Garuda - Garba Rujukan Digital

Implementasi Arsitektur Operational Data Store (ODS) dan Dimensional Data Store (DDS) dalam Pembangunan Data Mart Lulusan Bakhtiar, Rohmana Zulfa; Riyadi, Slamet; Asroni, Asroni
Semesta Teknika Vol 18, No 1 (2015): MEI 2015
Publisher : Semesta Teknika

Show Abstract | Download Original | Original Source | Check in Google Scholar

Universitas Muhammadiyah Yogyakarta (UMY) is a big and high-grade educational institution. During the period of 1998-2014, UMY has produced about 20550 graduates. But, the big number of graduates is not supported by a good data storage system. Whereas those data are needed in filling up the accreditation form. For that reason, we have to build an integrated data storage system to provide graduates data as needed, that is graduate data mart. The development of graduate data mart uses SDLC Model Waterfall method. This method involves several types, there are requirement analysis, design system, implementation system, testing system, and maintenance system and those must be done sequentially. If there is an error, the process must be repeated from the beginning to fix the error. Development of graduate data mart uses Operational Data Store (ODS) and Dimensional Data Store (DDS) architecture. Those architectures are selected because they support transactional level. By using those architectures, graduate data mart is capable to display the data of graduates on the academic year, GPA, educational years, and the status of the student transfers. As the result, those data are able to help the management of university in filling up the accreditation form.

Penerapan Metode K-Means Untuk Clustering Mahasiswa Berdasarkan Nilai Akademik Dengan Weka Interface Studi Kasus Pada Jurusan Teknik Informatika UMM Magelang Asroni, Asroni; Adrian, Ronald
Semesta Teknika Vol 18, No 1 (2015): MEI 2015
Publisher : Semesta Teknika

Show Abstract | Download Original | Original Source | Check in Google Scholar

The selection process among outstanding students in a department has a big problem. This process is not fair because only involve one criteria and ignore the other criteria. We need the best student to participate in a competition held by the Indonesia Security Incident Response Team on Internet Infrastructure (ID SIRTII) of the Ministry of Communication and Information. This process uses Weka software to calculate the best student. It provides the various method to explore the data. One of them is clustering method. There are many algorithms in clustering method. In this research, we will investigate widely about one of that algorithms. Its name is K-Means. This algorithm (K-Means) will give the recommendations about the best student based on the cluster. It will represent the many clusters of a student group. The best cluster can be calculated more to get the names of the best students group. They are eligible to enter the competition.Â K-means involve the GPA (Grade Point Average) and related course to support the academic skill in order to get the best student. This research helps the teacher select the best student to enter the competition. Many similar cases can use this algorithm in order to get the best student.

Penerapan Algoritma C4.5 untuk Klasifikasi Jenis Pekerjaan Alumni di Universitas Muhammadiyah Yogyakarta Asroni, Asroni; Respati, Badrahini Masajeng; Riyadi, Slamet
Semesta Teknika Vol 21, No 2 (2018): NOVEMBER 2018
Publisher : Semesta Teknika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/st.212222

The development of education in Indonesia has increased very rapidly. One of the things that have become a benchmark for success in the quality of education at the university is the kind of job getting graduates after graduation. This research aims to identify factors that have an impact on the type of job classification method based on the C 4.5 alumni algorithm. The methodology of this research begins with the study of literature, the identification of a process of data extraction, data selection, data collection, data processing, data testing, and DA conclusion. This research uses some features of the data on a few faculty members, the year of graduation, the annual completion rate, and the strength as a classification performance parameter. Graduates data used up to 259, and consisted of 3 faculties of Economics, medicine and engineering forces from 2001-2013 and graduated from 2011-2016. The research results that have been done is if it comes from the Faculty of Economics, in 2011 and 2012 the majority of work in the private sector has passed, if it comes from the Faculty of Medicine with the years 2011 and 2012 graduated with a cumulative labor rate of between 3 to 3.5 majority working in The private sector, 2012 with a GPA between 3 and 3.5 working in the Private Sector. Finally, the C4.5 algorithm is suitable for the classification of alumni work types.

