PENGARUH VARIABEL BEBAS DALAM ANALISIS KAPASITAS DUKUNG DAN PENURUNAN FONDASI TIANG MENGGUNAKAN CORRELATION BASED FEATURE SELECTION (CFS)

Raden Harya Dananjaya, Sutrisno Sutrisno, Taufiqah Apriliani

Abstract

Fondasi berfungsi sebagai penyalur beban konstruksi ke tanah dan menstabilkan struktur pada bangunan. Estimasi kapasitas dukung dan penurunan fondasi menjadi salah satu bagian penting dalam perancangan bangunan. Dikarenakan perilaku tanah yang kompleks, beberapa asumsi digunakan dalam perancangan fondasi. Sistem kecerdasan buatan (AI) sering digunakan untuk mengatasi masalah tersebut. Penelitian ini membahas tingkat signifikasi variabel bebas terhadap hasil prediksi artificial neural network (ANN) dan support vector machine (SVM) menggunakan metode correlation-based feature selection (CFS). Tingkat akurasi diukur menggunakan koefisien determinasi (R2) dan root mean square error (RMSE).  Data set yang digunakan berasal dari pengujian cone penetration test (CPT), karakteristik tiang, dan pengujian beban tiang statis. Data kemudian dibagi menjadi data training dan testing. Setelah pembuatan model dengan data training, model divalidasi menggunakan data testing. Tingkat akurasi diukur menggunakan koefisien determinasi (R2) dan root mean square error (RMSE). Hasil CFS menunjukkan bahwa faktor yang paling berpengaruh pada kapasitas dukung adalah hambatan konus (qc) dengan nilai korelasi (|r|) sebesar 0,7672, sedangkan faktor yang paling berpengaruh terhadap penurunan fondasi tiang adalah diameter fondasi (D) dengan nilai korelasi  (|r|) sebesar 0,4287.

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DOI: https://doi.org/10.20961/mateksi.v11i3.65116

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