Abstract
Abstract. The world of mining is closely related to rock because most of the minerals are stuck to or in the rock itself. Therefore we need a method and technique on how to separate the mineral from rocks that are not economical. Because rocks have different properties in each type, in this case rock mechanics is needed. One of the tests for the mechanical properties of rock is the uniaxial compressive strength test. UCS is one of the most important and most widely used rock mechanics parameters in rock engineering. To test rocks, samples from the field are needed in the form of solid rock or coring rock. Sometimes there are rocks with a thin layer, causing the coring to crack or break, causing difficulty in sample preparation. One method that arises for the above problem is the Block Punch Index (BPI) test. The Block Punch Index (BPI) test is useful for testing in the field because the tool is easy to carry and the level of accuracy is better than the Point Load Index (PLI) test. The BPI test and the PLI test are both index tests, the difference is that the PLI uses point loading and the BPI uses block-shaped loading. It can be used to determine rock strength values and even to analyze slope stability based on index values and rock strength. Researchers designed a BPI tool for research that is useful for obtaining a graph of the relationship between UCS and BPI. As a result of the research, the following conclusions were made. First, the design of the BPI tool is made based on several components, including an iron pipe with a thickness of 0.5 cm with a diameter of 6 cm and a height of 9 cm. Solid iron in the shape of the letter T with a block punch size of 18 mm. Solid iron with a diameter of 6 cm, a width of 20 mm for the sample break and a depth of 15 mm. Second, the thickness of the sample according to the tool is a sample with a thickness of 10 mm because there are more valid fractures than samples with a thickness of 7.5 mm and 12.5 mm. Third, from the graph of the relationship between BPI and UCS, to predict the value of UCS, you can use the formula y = -0.5164x2 + 4.7167x + 4,8406
Keywords : Rock, BPI, Graphics, UCS, and Mechanical Properties