MODELING OF SLUMP VALUE AND DETERMINATION OF INFLUENTIAL VARIABLES WITH REGRESSION APPROACH - Eri Cahyani; Ari Wibowo; Indradi Wijatmiko (Rekayasa Sipil, 2019)
There are many factors underlying the instability of the consistency of the concrete mixture. The consistency of the concrete mixture was measured using a slump test. Slump tests are commonly used in measuring the quality of fresh concrete. The instability of the slump value becomes an unsolved problem. To facilitate predicting slump values, modeling is needed to reduce variations in concrete job mixs. Regression has been known as the basic method of predictive modeling. Collected data is divided according to the ratio of sand to: <38%, 38-44% and> 44%. The sand ratio data <38% is the most suitable model, because it has a value of R2 0.957, adj. R2 0.897 and MSE 0.31. The most influential variable is water, retarder, gravel 20-30mm. The resulting modeling is adjusted to the range of data collected.