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EDUMATIC: Jurnal Pendidikan Informatika
Published by Universitas Hamzanwadi
ISSN : -     EISSN : 25497472     DOI : 10.29408
Core Subject : Science, Education,
Computer Science & IT Education
EDUMATIC: Jurnal Pendidikan Informatika (e-ISSN: 2549-7472) adalah jurnal ilmiah bidang pendidikan informatika yang diterbitkan oleh Universitas Hamzanwadi dua kali setahun yaitu pada bulan Juni dan Desember. Adapun fokus dan skup jurnal ini adalah (1) Komputer dan Informatika dalam Pendidikan; (2) Model Pembelajaran dan Model TIK; (3) Pengembangan Media Pembelajaran Berbasis Teknologi Informatika; (4) Interaksi Manusia dan Komputer; (5) Sistem Informasi dan Teknologi Informasi.
Arjuna Subject : -
Articles 439 Documents
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Media Informasi untuk Perawatan Kucing berbasis Android Rasyid Hardi Wirasasmita; Muhamamad Zamroni Uska; Jamaluddin Jamaluddin; GB Deni Rahman
Jurnal Pendidikan Informatika (EDUMATIC) Vol 7 No 2 (2023): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v7i2.23863

Abstract

The use of information technology so far is not only in the field of education, but can also be utilized in the health sector, such as cat care. Raising a cat has different needs and ways of caring for other animals such as feeding, drinking, shelter, and health. This study aims to produce android-based cat care information media, knowing the feasibility and response of users. This type of research is research and development using the Rapid Application Development (RAD) model which consists of 3 stages, namely: requirements planning, RAD design workshop, and implementation. The subjects in this study amounted to 19 cat owners to find out the user's response. Data collection techniques using questionnaires and data analysis using quantitative descriptive. Our findings show that the application developed is in the form of Android-based cat care information media. The material expert due diligence result is 96.3% (very feasible). Meanwhile, the results of the due diligence of media experts obtained 87% (very feasible). Thus this application is worthy of being used as an android-based cat care information media. So that this application can help some parties or cat owners to take care of their cats without having to go to a veterinary clinic.
Aplikasi Pengamanan Data Karyawan menggunakan Algoritma Advanced Encryption Standard dan Cloud Computing berbasis Mobile Adi Kannatasik; Moh. Ali Romli
Jurnal Pendidikan Informatika (EDUMATIC) Vol 7 No 2 (2023): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v7i2.23948

Abstract

Documents are valuable assets that often contain important information, including employee personal data, and are vulnerable to security threats such as theft and alteration by unauthorized parties. This research aims to develop an Android-based document security application that combines the Advanced Encryption Standard (AES) algorithm and cloud computing technology. This type of research is developed using the System Development Life Cycle (SDLC) model, which involves requirements analysis, design, coding, and testing. At the needs analysis stage, focus is given to employee data that needs to be secured. System design includes data structure, system structure, and user interface (UI). System design includes use case elements, class diagrams, and application architecture. Coding was done using Flutter as the user interface, Laravel as the backend, and MySQL as the database. System testing uses black box testing. Our test results show that the data security application is successful in carrying out the data encryption and decryption processes. Compared to previous web and desktop-based developments, this application provides a more adaptive solution to high mobility in the work environment. Cloud computing integration provides flexibility in data access, and the use of the Android platform significantly increases user mobility.
Analisis Pengaruh Penggunaan Internet Download Manager pada Load Balancing di Mikrotik Muhammad Wardhani; Muhammad Taufiq Nuruzzaman
Jurnal Pendidikan Informatika (EDUMATIC) Vol 7 No 2 (2023): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v7i2.24295

