Gypsum is one of the additive raw materials added to the clinker grinding process that regulate the binding time of cement or commonly known as a retarder. This research aims to observe the effect of gypsum added variation on the compressive strength of mortar and the whole quality of Portland Composite Cement at plant 14 P.T Indocement Tunggal Prakasa Tbk. The PCC compositions did prepare with a variation of the addition of 0 - 5% gypsum where the clinker ratio did fix at 75%, and two other additives, namely limestone, and trass did add with a fixed ratio of 1.2: 1. The effect of adding gypsum to clinker measured by performing a mortar compressive strength test and the binding time at the ages of 1, 3, 7, and 28 days. The results of series observation and analysis show that composite Portland cement has the most optimal quality in the addition of gypsum as much as 3.5%, where SO3 content is 1.7%, the initial setting time is ≥ 90, and the final setting time is maximum at 375 minutes.

Currently, the use of alternative fuels and raw materials (AFR) in the cement industry is very attractive. This is driven by demands for environmental sustainability and the efficiency of fuel and raw material costs. One of the materials that can be used as AFR is sludge oil. However, it needs to be ensured that the chlorine content in the sludge oil does not exceed the threshold so that it does not have a negative impact during the cement production process. It is known that if the chlorine content is more than the threshold, it can cause blocking or clogging of the separator and the kiln. This study aims to determine the performance of the Jena Multi EA 4000 instrument in determining the chlorine content in sludge oil quickly and accurately. Analytic Jena Multi EA 4000 is an Atomic Absorption Spectrometers (AAS) instrument that can be used for analysis of samples in the form of solids or slurries containing chlorine. As validation of the resulting analysis, the wet method is used, which as usual, to determine chlorine levels. From the statistic analysis, namely the F-test and T-test, We found that F-count equal to 0.0080 and F-table equal to 4.2839. it shows that F-count < F-table, indicating the difference in the variance of the two methods H0: s12 = s22 is accepted because there is no difference to the variability of these two tests and the value of T-count = -3.9717 and T-table = 2.1788 so that T-count <T-table is accepted because there is no difference in the average accuracy of the two methods H0: M1 = M2.

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