Article Per Year (5 Year)
p-Index From 2021 - 2026
1.723
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control) Semesta Teknika Journal of Electrical Technology UMY Indonesian Journal of Information System Jurnal Surya Masyarakat Emerging Information Science and Technology Prosiding Seminar Nasional Program Pengabdian Masyarakat
Slamet Riyadi
Universitas Muhammadiyah Yogyakarta
Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Library & Information Science Medicine & Pharmacology Public Health Social Sciences

Published : 24 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : Semesta Teknika

 1 
Perkiraan Masa Tunggu Alumni Mendapatkan Pekerjaan Menggunakan Metode Prediksi Data Mining Dengan Algoritma Naive Bayes Classifier Asroni Asroni; Nadiyah Maharty Ali; Slamet Riyadi
Semesta Teknika Vol 21, No 2 (2018): NOVEMBER 2018
Publisher : Universitas Muhammadiyah Yogyakarta

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

Abstract

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

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

Abstract

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.
Implementasi Arsitektur Operational Data Store (ODS) dan Dimensional Data Store (DDS) dalam Pembangunan Data Mart Lulusan Rohmana Zulfa Bakhtiar; Slamet Riyadi; Asroni Asroni
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.v18i1.706

Abstract

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.
Co-Authors Abdul Eriawan Nahar Abyiyansyah Meidy Laksono Agus Jamal Amelia Mutiara Ayu Ratiwi Anna NN Chamim Aprilia Kurnianti Arif Ahmad Fadlil Arif Bintoro Johan Asroni Asroni Badrahini Masajeng Respati Cahya Damarjati Cut Maya Putri Audilla Dwijoko Purbohadi Dyah Mutiarin Fadhan Anwarodin Fauri Hakim Haris Setyawan Indira Prabasari Kamarul Hawari Ghazali Kurnianti, Apriliya Laila Ma’rifatul Azizah Lusiana Ning Saputri Milou Derks Muhammad Aldi Joko Satria Perdana Muhammad Habil Muhammad Rizki Frebian Nadiyah Maharty Ali Nafi A Utama Nafi Ananda Utama Nasrul Saefullah Nisrina Akbar Rizky Putri Nurfahmi Nurfahmi Rammadhany Rammadhany Ricki Irawan Ridho Novradinata Rohmana Zulfa Bakhtiar Ronald Adrian Ronald Adrian Sakir Ridho Wijaya Sartika Puspita Sofiani, Erma Sudiwijaya, Erwan Suparman Suwadi Suwadi Tony K Hariadi Yunita Lestari Zulfan Fadholi