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Journal : Emerging Information Science and Technology

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.
Ajax Based Exam Engine with Tagging System to Improve Learning Asroni Asroni; Minhajuddin K. Abdurrahim; Cahya Damarjati
Emerging Information Science and Technology Vol 1, No 1: February 2020
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (459.652 KB) | DOI: 10.18196/eist.113

Abstract

In this paper, we propose exam engine software with tagging system to help students’ study. With this tagging system, they can analyze their subject learning through exam they have done from time to time. When the students see their reports, the students will decide which subjects are low in grade and should be re-studied. We use AJAX technology to enrich the user experience of this exam engine. After we test all feature with unit testing, this exam engine is proven to runs well and do benefits for students.
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.
Applying the Naive Bayes Algorithm to Predict the Student Final Grade Ronald Adrian; Muhammad Aldi Joko Satria Perdana; Asroni Asroni; Slamet Riyadi
Emerging Information Science and Technology Vol 1, No 2: May 2020
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (749.771 KB) | DOI: 10.18196/eist.127

Abstract

The teaching and learning process of the Faculty of Engineering of Universitas Muhammadiyah Yogyakarta has used e-learning intensively. One of the benchmarks in determining students’ final grade is to take the values in e-learning. This study aims to predict students’ final grades by utilizing the data mining process and the Naive Bayes algorithm. This study provides students and lecturers information to enhance the teaching and learning process to improve students’ final grades and maintain satisfactory final grades until the lecture is complete. The research began with the literature study, data collection, data selection, data cleaning, data transformation and implementation with rapidminer and conclusion drawing. Based on the prediction of students’ final grades, one course obtained many unsatisfactory grades with an accuracy rate of 93.75%. Thus, the higher the accuracy value, the closer the predicted final value to the actual value. 
The Development of 3D Survival Simulation Game for Identifying Safe Food and Water in Borneo Forest Yuda Fatah Kurniawan; Reza Giga Isnanda; Asroni Asroni
Emerging Information Science and Technology Vol 1, No 1: February 2020
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (551.704 KB) | DOI: 10.18196/eist.111

Abstract

For adventures who like to explore the forest with diverse type of flora, such as Borneo forest, being lost and have limited supply of food and water become one of the biggest threats for survival. Therefore, it is important to know how to identify food and water that is safe for consumption. Unfortunately, the learning media for survival skills are still heavy on verbal approach, so there is a need for a more practical and visual learning media. To overcome the problem, this research was aimed to develop a survival simulation game that teach the player how to identify safe food and water in Borneo forest. The game was developed in six steps based on Luther’s steps of authoring multimedia. At the end of the development process, the feasibility of the game as learning media is tested using pre-test and post-test method. Statistical analysis using paired t-test showed that the post-test result (M=77.33, SD=5.37) was significantly higher than the pre-test result (M=56.67, SD=8.24) ); t(29)=18.49, p 0.001. This indicates that the game is feasible in teaching the knowledge to the player. In the future, this game can be an alternative and practical solution for teaching survival skill.
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%.
Web-Based Data Information System for Students and Teachers at Al-Qur’an Education Parks in Kasihan, Bantul Teuku Syauqi Maulana; Haris Setyawan; Asroni Asroni
Emerging Information Science and Technology Vol 2, No 1: May 2021
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v2i1.16870

Abstract

Al-Qur’an Kindergarten (TKA) and Al-Qur’an Education Park (TPA) are non-formal religious education institutions emphasizing studying Islamic values. The development of society necessitates institutions that hold TKA/TPA-related information promptly and correctly. Currently, technology is required to aid an institution in maintaining data and providing TKA/TPA-related information. The data information system aims to provide data for the TKA/TPA coordination agency and ensure the implementation of the administrative order to assure the operational and development sustainability of the IT-based TKA/TPA operating regions. This research intends to develop a web-based information system that can handle the data of students and teachers to reduce the number of errors due to manual data management. A web-based application system for student and teacher data information in TPA in Kasihan was developed utilizing the CodeIgniter framework, the Hypertext Preprocessor (PHP) programming language, the MySQL database, the SDLC method, and the Prototype model. Due to its superiority, the website was selected as the application’s foundation since it is lightweight and could be accessed rapidly using a web browser and an internet or intranet connection to the server. This study has produced a web-based application constructed successfully and could be utilized as a data information system for TPA students and teachers in Bantul.