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Penerapan Metode Clustering dengan Algoritma K-Means pada Pengelompokkan Data Calon Mahasiswa Baru di Universitas Muhammadiyah Yogyakarta (Studi Kasus: Fakultas Kedokteran dan Ilmu Kesehatan, dan Fakultas Ilmu Sosial dan Ilmu Politik) Asroni Asroni; Hidayatul Fitri; Eko Prasetyo
Semesta Teknika Vol 21, No 1 (2018): MEI 2018
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/st.211211

Abstract

The increasing new prospective students in a University to make the stack more and more data, departing from it then conducted a search for new knowledge with data mining. Grouping data for prospective new students will be made by the method Clustering and used the algorithm k-means. In this penmaru there are 5 data attributes are used i.e., hometown, gender, status to qualify for selection, driveways, and majors. This analysis is performed using WEKA software and the source data taken from admissions data (penmaru) in the form of a data warehouse. Class from the use of this method is the attribute of the majors. Iteration performed as many as 3 times and the number of a cluster at the Faculty of medicine and health sciences, i.e. 4 clusters, Faculty of social and political science 3 clusters. Method Clustering can be applied to the classification of data for prospective new students. Another thing that can be analyzed from the results of the grouping candidate data, promotion strategies from each Department to increase the quantity and quality.
Visualization of Alumni Performance Using Dashboard to Support Higher Education Decision Making Hesty Ulfatriyani; Eko Prasetyo; Aprilia Kurnianti
Emerging Information Science and Technology Vol 1, No 3: August 2020
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (402.944 KB) | DOI: 10.18196/eist.v1i3.13174

Abstract

Universities in Indonesia create fierce competition. Alumni have an essential role for the educational institution, not only as a tool for measuring the performance quality and ability of education implementation but also as the standard or feedback to the perfection of the education system. One effective data presentation model is the dashboard system seen from the complexity, interactivity, and informative data presented. Therefore, this study aims to build a dashboard system at Universitas Muhammadiyah Yogyakarta (UMY). This study utilized the dashboard life cycle method in its implementation. This method had six stages: project initiation, design, construction, testing, launching and monitoring. This method allowed the study to show data on the number of judicium students, the number of graduates, the average GPA of the alumni, the average study period of alumni, and the number of alumni per graduation level for the 2012/2013 to 2017/2018 academic year, according to the accreditation forms and needs analysis. The dashboard system can provide information about alumni at UMY from 2012 to 2017. The dashboard system is ready to be applied as a decision-making tool, particularly as a strategy for improving the quality and empowering strategy for alumni of the university.
Perancangan Data Warehouse Sistem Informasi Eksekutif untuk Data Akademik Program Studi Eko Prasetyo; Lukito Edi Nugroho; Marcus Nurtiantara Aji
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 1 No 3: Agustus 2012
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (372.426 KB)

Abstract

This research examines the design of data warehouse that are the result of data integration and abstraction from various academic applications that accommodate the needs of history and archiving data to support executive information systems in the academic field. Identification of the executive reports use reference of the program accreditation forms, internal academic quality audit questionnaires, Dean’s annual reports, self-evaluation forms of Competitive Grant Program, features of the existing EIS, and features of executive data on the university academic administration website. The subject of this research is student data based on chronological stages starting from candidates selection process, new students, and students during lectures. The success of data warehouse design is determined by the right description of the business events, data completeness and validity, data mart design using metrics bus architecture, star schema design and ETL process to integrate, extract, cleanse, transform and load it into the data warehouse.