Article Per Year (5 Year)
p-Index From 2021 - 2026
1.671
P-Index
This Author published in this journals
All Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING EDUMATIC: Jurnal Pendidikan Informatika Journal of Information Systems and Informatics Infotek : Jurnal Informatika dan Teknologi Jurnal Pendidikan, Sains, Geologi, dan Geofisika (GeoScienceEd Journal) Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Teknologi Informasi untuk Masyarakat (Jurnal Teknokrat) Pekayunan
Zaenul Amri
Program Studi Pendidikan Informatika, Universitas Hamzanwadi
Agriculture, Biological Sciences & Forestry Chemistry Computer Science & IT Control & Systems Engineering Education Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Physics

Published : 13 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : EDUMATIC: Jurnal Pendidikan Informatika

 1 
Analisis Usability Website Universitas Hamzanwadi terhadap Kepuasan Pengguna dengan Menggunakan User Satisfaction Model Amri, Zaenul; Uska, Muhammad Zamroni; Arianti, Baiq Desi Dwi
Jurnal Pendidikan Informatika (EDUMATIC) Vol 2, No 1 (2018): Edumatic : Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The purpose of this study is to find out: (1) the level usability of the hamzanwadi university website for user satisfaction by using the user satisfaction model, (2) model produced by Green and Pearson 2010 with 9 variables measurement including: design credibility, content, interactivity, navigability, responsiveness, download delay, perceived usefulness, perceived ease of use, user satisfaction. This type of research is quantitative by using survey method. The population of this study is all students of Faculty of Teacher Training and Education (FKIP) Hamzanwadi University with the numbers of 3724 students and the numbers of samples in this study were 361 students using cluster sampling technique. Data collection techniques in this study using a questionnaire with likert scale. The technique used to analyze the data is descriptive statistics. The result of this study shows that (1) from 9 variable measurement of usability of website of Hamzanwadi University only 4 variables that stated good and able to fulfill user satisfaction there are, design credibility variable, content, and perceived ease of use with mean value = 11, and interactivity with value mean = 7, (2)  5 other variables are enough and have not able to meet user satisfaction there are, variable navigationability, responsiveness, download delay, perceived usefulness, and user satisfaction with mean value = 10. So it can be concluded that the overall usability of the website of Hamzanwadi University has not can meet user satisfaction.
Analisis Usability Website Universitas Hamzanwadi terhadap Kepuasan Pengguna dengan Menggunakan User Satisfaction Model Zaenul Amri; Muhammad Zamroni Uska; Baiq Desi Dwi Arianti
Jurnal Pendidikan Informatika (EDUMATIC) Vol 2, No 1 (2018): Edumatic : Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v2i1.842

Abstract

The purpose of this study is to find out: (1) the level usability of the hamzanwadi university website for user satisfaction by using the user satisfaction model, (2) model produced by Green and Pearson 2010 with 9 variables measurement including: design credibility, content, interactivity, navigability, responsiveness, download delay, perceived usefulness, perceived ease of use, user satisfaction. This type of research is quantitative by using survey method. The population of this study is all students of Faculty of Teacher Training and Education (FKIP) Hamzanwadi University with the numbers of 3724 students and the numbers of samples in this study were 361 students using cluster sampling technique. Data collection techniques in this study using a questionnaire with likert scale. The technique used to analyze the data is descriptive statistics. The result of this study shows that (1) from 9 variable measurement of usability of website of Hamzanwadi University only 4 variables that stated good and able to fulfill user satisfaction there are, design credibility variable, content, and perceived ease of use with mean value = 11, and interactivity with value mean = 7, (2)  5 other variables are enough and have not able to meet user satisfaction there are, variable navigationability, responsiveness, download delay, perceived usefulness, and user satisfaction with mean value = 10. So it can be concluded that the overall usability of the website of Hamzanwadi University has not can meet user satisfaction.
Prediksi Tingkat Kelulusan Mahasiswa menggunakan Algoritma Naïve Bayes, Decision Tree, ANN, KNN, dan SVM Zaenul Amri; Kusrini Kusrini; Kusnawi Kusnawi
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.v7i2.18620

Abstract

The student graduation rate in all universities can be measured by looking at their study duration, both on time and delayed. Thus, by observing the study duration, it can affect the quality of study programs in universities. The purpose of this research is to apply and compare the Naïve Bayes, Decision Tree, Artificial Neural Network, K-Nearest Neighbor (K-NN), and Support Vector Machine (SVM) algorithms in predicting the graduation rate of students. The dataset in this research consisted of 807 student data from the Faculty of Engineering, Universitas Hamzanwadi. The data analysis technique used was descriptive statistics by applying the knowledge discovery in a database (KDD) method. The testing of the five algorithms was done by optimizing the data using the SMOTEENN technique, with a data split of 80% for training and 20% for testing, using a random state of 42. Our findings show that the Naïve Bayes algorithm had an accuracy of 92.37%, Decision Tree 91.60%, K-NN 96.95%, SVM 93.13%, and ANN 90.84%. Among the five algorithms tested, the K-NN algorithm had the highest accuracy rate of 96.95%. The predicted results tended to indicate delayed graduation influenced by GPA. Therefore, the institution needs to pay more attention to students predicted to be delayed to improve their GPA each semester, thus promoting timely graduation within the expected time frame.
Co-Authors Amir Bagja Baiq Desi Dwi Arianti Fathurrahman, Imam Hendrik Hendrik Khairul Imtihan Kholisho, Yosi Nur Kusnawi Kusnawi Kusrini Kusrini M. Nurul Wathani Muahamd Rodi Muhamad Rodi Muhammad Djamaluddin Muhammad Rodi Nafisah, Khufatun Rusniatun, Siska Yuni Sanusi, M Ujang Saputra, Lalu Rendi Suhartini Uska, Muhammad Zamroni Wirasasmita , Rasyid Hardi Zulkipli