Perkiraan Masa Tunggu Alumni Mendapatkan Pekerjaan Menggunakan Metode Prediksi Data Mining Dengan Algoritma Naive Bayes Classifier Asroni, Asroni; Ali, Nadiyah Maharty; Riyadi, Slamet
Semesta Teknika Vol 21, No 2 (2018): NOVEMBER 2018
Publisher : Semesta Teknika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/st.212225

Student and Alumni data Universitas Muhammadiyah Yogyakarta is very common, and one of these is the alumni data obtained from work after the completion of undergraduate studies. Former students are given jobs caused or influenced by a range of factors. This research aims to have the grace period Classification or old alumni gain positions by triggering a process of data extraction and using the Bayes naïve classification algorithm. The algorithms used later succeeded in predicting sooner or later to get a job, the predictive results alumni can be used to make decisions to improve the quality of a university. Research on the support system using several parameters, i.e., gender, faculty, GPA, year of graduation, and job status. The data used are as much as 435, including seven years of 2011-2014 volume. The results of this study have the accuracy level of former students having the grace period come to 71% and of the calculated results of the predictions of the former students obtaining a job at Universitas Muhammadiyah Yogyakarta of the year 2011-2014 the Ensure that the work is carried out more quickly with the status of the slow to deliver the work

Sistem Informasi Menajemen Aset (Studi Kasus: Desa Barepan) Setyawan, Haris; Asroni, Asroni
Semesta Teknika Vol 21, No 2 (2018): NOVEMBER 2018
Publisher : Semesta Teknika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/st.212221

Barepan Village is one of the villages in Cawas sub-district, Klaten, Central Java. In 2017 Barepan Village has owned a new building as a means of village administration and obtains assets that support the implementation of government such as computers, tables, chairs, and others. However, asset management is currently not going well and does not have a unique asset database to facilitate the management and tracking of its assets. This caused the difficulty of conducting asset track which made it difficult for asset managers to know the condition of the asset was right, damaged or lost. Therefore, an information system is needed which has the objective to be able to run the business process of asset management to be neat and structured so that asset managers can efficiently manage and track assets. The process of designing an Asset Management Information System using the waterfall model software development method begins with needs analysis, design, coding, testing, and maintenance. From the design stage, it was then created with Code Igniter in the form of a PHP framework with the MVC concept so that a website-based Information System with the MVC concept was produced. Verification and validation are then carried out to determine the suitability of the system design with the Asset Management Information System final results that have been made. Finally, an asset information system can be obtained that fits your needs and archives assets well.

Penerapan Metode K-Means Untuk Clustering Mahasiswa Berdasarkan Nilai Akademik Dengan Weka Interface Studi Kasus Pada Jurusan Teknik Informatika UMM Magelang Asroni, Asroni; Adrian, Ronald
Semesta Teknika Vol 18, No 1 (2015): MEI 2015
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/st.v18i1.708

The selection process among outstanding students in a department has a big problem. This process is not fair because only involve one criteria and ignore the other criteria. We need the best student to participate in a competition held by the Indonesia Security Incident Response Team on Internet Infrastructure (ID SIRTII) of the Ministry of Communication and Information. This process uses Weka software to calculate the best student. It provides the various method to explore the data. One of them is clustering method. There are many algorithms in clustering method. In this research, we will investigate widely about one of that algorithms. Its name is K-Means. This algorithm (K-Means) will give the recommendations about the best student based on the cluster. It will represent the many clusters of a student group. The best cluster can be calculated more to get the names of the best students group. They are eligible to enter the competition.Â K-means involve the GPA (Grade Point Average) and related course to support the academic skill in order to get the best student. This research helps the teacher select the best student to enter the competition. Many similar cases can use this algorithm in order to get the best student.

Title

Found 6 Documents
Search
Journal : semesta teknika

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 6 Documents Search Journal : semesta teknika

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 6 Documents
Search
Journal : semesta teknika