NAUFAL, MUHAMAD FAHRI (2022) Komparasi Algoritma Regresi Linear dan Algoritma C4.5 Untuk Memprediksi Penjualan Sayur Mayur (PT. Kebun Sayur Segar). S1 thesis, Universitas Mercu Buana.
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Abstract
Vegetables are a staple food other than rice which is often consumed daily. Vegetables are also healthy foods that contain high water content, vitamins and a lot of fiber so that they are good for the body. As for examples of vegetables that are often consumed daily such as Spinach which contains vitamins A, B, C and E, there are also Carrots which are vegetables that are good for the eyes because they contain vitamin A, and there are manymore vegetables that contain a lot of vitamins and are good for the body. PT. The Fresh Vegetable Garden grows its own vegetables that are sold so that the condition of the vegetables until they are produced is still fresh, but there are often some vegetables that are wilted and rotten due to too much stock. This resulted in losses for PT. Fresh Vegetable Garden. Therefore, in this study, researchers want to predict the sale of vegetables in PT. Fresh Vegetable Garden to be able to predict future vegetable stocks to be able to reduce losses, therefore predictions are needed using linear regression algorithms and C4.5 algorithms to predict. This research obtained the results from the vegetable sales chart, namely the type of vegetable that customers are interested in is hydroponic. Based on the tests of all these experiments where the test uses mae parameters, MSE, R2 Score with linear regression test results, Based on the parameters used get the results of standard value accuracy, where the linear regression algorithm gets the accuracy of MAE parameters 42762.92, MSE 14888137878.77 and R2 Score 0.64. For calculations using the C 4.5 algorithm with parameters MAE 32729.73, MSE 15607295869.63, and R2 Score 0.62. Key words: prediction, regression linear algorithm, C4.5 algorithm Sayur-mayur adalah makanan pokok selain nasi yang sering dikonsumsi sehari-hari. Sayur-mayur juga makanan sehat yang mengandung kadar air tinggi, vitamin dan serat yang banyak sehingga baik untuk tubuh. Adapun contoh sayur yang sering di konsumsi sehari-hari seperti Bayam yang mengandung vitamin A, B, C dan E, ada juga Wortel yang merupakan sayuran yang baik bagi mata karena mengandung vitamin A, dan masih banyak lagi sayur yang banyak mengandung vitamin dan baik untuk tubuh. PT. Kebun Sayur Segar menanam sendiri sayur-mayur yang di jual sehingga kondisi sayur sampainya diprodusen masih segar, namun sering kali ada beberapa sayur yang layu dan busuk dikarenakan stok terlalu banyak. Hal ini mengakibatkan kerugian untuk PT. Kebun Sayur Segar. Oleh karena itu dalam penelitian ini peneliti ingin melakukan prediksi terhadap penjualan sayuran pada PT. Kebun Sayur Segar untuk dapat memprediksi terhadap stok sayur kedepannya untuk dapat mengurangi kerugian oleh karena itu dibutuhkan prediksi dengan menggunakan algoritma regresi linear dan algoritma C4.5 untuk memprediksi. Penelitian ini mendapatkan hasil dari grafik penjualan sayur-mayur yaitu jenis sayur yang diminati customer adalah hydroponic. Bedasarkan dari pengujian dari semua percobaan ini dimana pengujian menggunakan parameter MAE,MSE,R2 Score dengan hasil pengujian regresi linear, Bedasarkan parameter yang dipakai mendapatkan hasil akurasi nilai standar, dimana algoritma regresi linear mendapatkan akurasi parameter MAE 42762.92, MSE 14888137878.77 dan R2 Score 0.64. Untuk perhitungan menggunakan algoritma C 4.5 dengan parameter MAE 32729.73, MSE 15607295869.63, dan R2 Score 0.62. Kata kunci: prediksi, algoritma regresi linear, algoritma C4.5
| Item Type: | Thesis (S1) |
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| Call Number CD: | FIK/INFO. 22 124 |
| Call Number: | SIK/15/22/049 |
| NIM/NIDN Creators: | 41518010064 |
| Subjects: | 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika 500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 518 Numerical Analysis/Analisis Numerik, Analisa Numerik |
| Divisions: | Fakultas Ilmu Komputer > Informatika |
| Depositing User: | WADINDA ROSADI |
| Date Deposited: | 19 Oct 2022 06:45 |
| Last Modified: | 19 Oct 2022 06:45 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/70601 |
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