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All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) TEKNIK INFORMATIKA Jurnal Informatika Dinamik Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmu Komputer dan Informasi AMIKOM ICT AWARD 2010 Techno.Com: Jurnal Teknologi Informasi Jurnal Simetris Jurnal Buana Informatika Jurnal Sarjana Teknik Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Dinamika Informatika CommIT (Communication & Information Technology) Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Jurnal technoscientia Jurnal Teknologi Jurnal Pseudocode Jurnal Teknologi Informasi dan Ilmu Komputer Telematika Jurnal Edukasi dan Penelitian Informatika (JEPIN) Techno (Jurnal Fakultas Teknik, Universitas Muhammadiyah Purwokerto) JUITA : Jurnal Informatika Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) Seminar Nasional Informatika (SEMNASIF) CESS (Journal of Computer Engineering, System and Science) Proceeding SENDI_U Jurnal IPTEK-KOM (Jurnal Ilmu Pengetahuan dan Teknologi Komunikasi) Jurnal Inspiration KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Proceeding of the Electrical Engineering Computer Science and Informatics PROtek : Jurnal Ilmiah Teknik Elektro Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Creative Information Technology Journal SISFOTENIKA IJCIT (Indonesian Journal on Computer and Information Technology) Jurnal Ilmiah Universitas Batanghari Jambi INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JIKO (Jurnal Informatika dan Komputer) JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Pilar Nusa Mandiri Journal of Electrical Technology Syntax Literate: Jurnal Ilmiah Indonesia Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control CogITo Smart Journal InComTech: Jurnal Telekomunikasi dan Komputer Insect (Informatics and Security) : Jurnal Teknik Informatika Jurnal Eksplora Informatika JITK (Jurnal Ilmu Pengetahuan dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Komtika (Komputasi dan Informatika) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Informatika Universitas Pamulang Applied Information System and Management Jurnal Sinergitas PkM & CSR Jurnal Sisfokom (Sistem Informasi dan Komputer) ILKOM Jurnal Ilmiah RESEARCH : Computer, Information System & Technology Management INTECOMS: Journal of Information Technology and Computer Science JurTI (JURNAL TEKNOLOGI INFORMASI) Angkasa: Jurnal Ilmiah Bidang Teknologi Jiko (Jurnal Informatika dan komputer) CARADDE: Jurnal Pengabdian Kepada Masyarakat CYBERNETICS Digital Zone: Jurnal Teknologi Informasi dan Komunikasi JURIKOM (Jurnal Riset Komputer) Journal on Education JURTEKSI Jurnal Informasi dan Komputer Multitek Indonesia : Jurnal Ilmiah Jurnal Manajemen Informatika Jambura Journal of Informatics JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) EXPLORE ComTech: Computer, Mathematics and Engineering Applications CSRID (Computer Science Research and Its Development Journal) Jurnal Ilmiah Sinus Informasi Interaktif Majalah Ilmiah Bahari Jogja CCIT (Creative Communication and Innovative Technology) Journal EDUMATIC: Jurnal Pendidikan Informatika Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika TAFAQQUH: Jurnal Hukum Ekonomi Syariah Dan Ahwal Syahsiyah Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Technologia: Jurnal Ilmiah JURNAL TAHURI SENSITEK E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi Aisyah Journal of Informatics and Electrical Engineering Jurnal Manajemen Informatika dan Sistem Informasi Journal of Information Systems and Informatics TAJDID KURVATEK Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Jurnal Tecnoscienza Respati Jurnal Teknika IT (INFORMATIC TECHNIQUE) JOURNAL JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Journal of Intelligent Decision Support System (IDSS) G-Tech : Jurnal Teknologi Terapan International Journal of Advances in Data and Information Systems Jurnal Sistem Komputer dan Informatika (JSON) Journal of Innovation Information Technology and Application (JINITA) Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat Bulletin of Computer Science and Electrical Engineering (BCSEE) Infotek : Jurnal Informatika dan Teknologi jurnal syntax admiration Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) TEPIAN Infokes : Jurnal Ilmiah Rekam Medis dan Informasi Kesehatan JURNAL TEKNOLOGI TECHNOSCIENTIA Jurnal Teknik Informatika (JUTIF) Jurnal Teknimedia: Teknologi Informasi dan Multimedia JNANALOKA Journal of Electrical Engineering and Computer (JEECOM) Journal of Applied Data Sciences Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Mitra Mahajana: Jurnal Pengabdian Masyarakat Journal of Applied Computer Science and Technology (JACOST) Jurnal Pendidikan dan Teknologi Indonesia International Journal of Computer and Information System (IJCIS) Jurnal Informatika dan Teknologi Komputer ( J-ICOM) International Research on Big-data and Computer Technology (IRobot) Bulletin of Computer Science Research INFOSYS (INFORMATION SYSTEM) JOURNAL J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Journal Automation Computer Information System (JACIS) Jurnal Ekonomi dan Teknik Informatika International Journal Artificial Intelligent and Informatics Jurnal Ilmiah IT CIDA : Diseminasi Teknologi Informasi Jurnal Dinamika Informatika (JDI) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Informatika Teknologi dan Sains (Jinteks) Duta.com : Jurnal Ilmiah Teknologi Informasi dan Komunikasi Prisma Sains: Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram EXPLORE Journal of Comprehensive Science Techno SENTRI: Jurnal Riset Ilmiah Indonesian Journal Computer Science (ijcs) Jurnal Educative: Journal of Educational Studies Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer JURNAL TEKNIK INDUSTRI STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Jurnal Pendidikan Indonesia (Japendi) Cerdika: Jurnal Ilmiah Indonesia International Journal of Advanced Science Computing and Engineering Innovative: Journal Of Social Science Research J-Icon : Jurnal Komputer dan Informatika Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) SmartComp Fahma : Jurnal Informatika Komputer, Bisnis dan Manajemen Jurnal Informatika Polinema (JIP) Jurnal Informatika: Jurnal Pengembangan IT Teknomatika: Jurnal Informatika dan Komputer Proceeding of International Conference on Information Science and Technology Innovation (ICoSTEC) Tafaqquh : Jurnal Hukum Ekonomi Syariah dan Ahwal Syahsiyah Explore The Indonesian Journal of Computer Science Scientific Journal of Informatics Jurnal Teknologi KOPEMAS International Journal of Information Engineering and Science At-Tahdzib: Jurnal Studi Islam dan Muamalah semanTIK JESICA Jurnal Sistem Informasi Komputer dan Teknologi Informasi JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Jurnal Komtika (Komputasi dan Informatika)
Ema Utami
Universitas Amikom Yogyakarta
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Enhanced Heart Disease Diagnosis Using Machine Learning Algorithms: A Comparison of Feature Selection Hirmayanti; Ema Utami
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 2 (2025): April 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i2.6175

