
        "sns.heatmap(data.corr(),cmap='Reds', annot=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 446
        },
        "id": "uTpPXN9jj7Iw",
        "outputId": "fbe538f6-ebaf-4108-ab88-7600bbc4d063"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd015773c50>"
            ]
          },
          "metadata": {},
          "execution_count": 12
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 576x432 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "menampilkan stastic total semen per kg pada bangunan"
      ],
      "metadata": {
        "id": "J8_2_3GWosG7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.set({'figure.figsize':(10,6)}, rc={'axes.facecolor':'white'} )\n",
        "plt.hist(x=data['cement'], color='skyblue')\n",
        "plt.title('Total Semen (KG) Pada Pembangunan',size=18)\n",
        "plt.xlabel('Semen (KG)', size=14)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 412
        },
        "id": "qYxQwLt8kP7S",
        "outputId": "4516b5bf-d73f-4f32-d6da-be532161b113"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "menampilkan stastic kekuatan bangunan dan total nya dengan format MPa"
      ],
      "metadata": {
        "id": "4IpnBSRcoxdT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.set({'figure.figsize':(10,6)}, rc={'axes.facecolor':'white'} )\n",
        "plt.hist(x=data['strength'], color='orange')\n",
        "plt.title('Total Kekuatan Bangunan (MPa)',size=18)\n",
        "plt.xlabel('Kekuatan Bangunan (MPa)', size=14)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 412
        },
        "id": "uDQP3w3tlxQX",
        "outputId": "21086bed-e6f0-4e7b-c204-e700e3bb98fd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "menampilkan stastik hubungan anatara total cement(kg) dan kekuan bangunan (mpa)\n",
        "\n",
        "\n",
        "2. Jelaskan kesimpulan yang bisa di ambil dari analysis yg anda lakukan\n",
        "\n",
        "> # Buat uji hipotesis untuk menentukan null atau alternate hypothesis\n",
        "\n"
      ],
      "metadata": {
        "id": "FZN5xN2mo4hJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.set({'figure.figsize':(10,6)}, rc={'axes.facecolor':'white'} )\n",
        "plt.scatter(x=data['cement'], y=data['strength'], color='purple')\n",
        "plt.title('Hubungan antara Total Cement(KG) dan Kekuatan Bangunan (MPa)',size=18)\n",
        "plt.xlabel('Semen (KG)', size=14)\n",
        "plt.ylabel('Kekuatan (MPa)', size=14)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 412
        },
        "id": "3e-AVSGGmODM",
        "outputId": "1f56e038-79c2-472f-dd7c-ac94f1dbe18f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Secara umum, null hypothesis akan menyatakan bahwa kedua populasi yang diuji tidak memiliki perbedaan yang signifikan secara statistik.\n",
        "alternate hypothesis akan menyatakan bahwa ada perbedaan.\n",
        "Two sampled T-test :-Uji Independent Samples t Test atau 2-sample t-test membandingkan rata-rata dua kelompok independen untuk menentukan apakah ada bukti statistik bahwa rata-rata populasi terkait berbeda secara signifikan."
      ],
      "metadata": {
        "id": "t6vLKQPGe-Ca"
      }
    }
  ]
}