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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 4: November 2020" : 5 Documents clear
The Development of Game App 'Find the Object' to Improve English Vocabulary Mastery Titis Wisnu Wijaya; Reza Giga Isnanda; Bhaskara Satrya Priwadhana
Emerging Information Science and Technology Vol 1, No 4: November 2020
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v1i4.16594

Abstract

English is a communication international language with more than 50 countries using it as their primary language. Therefore, understanding and ability to communicate in English is needed. During this time, the method of learning English is mostly delivered using the Teacher Centered Learning (TCL) method and there are still a few English vocabulary learning media in the form of applications used in the learning process in the classroom. The purpose of this study was to create a game called Find the Object to help students, especially the elementary school level, to learn English vocabulary to make it more interesting. There is a pre-test and post-test to conclude whether this game significantly managed to improve the mastery of English vocabulary. This needs to be proven through observing the value of the pre-test and post-test
Scholarship Acceptance Selection Using Neural Network Method Rammadhany Rammadhany; Slamet Riyadi; Asroni Asroni
Emerging Information Science and Technology Vol 1, No 4: November 2020
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v1i4.16595

Abstract

Muhammadiyah University of Yogyakarta is one of the private tertiary institutions that provides scholarship programs. UMY provides scholarship programs for outstanding students and middle-lower class students. In the process of receiving a scholarship, UMY has two stages, namely registration and selection. In order to obtain a scholarship, students who register must be declared to pass administrative selection and meet the assessment component as a condition for students to be eligible for scholarships. In order to know the scholarship information received by students, data processing is needed, data processing is often referred to as data mining. This writing is done to predict prospective scholarship recipients using the Neural network algorithm. The methodology at this writing begins with searching for literature studies, choosing data mining methods, data collection, data processing, application and testing of models, results and conclusions. The data used at this writing are 2019 general scholarship data, GPA data, and organizational active information data. The attributes used are parental income, GPA, scholarships, qualification and non-qualification, and active organizational information. The caption attribute qualification and non-qualification is used as a label. At this writing the authors get an accuracy of 72.62%..
Advanced Development of a Prayer Schedule Bot Application on Telegram Using PHP Sofran Bahrurozi; Asroni Asroni; Cahya Damarjati
Emerging Information Science and Technology Vol 1, No 4: November 2020
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v1i4.16596

Abstract

A bot is a web robot or an assistant with computer intelligence. The usefulness of a bot is very much starting from the web, messenger, and others. One application possessing a provider to make a bot is a Telegram. The development of technology, such as social media applications, has made them prevalent for the public, including most Muslims. Sometimes, people will be negligent in worshiping when using the application. Therefore, creating a prayer schedule bot is necessary to prevent people from doing so. A framework creation aimed to facilitate the stages of making a bot using a PHP programming language. The bot-making results could be utilized in various countries with the calculation method found in a bot, providing a preference for users. Telegram bot is preferred for smartphone users wanting storage efficiency and having an internet connection. In contrast, the conventional prayer scheduler application does not care much about the storage taken and does not have an internet connection.
Integration and Geographic Visualization of TKA-TPA Data Using Mapbox Bhaskoro Wicaksono; Asroni Asroni; Asep Setiawan
Emerging Information Science and Technology Vol 1, No 4: November 2020
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v1i4.16597

Abstract

TKA-TPA data management is performed conventionally and inaccurately. Accordingly, it may result in considerable data loss. Data collection for TKA-TPA by BADKO Kasihan Bantul Yogyakarta is still carried out conventionally. Therefore, this study supports BADKO TKA-TPA in data management, data reporting, data mapping, and data publication. A Web Geographic Information System (GIS) was created using the CodeIgniter framework with the Hypertext Preprocessor (PHP) programming language, MapBox on the Maps API Service, MySQL database, and the SDLC with the prototype method. The study result is a web-based GIS application. This GIS application has been successfully built and can be used by BADKO TKA-TPA Kasihan Bantul Yogyakarta for its data management and mapping system.
Prediction of Student Study Period Based on Admission Pathways Using Support Vector Machine Algorithm Cut Maya Putri Audilla; Slamet Riyadi; Asroni Asroni
Emerging Information Science and Technology Vol 1, No 4: November 2020
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v1i4.16598

Abstract

In Indonesia, the quality of a university is measured based on the accreditation by BAN-PT (National Accreditation Board for Higher Education). BAN-PT possesses several main standards in measuring the quality of a university, one of which is students and graduates. The accuracy of the student study period is a crucial issue because it is the basis for the effectiveness of a university. Prediction is a process of systematically estimating something most likely to happen in the future based on past and present information to minimize the error (difference between something that happens and the forecast results). One technique used to make predictions is data mining. Universitas Muhammadiyah Yogyakarta (UMY), as one of the best private universities in Indonesia, must maintain the quality of its students. Student admission at UMY is an internal selection carried out through several methods: student achievement and academic ability tests. The Support Vector Machine (SVM) method is part of the prediction method. Analysis of the SVM prediction utilized the historical data from alumni of the Faculty of Law of UMY in the graduation year of 2015-2019. The application of SVM has provided better accuracy, precision, and recall results. The best kernel accuracy level was the SVM RBF kernel with an optimum C value of 10 and a gamma value of 0.4 with an accuracy of 96.00%.

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