Abstract

Heart disease or cardiovascular disease is one of the leading causes of death in the world. Based on WHO data, in 2019, as many as 17.9 million people died from cardiovascular disease. If early prevention is not carried out immediately, of course, the victims will increase every year. Therefore, with the increasingly rapid development of technology, especially in the health sector, it is hoped that it can help medical personnel in treating patients suffering from various diseases, especially heart disease. So in this study, it will be more focused on the selection of relevant features or attributes to increase the accuracy value of the Machine Learning algorithm. The algorithms used include Random Forest and SVM. Meanwhile, for feature selection, several feature selection techniques are used, including information gain (IG), Chi-square (Chi2) and correlation feature selection (CFS). The use of these three techniques aims to obtain the main features so that they can minimize irrelevant features that can slow down the machine process. Based on the results of the experiment with a comparison of 70:30, it shows that CFS-SVM is superior by using nine features, which obtain the highest accuracy of 92.19%, while CFS-RF obtains the best value with eight features of 91.88%. By using feature selection and hyperparameter techniques, SVM obtained an increase of 10.88%, and RF obtained an increase of 9.47%. Based on the performance of the model using the selected relevant features, it shows that the proposed CFS-SVM shows good and efficient performance in diagnosing heart disease.
A Comparative Study of EmberGen and Blender in Fire Explosion Simulations Arya Luthfi Mahadika; Ema Utami
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 2 (2025): MEY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v14i2.2335

