The quality of universities, especially study programs in Indonesia is measured based on accreditation conducted by BAN PT. According to BAN PT the quality is measured based on 7 main standards, one of them is Student and Graduate. One of the problems that still be the subject of discussion related to student failure is about the students who graduated not on time. Students graduating not on time are students who can not complete their studies in accordance with the provisions of time given. The existence of a graduate student is not timely of course cause problems and potentially drop out that affect the quality of education and accreditation. A system that predicts students' graduation is required by evaluating their learning outcomes. The timeliness of graduating students can be done with data mining techniques to find graduation patterns of students who have graduated which then used as a basis to predict students' graduation in the next year. This study showed that Naïve Bayes was able to classify the correct data testing on average by 86.16% and 13.84% error. In addition, other information obtained from the data testing used that the students who entered from the PMDK Pass graduated on time as much as 40%, other paths graduated on time by 26.7%, and pass filter exam on time 13.3%.

Bongongoayu is one of the regions in Indonesia that has geothermal potential. Bongongoayu requires surface and subsurface data to support the preliminary data. This research aims to determine surface and subsurface data conducted by geology and magnetic method. The surface data, including geomorphology, lithology, hydrology and manifestation. The subsurface data have taken by the magnetic method. The result showed that the geothermal manifestation of Bongongoayu is a hot pool. The surface temperature is 43 to 59 °C. The geomorphology units is composed of volcanic hills unit and lake plains unit. The lithology of the research area is composed of granite and alluvial deposits. Based on petrographic analysis, the level of alteration in granite rocks is 65% and is classified as moderate alteration. The recharge area is in the north and southwest of the research area. Discharge area is in the central area. Based on 2D magnetic modeling, there are two subsurface layers. The first layer is alluvial and the second layer is granite. Rocks that are under the alluvial layer and have been altered are interpreted as a cap rock. 2D magnetic models show normal faults in the research area as a controlling factor for geothermal fluid.

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