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All Journal Jurnal Teknologi Informasi dan Multimedia Jurnal INFOTEL SainsTech Innovation Journal
Danang Tejo Kumoro
Universitas Qamarul Huda Badaruddin
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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EVALUASI SISTEM INFORMASI PENGGUNAAN E-LEARNING SEBAGAI SISTEM PERKULIAHAN PERGURUAN TINGGI Uswatun Hasanah; Syahroni Hidayat; Danang Tejo Kumoro
JURNAL INFOTEL Vol 12 No 4 (2020): November 2020
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v12i4.475

Abstract

This study aims to evaluate the use of technology to support teaching and learning activities. Lecturers and students have applied e-learning to teach subjects. The purpose of this evaluation is to measure the success of the use of STMIK Bumigora e-learning by using the Technology Acceptance Model (TAM) approach, which is an approach that can explain user behavior towards the use of technology. Evaluation of the use of e-learning is formulated into a model based on the TAM model, while SEM (Structural Equation Modelling) is used for data analysis. Based on the measurement analysis in this study, several factors most influenced the effectiveness of e-learning, namely the usage tutorial for users, ICT facilities related to the Ease of accessing the internet network. Meanwhile, in structural analysis, it was found that attitudes toward the use and perceived usefulness were strongly correlated with real use factors. The actual use is a real condition of the use of e-learning measured by the frequency and duration of time in using the technology, which is influenced by the user's belief in accepting the existence of e-learning in STMIK Bumigora and user beliefs related to the benefits when using it. Therefore, attitudes toward the use and perception of usefulness are the main determining factors in measuring the frequency and duration of e-learning use.
Media Pembelajaran Hewan Penghasil Listrik dengan Pemanfaatan Teknologi Augmented Reality untuk Siswa SMP Miftahul Madani; Hendri Hamzanwadi; Melati Rosanensi; Danang Tejo Kumoro
Jurnal Teknologi Informasi dan Multimedia Vol. 6 No. 1 (2024): May
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v6i1.510

Abstract

Augmented reality technology is a virtual object that can provide information to help users carry out work related to this technology. The learning process applied to students at SMPN 1 Praya Tengah with the theme of introducing electricity-producing animals with a learning method using printed books and verbal explanations using a whiteboard as a learning medium so that students cannot see pictures of electricity-producing animals. This research is aimed at producing more interactive learning media in introducing electricity-producing animals by using augmented re-ality technology at SMPN 1 Praya Tengah to increase interest in learning. The methodology used is the MDLC method which uses 6 stages, namely the concept, design, material collection, manu-facturing, testing and distribution stages which are implemented in learning media. The results obtained are interactive learning media on how to recognize electricity-producing animals using augmented reality which can be run on desktop-based computers. The conclusion obtained from this research is that the application of a learning media application to introduce electrici-ty-producing animals using augmented reality technology for students at SMPN 1 Praya Tengah can help students learn about electricity-producing animals in real time or in the form of 3-dimensional objects and animations. The test results used a test scale, namely a Likert scale with a value of 45.25 which can be categorized as Strongly Agree.
Benchmarking Model Machine Learning untuk Prediksi Data Berdasarkan Akurasi dan Error Valian Yoga Pudya Ardhana; Syahrani Lonang; Danang Tejo Kumoro; M. Dermawan Mulyodiputro
SainsTech Innovation Journal Vol. 8 No. 2 (2025): SIJ VOLUME 8 NOMOR 2 TAHUN 2025
Publisher : LPPM Universitas Qamarul Huda Badaruddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37824/sij.v8i2.2025.1141

Abstract

Perkembangan machine learning mendorong pemanfaatan berbagai model regresi untuk melakukan prediksi data secara akurat dan efisien. Namun, perbedaan karakteristik dataset menyebabkan kinerja setiap model bervariasi, sehingga diperlukan proses benchmarking untuk menentukan model yang paling optimal. Penelitian ini bertujuan untuk membandingkan kinerja beberapa model machine learning dalam tugas prediksi data berbasis regresi tanpa melakukan pengembangan aplikasi. Model yang dievaluasi meliputi Linear Regression, Decision Tree Regression, Random Forest Regression, Support Vector Regression, dan K-Nearest Neighbor Regression. Dataset yang digunakan merupakan dataset publik dengan variabel numerik yang telah melalui tahap praproses data, meliputi pembersihan data, normalisasi, dan pembagian data latih serta data uji. Evaluasi kinerja model dilakukan menggunakan metode K-Fold Cross Validation dengan metrik Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), dan koefisien determinasi (R²). Hasil penelitian menunjukkan bahwa Random Forest Regression memberikan kinerja terbaik dengan nilai error terendah, nilai R² tertinggi, serta stabilitas model yang baik dibandingkan model lainnya. Hasil ini menunjukkan bahwa pendekatan ensemble efektif dalam meningkatkan akurasi dan kemampuan generalisasi model pada tugas prediksi data regresi.
Co-Authors Hendri Hamzanwadi M. Dermawan Mulyodiputro Melati Rosanensi Miftahul Madani Syahrani Lonang Syahroni Hidayat Syahroni Hidayat Uswatun Hasanah Valian Yoga Pudya Ardhana