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This study aims to investigate the influence of Problem-Based Learning/PBL) to increase student’s softskills in Accounting Department at Ambon City and then simultaneously generate accounting learning model that can be used by universities to improve the quality of learning both personal qualities and scientific quality through analytical skills, creativity, and open to innovation and new findings. The population in this study were students from the Department of Accounting at the Faculty of Economics and Faculty of Economics, Pattimura University in Darussalam Ambon. Samples were students from the Department of Accounting that would  taken courses in Management Accounting at Department of Accounting - FE Pattimura University, and Darussalam University in Ambon City. In every department, sampling of 30 people. The sampling technique used is nonprobability sampling with purposive sampling. Methods of data collection begins with the class treatments (to make small groups, giving the case/problem, advice by the facilitator, discussion in small group, resume small group, and facilitators make conclusions on the problems discussed), then a questionnaire distributed to respondents for answering that how perception’s respondent of PBL influence to  increase in student’s softskills. The results of hypothesis testing with simple regression analysis showed that problem-based learning (PBL) to have significant effect on the increase student’s softskill in university of state and university of private at Ambon City.   Key Words: Problem-Based Learning, Softskills

Academic data increases every year in line with the increase of students. Abundant data store is alsoan abundance of information. Data mining technology is a tool for extracting information on largedatabases and has been widely used in many domains. Predicting student performance (study evaluation) isan activity to determine a future state based on existing data. Data in the field of academic research hasbeen done with various methods and algorithms, but the use of algorithm SLIQ (Supervised Learning InQuest) has not been done.SLIQ is an algorithm developed by the IBM's Quest project team in 1996 for mining large datasets.SLIQ algorithm classify and predict the students performance, beginning with the data cleaning, conductedelection training and testing data. By calculating gini index of each attribute and then selecting thesmallest gini index data table is split according to the criteria until find the same class. From the results ofthe calculation process can produce a set of rules that can be used to predict student performance.From the experiment it can be concluded that the algorithm SLIQ with decision tree technique canbe used as an alternative in designing a system datamining applications. Tests conducted system showedthat the constructed model can be used to predict the performance of new students. The resulting accuracyof the model system in fact has a lower score than the accuracy of other applications that are used as acomparison of Tanagra. Advantages of the proposed system is in its design does not need complexcalculations in obtaining the gini index attributes.