Abstract

Internet Download Manager (IDM) is one of the popular applications used by users to download various types of files from the internet. Load balancing is a technique used to increase the efficiency of using network resources by distributing data traffic evenly across several connection lines. This research aims to determine the extent to which IDM influences the effectiveness of load balancing as well as the influence of using Internet Download Manager (IDM) in the context of load balancing using the Policy-based Load Balancing (PCC), Equal Cost Multi-Path (ECMP), and Next-Hop Target methods. (NTH) on the MikroTik RB751 device. In this research, we used the PPDiOO method for systematic data collection and Quality of Services (QoS) analysis as a parameter for network data collection techniques. The research subject is the system or user who uses the device, while the research object is the impact of using IDM on load balancing performance. The main independent variable is the use of IDM, while the dependent variable is load balancing performance with different methods. Our findings show that using IDM consistently provides significant improvements in network performance compared to not using IDM.
Sistem Pakar menggunakan Metode Certainty Factor Mendiagnosa Gizi Buruk Balita berbasis Android Rahma Azizah Lubis; Muhammad Dedi Irawan
Jurnal Pendidikan Informatika (EDUMATIC) Vol 7 No 2 (2023): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v7i2.24340

Abstract

Toddlers are a vulnerable age group facing issues such as insufficient nutrition and malnutrition. Every year, malnutrition in toddlers emerges as a significant health issue. Several factors influencing this condition include limited access to nutritious food, a lack of parental understanding, and economic challenges. This research aims to develop an expert system for early detection of malnutrition in toddlers based on Android using the Certainty Factor method. Employing the research and development method and system development using the waterfall model, the analysis involves gathering information through interviews, observations, and literature reviews. Subsequently, the system is designed to utilize the Unified Modeling Language (UML) to provide an overview of the intended application. The implementation phase utilizes the Certainty Factor method, incorporating knowledge from experts and symptom data from diagnosed cases of toddler malnutrition as the foundation. The diagnosis results of malnutrition will be presented clearly to users, indicating the success rate in percentage form. Testing of this expert system demonstrates a high accuracy level of 99%. The results of the system testing align with its functions based on black-box testing. This system can make a significant contribution to early detection efforts for malnutrition in toddlers and reduce the burden of malnutrition in society. 
Analisis Sentimen Review ChatGPT di Play Store menggunakan Support Vector Machine dan K-Nearest Neighbor Pamungkas, Adji Surya; Cahyono, Nuri
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.24114

Abstract

The ChatGPT application for Android was launched on July 25, 2023, and the language model from OpenAI achieved a rating of 4.8 until early 2024. Despite the majority of positive reviews, user reports stating that ChatGPT provides inaccurate answers raise concerns about the reliability of this application. This research aims to compare the models of the Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) algorithms in analyzing the sentiment of ChatGPT application reviews. Utilizing text mining methods to extract information from text, data was collected from Google Play Store reviews using data scraping techniques and analyzed with Support Vector Machine and K-Nearest Neighbor algorithms. Cross-validation with 5 folds and data split using 80% training and 20% testing data were applied to evaluate the performance of both algorithms. The sentiment classification results showed that the Support Vector Machine algorithm achieved an average accuracy of 80%, while K-Nearest Neighbor reached 71%. SVM excels due to its ability to overcome KNN's limitations regarding less relevant features that do not significantly contribute to predictions. The findings of this study are expected to help developers understand and respond to user feedback regarding the reliability of ChatGPT.
Analisis Sentimen Ulasan Aplikasi PosPay untuk Meningkatkan Kepuasan Pengguna dengan Metode K-Nearest Neighbor (KNN) Mustaqim, Kiki; Amaresti, Fatia Amalia; Dewi, Intan Novita
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.24779

Abstract

PT Pos Indonesia has launched a digital pospay service. Users who have a positive experience are more likely to return to application. User perceptions analysis can be known from the Review sentiments. Review sentiments that are classified as positive and negative are really needed by developers to improve services (user satisfaction). The research aims to increase user satisfaction of the PosPay application based on the application's review data. The source of data is a review of the pospay application at Google play store. The method used quantitative study method that is K-Nearest Neighbor (K-NN) that classify objects based on learning data that are closest to the object. Research variable is the word from user commentary that associated with the pospay application services. Application review data in scrapping, preprocessing, splits data (train data and test data). Supervised learning (TF-IDF and K-NN) prepared with python programming provides data visualizing. The research results show that the sentiment of Pospay application users tends to be positive. K-NN classification model produces 91% accuracy, 90% precision and recall by 99%. The key word of positive sentiment is: easy, helpful, transaction. Keyword negative sentiment: balance, pay, login.
Penerapan Algoritma Support Vector Machine untuk Memprediksi Tingkat Partisipasi Pemilu terhadap Kualitas Pendidikan Anggraeni, Anifah Warda; Fitrani, Arif Senja; Eviyanti, Ade
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.24838

