Abstract. The use of coal waste (Fly Ash) is currently being developed in building materials technology, as a high-strength concrete mix material. This study aims to determine the strength of concrete by adding fly ash as a substitute for cement in high-strength concrete mixtures. This research was conducted with an experimental method to obtain results and data that would confirm the variables studied. The total number of specimens used in this study were 36 pieces with different sizes of cube tests which were 15 cm x 15 cm x 15 cm. A total of 36 concrete samples were used to test the compressive strength of concrete with a percentage of Fly Ash in 0% (normal concrete), 20%, 25% and 30% with a concrete treatment age of 7 days, 21 days and 28 days. A total of 12 more samples were used to test water absorption in concrete at 28 days of maintenance. Each percentage percentage of Fly Ash uses 3 concrete test samples. The increase in compressive strength occurs at 7, 21 and 28 days in concrete. However, the compressive strength of concrete produced by concrete using the percentage of Fly Ash is always lower than the value of normal concrete compressive strength. From testing the compressive strength of concrete at 28 days of treatment with content of 0%, 20%, 25% and 30% Fly Ash obtained results of 45.87 MPa, 42.67 MPa, 40.89 MPa, and 35.27 MPa respectively
The paper presents an investigation of university students’ travel mode choice behaviour for commuting to campus. It uses a dataset collected through a survey among students of four universities in Semarang, i.e., Unnes, UINW, Udinus, and Unissula. Eight hundred and thirty-seven respondents completed the questionnaires. Multinomial logit (MNL) models are used for investigating four transport mode choices, i.e., walk, motorcycle, car, and bus. The independent variables are schools, genders, origin, residential types, vehicle ownership, driving license ownership, monthly allowance, transportation budget, and commuting distance. The model shows that all independent variables, except monthly allowance, are significant predictors. Overall, the model prediction accuracy is about 90 percent. A motorcycle was the foremost prevalent transport for school trips. Empirical models reveal that the mode of choice behaviour of non-native students differs significantly from those that originate in Semarang. The log odds of driving a car, riding a motorcycle, and walking versus riding a bus are higher when students’ origin is not from Semarang compared to Semarang.
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