Abstract

The advancement of visual effects (VFX) technology has intensified the need for efficient fire explosion simulations across film, gaming, and real-time applications. This study investigates and compares the performance of two prominent simulation tools—EmberGen and Blender—by focusing on processing time efficiency and simulation quality. The research specifically evaluates five critical simulation aspects: fire particle generation, smoke behavior, turbulence effects, light dispersion, and final rendering (finishing). A total of five professional VFX artists conducted five separate tests using each software, generating a comprehensive dataset for analysis. Results show that EmberGen achieves a 29.91% overall improvement in simulation speed compared to Blender, with significant gains in fire particle generation (38.5%), smoke simulation (42.3%), turbulence effects (15.7%), light dispersion (8.9%), and finishing (11.6%). These findings indicate that EmberGen is highly effective for real-time or rapid-turnaround projects, while Blender remains advantageous for detailed, high-fidelity simulations in cinematic contexts. The study concludes that software selection should be driven by project-specific demands, where EmberGen supports time-sensitive production workflows and Blender offers greater artistic control. This research underscores the critical need for aligning simulation tools with both creative goals and production efficiency, contributing to decision-making in VFX, animation pipelines, and educational training environments within the information systems and digital content domains.
Comparative analysis of YOLOv8 techniques: OpenCV and coordinate attention weighting for distance perception in blind navigation systems Utami, Ema; Syahrudin, Erwin; Hartanto, Anggit Dwi
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i3.pp3267-3278

Abstract

Blindness is a very important issue to consider in research aimed at assisting vision. This condition requires further study to provide solutions for the blind. This study evaluates and compares the effectiveness of the you only look once v8 (YOLOv8) model integrated with OpenCV and the coordinate attention weighting (CAW) technique for distance estimation in a blind navigation system. Initially, YOLOv8 integrated with OpenCV produced less than optimal results, prompting further improvement efforts to surpass the performance of CAW. The goal is to enhance the accuracy and efficiency of distance perception without the need for additional sensors. The materials used include a variety of datasets annotated with distance information to train and evaluate the model. The methods employed include integrating YOLOv8 with OpenCV for baseline comparison and applying CAW to improve distance perception through enhanced feature attention. The results show that YOLOv8+OpenCV Improved achieves the lowest mean squared error (MSE) across the entire distance range: 0-1 m (0.44), 1-2 m (0.50), 2-3 m (0.58), 3-4 m (0.64), and 4-5 m (0.71). YOLOv8+CAW also outperforms YOLOv8+OpenCV original, demonstrating a notable enhancement in accuracy. The model achieves a detection accuracy of 95.7%, showcasing the effectiveness of computer vision techniques in supporting blind navigation systems, offering precise distance estimation capabilities and reducing the reliance on external sensors. The implications include improved real-time performance and accessibility for the blind, paving the way for more efficient and reliable navigation assistance technologies.
Perbandingan Algoritma Naïve Bayes dan K-Nearest Neighbor dalam Menentukan Kriteria Masyarakat Miskin Santoso, Arif; Utami, Ema; Hartanto, Anggit Dwi
Jurnal Informa : Jurnal Penelitian dan Pengabdian Masyarakat Vol 8 No 1 (2022): Juni
Publisher : Politeknik Indonusa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46808/informa.v8i1.211