Abstract

Elections are a democratic means of choosing leaders. Public participation in elections is important for a healthy democracy. The quality of education influences public participation in elections. Therefore, the government needs to improve the quality of education in the Pasuruan Regency area. This research aims to predict the level of participation in elections on the quality of education in Pasuruan Regency. This research uses the Education sector dataset obtained from BPS data for Pasuruan Regency in 2022 and the level of election participation obtained from the recapitulation of the 2019 election results. Data analysis was carried out in an experimental stage to determine the variables to be predicted (target variables) and the variables used to predict it (predictor variable) using the Support Vector Machine (SVM) algorithm with three kernels, namely linear, rbf, and polynomial. The findings show an accuracy of 88.4% for the linear kernel, 88.5% for the rbf kernel, and 88.5% for the polynomial kernel. The quality of education can influence the level of election participation. This is because high quality education can increase public awareness of the importance of participating in elections.
Perbandingan Pendekatan Computer Science Unplugged dan Plugged-In Learning pada Pembelajaran Informatika Prameswara, Irvan; Pramudita, Dias Aziz
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.25058

Abstract

Currently, informatics learning at Al-Islam Abidin Junior High School in Surakarta is often faced with the challenge of choosing effective and interesting learning methods for students, so that it causes teachers and students to find it difficult to determine which methods are more suitable to be applied in the classroom. There are several kinds of approaches to learning in informatics subject matter, namely by using CS unplugged and plugged-in learning. This study aims to analyze the comparison of CS unplugged and plugged-in learning approaches applied at Al-Islam Abidin Junior High School in Surakarta. The method used in this study is to use a quantitative approach. The participants involved totaled 40 people who would be divided into 2 classes, namely the control class and the experimental class, each class consisting of 20 people. Data collection in this study used pre-test and post-test. The results of pre-test and post-test testing show that learning using computer media (plugged learning) gets higher scores so it can be concluded that the plugged learning method is more suitable for use in informatics subjects. The impact of plugged-in learning method is that students can play and learn using technology, meanwhile unplugged learning makes the student can learn dependence on technology.
Game Edukasi Interaktif Sejarah Kerajaan Hindu-Buddha menggunakan Platform Scratch Perkasa, Rizal Arindra Esa; Wantoro, Jan
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.25161

Abstract

The lack of effectiveness of traditional history learning methods at SMKN 1 Pedan. So, it is necessary to develop educational game learning media using the Scratch application, with the aim of fostering interest in learning and student involvement in learning the history of Hindu-Buddhist kingdoms. This research aims to produce and develop products in the form of learning media with a scratch platform for Hindu-Buddhist History subjects. This type of research is development by building or creating Scratch-based learning media. The method used in research to develop educational game media is Research and Development (R&D). The instruments used are media questionnaires, materials, observations, interviews and literature studies. The research model used is ADDIE with stages of analysis, design, development and implementation, and the data analysis technique used is descriptive statistics. Our findings show that the results of media testing are very feasible. Meanwhile, the response of users of this media in the category is very good. So, this game can be used by students to learn the History of Hindu-Buddhist Kingdoms in grade 10 SMKN 1 Pedan.
Sistem Presensi Pendeteksi Wajah menggunakan Metode Modified Region Convolutional Neural Network dan PCA Talumepa, Renaldi Valentino; Putra, Donny Anggara; Soetanto, Hari
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.25207

Abstract

Attendance is an activity to collect data to find out the number of attendances at an event or activity. In order to increase effectiveness and time efficiency is important, it is necessary to have an artificial intelligence-based presence by means of face detection. This study aims to create a face detection attendance system using modified region convolutional neural network (MR-CNN) and principal component analysis (PCA) methods. This type of research is development research by applying the concept of digital image based on face recognition. This research applies a method in deep learning, namely MR-CNN through camera media to take images and the extraction process using the PCA method to reduce image resolution. Images that include various individuals who want to be recognized are stored and then used as datasets. From the dataset, the MR-CNN model was trained with training data. Our findings are in the form of a web-based facial short-attendance system. Where are the calculation results in this system has an accuracy value of 96.1%, so it can be used well for facial identification, and can be used at SMK Bhakti Anindya.

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