Model Jaringan Saraf Tiruan Kuat Tekan Beton Porus dengan Material Pengisi Pasir
DOI:
https://doi.org/10.5614/jts.2013.20.1.3Keywords:
Jaringan saraf tiruan, Densitas, Beton porus, Rasio pasir-semen.Abstract
Abstrak. Beton porus adalah salah satu beton ringan dan bentuk dasarnya merupakan perpaduan antara pasir, semen, air (campuran dasar) dan foam (biasanya 0,1-1,0 mm diameter). Penelitian ini difokuskan pada aplikasi jaringan saraf tiruan (JST) untuk memprediksi kuat tekan beton porus. Metode JST dapat menangkap interaksi yang kompleks antara variabel input/output dalam suatu sistem tanpa pengetahuan sebelumnya dari sifat interaksi dan tanpa harus secara eksplisit mengasumsikan bentuk model. Makalah ini menjelaskan data penelitian yang ada, seleksi data dan proses pelatihan model JST, dan validasi. Hasil penelitian menunjukkan bahwa kuat tekan beton porus dapat diprediksi lebih akurat, mudah dan cepat dari densitas beton porus, rasio pasir dan semen dan distribusi ukuran partikel pasir.Abstract. Foamed concrete is one of light concrete and its basic form is a blend of sand, cement, water (the base mix) and a pre-formed foam (usually 0.1 to 1.0 mm in diameter). This research focus on application of artificial neural networks (ANN) to predict the compressive strength of foamed concrete mixtures. The ANN method can capture complex interactions among input/output variables in a system without any prior knowledge of the nature of these interactions and without having to explicitly assume a model form. Indeed, such a model form is generated by the data points themselves. This paper describes the database assembled, the selection and training process of the ANN model, and its validation. Results showed compressive strength of foamed concrete can be predicted much accurately, easy and fast from density of foamed concrete, sand and cement ratio and particle size distribution of sand.
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