Abstract

Mewabahnya Virus Covid-19 memberikan dampak yang sangat besar dibidang ekonomi. Melemahnya ekonomi masyarakat menjadi permasalahan serius yang sangat perlu segera diatasi. Dalam upaya pemulihan ekonomi, pemerintah mengeluarkan kebijakan-kebijakan untuk pengentasan ekonomi antara lain penyaluran BLT. Akan tetapi kebijakan tersebut justru menimbulkan masalah baru yaitu penyaluran yang tidak tepat sasaran. Hal ini menibulkan gejolak dimasyarakat. Penelitian ini bertujuan untuk mengklasifikasikan data sesuai dengan kriteria dan memperoleh hasil terbaik dua metode yang akan digunakan. Penlitian ini menggunakan dua algoritma Naïve Bayes dan K-Nearest Neighbor dengan data yang diperoleh dari Data terpadu kesejahteraan Sosial (DTKS) dengan dua variabel yaitu mampu dan miskin. Hasil klasifikasi dengan dua algoritma Naïve Bayes dan K-Nearset Neighbor diperoleh hasil masing-masing 72.64% dan 95.40% dengan nilai AUC 0.836 dan 0.877. Berdasarkan nilai AUC yang diperoleh kedua algoritma tingkat akurasi termasuk good classification. Algoritma K-Nearset Neighbir lebih baik dalam klasifikasi masyarakat miskin dibandingkan algoritma Naïve Bayes dengan akurasi 95.40% dan nilai AUC 0.877.
Systematic Literature Review untuk Identifikasi Metode Evaluasi Website Layanan Pendidikan di Indonesia Sutanto, Nur Hamid; Utami, Ema; Rismayani, Rismayani
Jurnal Ilmiah IT CIDA Vol 7 No 1: Juni 2021
Publisher : STMIK AMIKOM Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (589.728 KB) | DOI: 10.55635/jic.v7i1.133

Abstract

Website menjadi suatu kebutuhan utama dari lembaga, instansi, atau perusahaan baik yang berorientasi pada profit maupun non-profit. Salah satunya adalah penyelenggaran Pendidikan tinggi di Indonesia. Website yang menjadi suatu alternatif dan solusi dalam penyampaian profil saat awal kehadirannya, berkembang menjadi pusat layanan yang mampu menjembatani perubahan dari layanan langsung melalui tatap muka berubah menjadi layanan berbasis platform yang dapat dilakukan secara online. Penelitian ini bertujuan untuk mengidentifikasi metode untuk mengevaluasi dan mengukur kualitas website layanan Pendidikan dari penilaian kepuasan penggunanya. Metode Systematic Literature Review (SLR) digunakan dalam penelitian ini. Peneliti menggunakan metode SLR untuk melakukan identifikasi, mengkaji, dan mengevaluasi penelitian yang ada dengan bidang topik yang fokus dan menarik, dengan menyajikan pertanyaan penelitian yang relevan. Dengan menggunakan Metode SLR peneliti dapat melakukan review dan identifikasi terhadap jurnal secara sistematis, dengan mengikuti langkah-langkah yang telah ditentukan. Hasil penelitian menunjukkan bahwa evaluasi pengukuran implementasi layanan sistem informasi berbasis website pendidikan adalah menggunakan metode webqual 4,0 yang berfokus pada pengukuran kepuasan dari penilaian pengguna berdasarkan pada tiga aspek area yaitu usability (kemudahan pengguna), information quality (kualitas informasi), dan service interaction quality (interaksi layanan) sehingga dapat menghasilkan rekomendasi pengembangan dan perbaikan dalam melakukan evaluasi dan pengembangan serta perbaikan terkait penggunaan website layanan pendidikan.
Simple Selection Index (SSI) Method in Electric Vehicle Selection for Logistics Companies Bisono, Hadi Hikmadyo; Utami, Ema
Sistemasi: Jurnal Sistem Informasi Vol 14, No 5 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i5.5434

