KOMPARASI METODE NEURAL NETWORK, SUPPORT VECTOR MACHINE DAN LINEAR REGRESSION PADA ESTIMASI KUAT TEKAN BETON

  • Tyas Setiyorini Teknik Informatika STMIK Nusa Mandiri Jakarta
  • Rizky Tri Asmono Teknik Informatika STMIK Nusa Mandiri Jakarta
Keywords: Metode Neural Network, Metode Support Vector Machine, Metode Linear Regression, Estimasi Kuat Tekan Beton

Abstract

Penggunaan beton sudah semakin meluas dikarenakan beton memiliki kuat tekan yang lebih tinggi dibandingkan dengan bahan lain. Para ahli melakukan prediksi kuat tekan beton dengan kurang efektif karena masih menggunakan aturan dan rumus standar tertentu.  Banyak penelitian dilakukan dengan beberapa metode namun belum diketahui metode mana yang terbaik. Penelitian ini melakukan komparasi antara metode Neural Network (NN), Support Vector Machine (SVM) dan Linear Regression (LR) dengan menggunakan dataset concrete compressive strength dan slump.   Pada dataset concrete compressive strength dengan menggunakan metode NN didapatkan RMSE 5,667, dengan menggunakan metode SVM didapatkan RMSE 5,165 dan dengan metode LR didapatkan RMSE 10,501. Sementara pada dataset slump dengan menggunakan metode NN didapatkan RMSE 0,422, dengan menggunakan metode SVM didapatkan RMSE 2,778 dan dengan menggunakan metode LR didapatkan RMSE 2,65. Setelah hasil tersebut dikomparasi dengan perangkingan didapatkan total ranking NN adalah 3, total rangking SVM adalah 4, dan total rangking LR adalah 5. Dari total rangking tersebut dapat disimpulkan bahwa kinerja NN lebih baik dibanding SVM dan LR.

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Published
2018-03-15
How to Cite
Setiyorini, T., & Asmono, R. (2018). KOMPARASI METODE NEURAL NETWORK, SUPPORT VECTOR MACHINE DAN LINEAR REGRESSION PADA ESTIMASI KUAT TEKAN BETON. Jurnal Techno Nusa Mandiri, 15(1), 51-56. https://doi.org/10.33480/techno.v15i1.58
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