PENERAPAN ALGORITMA K-MEANS UNTUK KLASTERISASI INDEKS STANDAR PENCEMARAN UDARA
https://doi.org/10.26594/teknologi.v14i2.4088
Abstract
Lingkungan merupakan satu ruang utuh yang berisi semua benda, daya, keadaan, serta makhluk hidup di dalamnya, termasuk juga manusia dan perilakunya yang mempengaruhi alam. Penting untuk menjaga lingkungan agar tidak timbul pencemaran yang dapat menciptakan kondisi yang tidak sehat. Pengelompokkan pencemaran lingkungan dapat mempermudah pemerintah dalam pertimbangan wilayah mana saja yang memerlukan atensi lebih dalam penegakkan perlindungan dan pengelolaan lingkungan hidup. Pengelompokan yang digunakan menggunakan algoritma K-Means Clustering yang dapat mengelompokkan data ke dalam kelompok yang sama dan data yang berbeda ke dalam kelompok yang berbeda. Klasterisasi dilakukan terhadap data indeks standar pencemaran udara provinsi DKI Jakarta berdasarkan parameter pencemaran udara. Sehingga dapat diketahui informasi mengenai kualitas udara terutama di wilayah provinsi DKI Jakarta. Data yang digunakan adalah data tahun 2021 dan diperoleh dari situs resmi Jakarta Open Data. Dataset berisi 365 hari pemantauan kualitas udara tahun 2021 serta parameter pencemaran udara seperti pm10, pm25, so2, co, 03, dan n02. Data yang telah diperoleh kemudian diolah dengan tools RapidMiner menggunakan Algoritma K-Means Clustering dalam 3 cluster, diketahui hasil klasterisasi yaitu kategori kualitas udara sehat pada cluster 0 terdiri dari 39 hari, kategori kualitas udara sedang pada cluster 1 yang terdiri dari 128 hari, dan kategori kualitas udara tidak sehat pada cluster 2 yang terdiri dari 198 hari. Sehingga dapat diketahui hasil klasterisasi dengan Algoritma K-Means terhadap kualitas udara di Provinsi DKI Jakarta tahun 2021 cenderung berada di kategori tidak sehat. Hasil klasterisasi ini diharapkan dapat menjadi masukan bagi pemerintah dalam upaya penanganan daerah yang mengalami pencemaran lingkungan.
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