Abstract

The rapid development of electric vehicles (EVs) has encouraged various industrial sectors, including logistics, to transition from fossil fuel-based vehicles to more environmentally friendly solutions. While EVs offer advantages such as energy efficiency, reduced carbon emissions, and lower operating costs, selecting the right electric vehicle for a logistics company is not a straightforward task. The main challenge lies in the wide variety of available models, each with different technical and operational specifications. This complexity increases as companies must consider multiple criteria such as price, payload capacity, vehicle width, battery capacity, and cargo volume. Therefore, a systematic approach is needed to support decision-making. One commonly used approach is the Multi-Criteria Decision-Making (MCDM) method. This study introduces the Simple Selection Index (SSI) method, a newly developed MCDM approach designed as a simplified version of the Preference Selection Index (PSI) method. The novelty of SSI lies in its ability to eliminate complex steps such as the calculation of preference variation values and preference deviation scores, making the ranking process more concise and easier to apply—without compromising the accuracy of the results. The study aims to evaluate the performance of the SSI method in selecting the most suitable electric vehicle by directly comparing its results with those of the PSI method, using a dataset comprising four vehicle alternatives and five key criteria: price, payload, width, battery capacity, and cargo volume. The findings show that the SSI method produces an identical ranking to the PSI method, with EV-4 as the top recommendation and EV-1 as the second-best alternative. With its more efficient process, the SSI method holds strong potential for application in fast and straightforward multi-criteria decision-making scenarios.
PENINGKATAN RESOLUSI VIDEO MUSIK LAWAS INDONESIA MENGGUNAKAN REAL ESRGAN X4PLUS Alfansani, Abdul Rauf; Utami, Ema; Ariatmanto, Dhani
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 7 No 2 (2025): EDISI 24
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v7i2.6146

Abstract

Video musik Indonesia lawas yang diproduksi pada era VCD umumnya memiliki kualitas visual rendah dan degradasi artefak yang signifikan. Penelitian ini mengevaluasi efektivitas model Real?ESRGAN?X4plus dalam meningkatkan resolusi video-video tersebut menggunakan pendekatan super?resolusi berbasis pembelajaran mendalam. Eksperimen dilakukan pada lima video dengan resolusi awal 480p yang ditingkatkan menjadi 1920p, dengan variasi parameter denoise_strength dari 0,0 hingga 1,0 dan tile_size dari 64 hingga 256. Model ini dibandingkan dengan metode interpolasi bicubic dan ESRGAN publik sebagai baseline. Evaluasi dilakukan menggunakan metrik PSNR dan SSIM, serta uji statistik paired t?test. Hasil menunjukkan bahwa konfigurasi optimal adalah denoise_strength = 0.0 dan tile_size = 256, menghasilkan PSNR tertinggi (35,10 dB) dan SSIM terbaik (0,956). Dibanding baseline, Real?ESRGAN memberikan peningkatan kualitas yang signifikan baik secara obyektif maupun visual. Model ini juga menunjukkan potensi dalam mempertahankan detail halus dan konsistensi temporal antar frame. Temuan ini mendukung pemanfaatan Real?ESRGAN sebagai solusi restorasi video budaya Indonesia, serta membuka peluang untuk pengembangan lanjut berbasis VSR temporal.
Hybrid Fuzzy Logic, Genetic Algorithms, and Artificial Neural Networks for Cattle Body Weight Prediction Anjar Setiawan; Ema Utami; Dhani Ariatmanto
Jurnal ilmiah Sistem Informasi dan Ilmu Komputer Vol. 5 No. 2 (2025): Juli : Jurnal ilmiah Sistem Informasi dan Ilmu Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juisik.v5i2.1319

Abstract

Cattle serve as the primary means of meat and milk production in numerous regions across the globe. Enhancing efficiency and productivity in cow ranching can provide significant economic consequences. The cattle industry is significant as it enables the estimation of cow weight, directly influencing beef and milk quality. This study aims to enhance the accuracy of cattle weight estimation by minimizing the Mean Squared Error (MSE) values. The integration of artificial neural network (ANN), fuzzy logic (FL), and genetic algorithm (GA) techniques is a promising artificial intelligence tool for predicting and modeling cattle weight in livestock weight prediction systems. The cow weight forecast yielded a Mean Squared Error (MSE) value of 10.9 kg, which is the best result. The results demonstrate the progress made in agriculture using advanced technologies. They offer a detailed examination of how artificial intelligence, fuzzy logic, and evolutionary techniques can be combined to address the many difficulties associated with estimating cattle body weight.
Prediksi Harga Bitcoin Menggunakan Model Hibrida Transformer Dan Long Short Term Memory Irawan, Rio; Utami, Ema
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 9 (2025): JPTI - September 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.1091

