Fountain of Informatics Journal

5-9

Authors: Indah Puji Astuti

The student is one of unsure in University or Higher Education. The student has different of data, such as self-identity information such as address, type of school, work of parents, type of class, etc. The students whose graduation rate is different, on time and not on time. The number of students who graduate is not on time will be a problem not only for university but also for faculty. The number of students graduating each year is one of factor of assessment when faculty or study program submits accreditation. C4.5 Algorithm is one of classification algorithm with decision trees. In this study conducted an analysis of student data Engineering Studies Program University of Muhammadiyah Ponorogo 2012/2013. The decision trees in this case is useful for exploring student data, finding the hidden relationship between of input attributes with a target attribute. The input attribute consist of, the type of school, address, work of parent, and type of class. The output attribute to classify is status, which consists of "on time" and "not on time". The results from this analysis shown that in this case the C4.5 algorithm can predict with an accuracy value only 82%.

20-27

Authors: Gita Indah Marthasari

One indicator of college efficiency is the study period of the students. It is important for university managers to improve the ratio of students who graduate on time. This research aims to analyze the characteristics that affect the study period of students from academic data. The methods used are association rule mining (ARM) and clustering. We propose a framework to analyze academic data using ARM and clustering method. ARM method is a method to find association rules that meet minimum support and minimum confidence. The algorithm used is Apriori. While clustering using Simple Expectation-Maximization (EM-clustering) algorithm. Simple EM is a model-based algorithm that searches for maximum likelihood estimation in the probability model. The variables analyzed were student achievement index, province of the students, and type of high school. The analysis is done using WEKA. Research begins with the collection of data from the primary source of the Biro Administrasi Akademik (BAA) Universitas Muhammadiyah Malang (UMM). Then, we do the data cleaning and transformation. Analyzing process is done in two step. First, do a rule search using Apriori algorithm. The regulated parameters are the minimum support and minimum confidence value. Second, we use Simple EM algorithm for the clustering process. The experiments were conducted to find the clustering result with the largest log likelihood value. Based on the experiment, the method used successfully describes the characteristics based on the study period.

8-16

Authors: Jumhurul Umami

One of the annual program in Pondok Modern Darussalam Gontor is selection lecturer or chaplain or teacher. In the selection process of teachers who are still there are problems such as the lack of expertise in IT that are still using Microsoft Access displayed manually and not using certain method, besides that just rely on the senior chaplain and part nurture students who are limited in number to evaluate classroom discipline students, the number of candidates for religious teacher will be selected also does not provide maximum results and requires a very long time. Therefore that Gontor require a system that can help in the decision making process to solve these problems, one of them made the Candidate Selection Decision Support System Ustadz Method Using Analytical Hierarchy Process (AHP). The results of the process of this system is the list of 100 best ratings will be a candidate teacher at Pondok Modern Darussalam Gontor I and served for one year to teach.

27-31

Authors: Sucipto

The development world of work is influenced by several factors such as the performance of human resources, so that each company tried to get quality employees. Improvement of human resources can be obtained from the process of field work practice in college. The field supervisor is a quality improvement factor for the students. Generally the selection of lecturers of fieldwork practice practicum is done without recommendation from students. That condition make students facing problems in field work practice. One of them is the students have difficulty adjusting to the supervisor because the characteristics of lecturers obtained from the college does not match with the required students. Therefore, a recommendation system of guidance lecturers in the field of Information System Department of X University facilitates the students to recommend lecturers according to their needs. In the recommendation process of lecturers the field work practices is conducted with the assessment of five variables. Variables obtained from lecturer performance assessment. Each of these assessments is taken into account and considered according to the needs of the students in the field. That system is made using decision support system method by multi-attribute of Weighted Product. Resulted of the analysis that has been done obtained an alternative of lecturers selected from the group of fieldwork students and the evaluation of lecturer selection by the student group. The result of the method is known that the analysis can give the recommendation of the supervisor lecturers to the student group in accordance with the highest score.