Perbandingan algoritma c4.5 dengan rough set dalam klasifikasi data laporan laba/rugi yang berpengaruh terhadap profit pada PT. Sarana Utama Nusa Trans

Khongdinata, Alvin (2021) Perbandingan algoritma c4.5 dengan rough set dalam klasifikasi data laporan laba/rugi yang berpengaruh terhadap profit pada PT. Sarana Utama Nusa Trans. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

Laporan laba/rugi merupakan laporan finansial pada perusahaan yang berisi data – data seperti data pendapatan, penjualan, stok, beban usaha, dan sebagainya yang ditanggung perusahaan. Rata – rata perusahaan pasti mempunyai laporan keuangan pada laba/rugi dan salah satunya yaitu PT. Sarana Utama Nusa Trans yang bergerak dalam bidang jasa kepabean (EMKL/PPJK) dan ekspedisi (Trucking). Dalam mengevaluasi laba/rugi, perusahaan hanya menganggap laba akan tercapai jika pendapatan yang diperoleh besar sehingga hal lain yang berpengaruh tidak diketahui. Untuk mengoptimalkan evaluasi laba/rugi, suatu perusahaan perlu untuk mengetahui apa – apa saja yang berpengaruhi terhadap laba/rugi yang diperoleh. Ada dua algoritma pada data mining yang digunakan dalam penelitian ini yaitu Rough Set dan Algoritma C4.5. Kedua algoritma tersebut digunakan untuk mencari aturan klasifikasi seperti hal apa saja yang berpengaruh terhadap laba dan rugi perusahaan. Data yang diperoleh dari laporan laba/rugi dari perusahaan terdapat 5 atribut dan 1 label/keputusannya yaitu Pendapatan (EMKL), Pendapatan (Trucking), Pembelian, Trip, Beban Usaha dan labelnya yaitu Laba. Berdasarkan perhitungan dari kedua metode, metode Rough Set menghasilkan new rules/aturan baru sebanyak 60 rules, sedangkan metode C4.5 Decision Tree menghasilkan new rules/aturan baru sebanyak 6 rules./Income Statement is a financial report on the company that contains data such as data on income, sales, stock, operating expenses, and so on that are borne by the company. The average company must have a financial statement on profit / loss and one of them is PT. Sarana Utama Nusa Trans which is engaged in customs services (EMKL/PPJK) and expeditions (Trucking). In evaluating profit/loss, the company only assumes that profit will be achieved if the income earned is large so that other influential factors are unknown. To optimize the evaluation of profit/loss, a company needs to know what affects the profit/loss obtained. There are two data mining algorithms used in this research, namely the Rough Set and the C4.5 Algorithm. The two algorithms are used to find classification rules such as what things affect the company's profit and loss. The data obtained from the profit/loss report from the company contains 5 attributes and 1 label/decision, namely Revenue (EMKL), Revenue (Trucking), Purchases, Trips, Operating Expenses and the label is Profit. Based on the calculations of the two methods, the Rough Set method produces 60 new rules / new rules, while the C4.5 Decision Tree method produces 6 new rules / new rules.

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