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Slamet Riyadi
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Department of Information Technology Faculty of Engineering, Universitas Muhammadiyah Yogyakarta F3 Building, 2nd Floor Brawijaya Street, Tamantirto, Kasihan, Bantul, Yogyakarta 55183 Indonesia
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Emerging Information Science and Technology
Published by Universitas Muhammadiyah Yogyakarta
ISSN : 27226042     EISSN : 27226050     DOI : https://doi.org/10.18196/eist
Core Subject : Science,
Computer Science & IT
Emerging Information Science and Technology is a double-blind peer-reviewed journal which publishes high quality and state-of-the-art research articles in the area of information science and technology. The articles in this journal cover from theoretical, technical, empirical, and practical research. It is also an interdisciplinary journal that interested in both works from the boundaries of subdisciplines in Information Science and Technology and from the boundaries between Information Science and Technology with other disciplines. EIST is an Open Access Journal to advance sharing science and technology. People have rights to read, download, copy, distribute, print and use with proper acknowledgment and citation. There is no publication fees for authors.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol 1, No 3: August 2020" : 5 Documents clear
Implementation of Multiclass Support Vector Machine for Classification of New Students Receiving Achievement Scholarships at Universitas Muhammadiyah Yogyakarta Nurfahmi Nurfahmi; Slamet Riyadi; Asroni Asroni
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 (660.278 KB) | DOI: 10.18196/eist.v1i3.10627

Abstract

The selection process for scholarship grantees at Universitas Muhammadiyah Yogyakarta (UMY) still utilizes the conventional method, namely Microsoft Excel. It is conducted by inputting all student data, then sorted from the highest to the lowest. Scholarships for prospective new students must be right on the target, meaning that they meet the criteria for students eligible for scholarships. It is intended not to harm other prospective students who should get scholarships. In previous studies, the classification process used many algorithms such as Naive Bayes, C.45, Decision Tree, k-Nearest Neighbor, and Support Vector Machine. The use of the Support Vector Machine algorithm employed a two-class classification. Support Vector Machine and Decision Tree algorithms are two classification methods that can obtain precise and accurate results. This study aims to use the Multiclass Support Vector Machine (LibSVM) algorithm to classify the achievement scholarship rankings for new students. The minimum amount of data used affected the classification results. From the 2015 to 2019 data, the highest amount of data was 2015, obtaining the highest accuracy result of 84.34% using the sigmoid kernel type and the k-fold value of 3. The classification was based on the entry system stages. PMDK stage 2 obtained an accuracy of 81.38%, with the most data amounting to 268 from stage 3.
Designing a Payroll System Database for Staff of the Informatics Engineering Department of Universitas Muhammadiyah Yogyakarta Nisrina Akbar Rizky Putri; Slamet Riyadi; 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 (1253.364 KB) | DOI: 10.18196/eist.v1i3.13157

Abstract

The development of a staff payroll system aims to create a system that can help an administrator recapitulate attendance and payroll data of Informatics Engineering (IE) Department staff quickly and accurately. Such a development requires a database. The database design is divided into four stages: requirement collection and analysis, conceptual database design, logical database design, and physical database design. Design testing was performed on the database by testing the access policies, anomaly check, and view check. The results reveal that the proposed system worked well did not encounter anomalies.
The Implementation of Clustering Method With K-Means Algorithm In Grouping Data of Students’ Course Scores at Universitas Muhammadiyah Yogyakarta Asroni Asroni; Dita Kurniasari; 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 (950.745 KB) | DOI: 10.18196/eist.v1i3.13172

Abstract

Student grades can be a reference. A large number of student grade data in a university causes data accumulation; thus, data are grouped with data mining. This study aims to classify student grade data in the second semester. Grouping student grade data was performed using the clustering method with the K-means algorithm. The research data were derived from the database of Universitas Muhammadiyah Yogyakarta. The data were students’ grades in the academic years of 2010/2011, 2011/2012, 2012/2013, 2013/2014, and 2014/2015. The analysis process was carried out using WEKA software, SQL Server 2014 Management Studio and Microsoft Excel. The clustering method could be applied to group student grade data. Clustering with K-means formed three clusters, with cluster 0 comprising 72 students, cluster 1 consisting of 190 students, and cluster 2 totaling 133 students. A cluster with the lowest average score could be used as a consideration in updating the learning methods to optimize students’ score acquisition.
Designing a Fun English Vocabulary Card Application as a Means of Learning English Vocabulary for Elementary School Students Haris Setyawan; Radityo Anindito Arighi; Reza Giga Isnanda
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 (622.81 KB) | DOI: 10.18196/eist.v1i3.13173

Abstract

English has been globally used for communication and studied by almost all countries. Therefore, understanding and being able to communicate in English is crucial. A lot of English learning is currently delivered using the lecture method, but there is no medium for learning English vocabulary in an application. This study aims to create a Fun English Vocabulary Card game to improve children’s English vocabulary. To design the learning model, the design of use case and activity diagrams was utilized. Based on the pre-test and post-test results, this game significantly increased children’s English vocabulary. The average pre-test score was 43.625, and the average post-test score was 95, which indicates that the educational game application could improve users’ knowledge and understanding of English vocabulary.
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.

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