Abstract

Peramalan harga Bitcoin merupakan tantangan signifikan akibat fluktuasi pasar yang tinggi, di mana model deret waktu konvensional seringkali gagal menangkap dependensi data jangka pendek dan panjang secara bersamaan. Untuk mengatasi masalah tersebut, penelitian ini bertujuan mengembangkan dan mengevaluasi model deep learning hibrida guna meningkatkan presisi peramalan harga Bitcoin. Model yang diusulkan mengintegrasikan arsitektur Long Short-Term Memory (LSTM), yang andal dalam memproses data sekuensial, dengan mekanisme atensi pada Transformer yang mampu mengidentifikasi hubungan data yang relevan. Metode penelitian mencakup penggunaan data harga historis Bitcoin yang telah melalui tahap pra-pemrosesan dan normalisasi. Arsitektur model terdiri dari dua lapisan LSTM (30 unit), diikuti oleh lapisan Transformer dengan Multi-Head Attention (satu head, dimensi kunci empat), dan diakhiri dengan lapisan Global Average Pooling. Pelatihan model dilakukan menggunakan konfigurasi optimal selama 10 epoch dengan ukuran batch 64. Hasil evaluasi menunjukkan kinerja prediksi yang sangat akurat, dibuktikan dengan nilai Mean Absolute Percentage Error (MAPE) sebesar 0,000695 dan R-squared (R²) 0,99999. Temuan ini menegaskan bahwa pendekatan hibrida efektif dalam menangkap pola kompleks pada data harga Bitcoin, sehingga menawarkan alat yang lebih kuat untuk analisis keuangan di pasar cryptocurrency.
DEGREE: Development and Validation of a User Experience Model for Digital Educational Games Using Cronbach’s Alpha and Fuzzy Logic Kurniawan, Mei Parwanto; Suyanto, M.; Utami, Ema; Kusrini, Kusrini
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.4942

Abstract

The rapid growth of digital educational games demands an evaluation model that accurately captures user experience and adopts a human-centred approach. This study introduces DEGREE (Digital Educational Game Review and Evaluation Engine), an enhanced model extending MEEGA+ by incorporating two previously underrepresented dimensions: Control and Feedback. Using a quantitative approach, questionnaires were distributed to high school students who actively use Minecraft and Duolingo, yielding 4800 responses.Reliability analysis via Cronbach’s Alpha revealed that the Player Experience + Control combination achieved the highest score (α = 0.914), while the inclusion of Feedback reduced reliability (α = 0.864), leading to its exclusion in the final model. The DEGREE model consists of two core domains: Usability (Aesthetics, Learnability, Operability, Accessibility) and Player Experience (Focused Attention, Fun, Challenge, Social Interaction, Confidence, Relevance, Satisfaction, Perceived Learning, User Error Protection, Control). Evaluation scores were calculated using the Fuzzy Weighted Average (FWA) method and Mean of Maximum (MoM) defuzzification. The Control dimension emerged as the most influential (0.2735), followed by Fun (0.2664) and Satisfaction (0.2516), highlighting the significance of user agency in digital learning environments. The DEGREE model offers a statistically robust and user-oriented framework for evaluating educational games, delivering actionable insights for developers and educators to design more effective and engaging digital learning experiences. This study contributes a new validated and generalizable evaluation framework that strengthens the theoretical foundation of user experience assessment in educational game design.
Co-Authors , Anggit Dwi Hartanto A.A. 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