Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
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This Author published in this journals
All Journal CESS (Journal of Computer Engineering, System and Science) Engineering, Mathematics and Computer Science Journal (EMACS)
Adam Fahsyah Nurzaman
Bina Nusantara University
Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering Industrial & Manufacturing Engineering Mathematics

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Dashboard System for Predicting Student Practicum Performance Using the Data Mining Method Adam Fahsyah Nurzaman; Riyanto Jayadi
CESS (Journal of Computer Engineering, System and Science) Vol 7, No 2 (2022): July 2022
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v7i2.35394

Abstract

One of the factors that can influence the success of an educational institution is the coveted quality of students. To be able to see the quality of students can be seen from the graduation obtained. One method that can be used to see the percentage of student graduation obtained is data mining. This research was conducted to examine the data assessment process using data mining methods as well as data visualization so that the information generated is better by using the dashboard. Decision tree method was chosen because the results obtained using data sources that create the highest accuracy. Out of this research, it is found that the dashboard which was developed to visualize the data to become more mature information and data assessment using data mining methods has succeeded in making stakeholders get better information and also helps in making better business decisions.
Bayesian Accelerated Failure Time Model for Risk Pregnancy Detection Dennis Alexander; Sarini Abdullah; Adam Fahsyah Nurzaman
Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 5 No. 3 (2023): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v5i3.10540

Abstract

Preeclampsia (PE) also known as a hypertension during third trisemester of pregnancy. PE, is one of the most feared complications of pregnancy because it can potentially become serious complications in the future, including mother and fetus’s death. The goal of this study is other than to have a bettter undestanding about risk factor in pregnancy by modelling the relationship between several factors and the time until deliveries under the PE condition. Data on 924 patients at obstetric and gynecology department in Jakarta were used in the analysis. Accelerated Failure Time (AFT) model was proposed to indentify some risk factors that influenced the condition. Model parameters were estimated using Bayesian method. Due to imbalance data, undersampling method will be used as a pre-procesing stage. Ratio between PE and non-PE data will be 60:40. Flat prior and posterior sample will be used using MCMC simulation with 12,000 iterations (including 2,000 iterations as a burnin stage) to get a convergen result. The iteration was repeated for 100 times so that the chosen data from undersampling was not error and biased. A consistent result for credible interval of the mean result was considered as the factors that affect PE condition consistently. From this study, there are two factors that have consistent Credible Interval result, Body Mass Index (BMI) and Mean Arterial Pressure (MAP).
Co-Authors Dennis Alexander Riyanto Jayadi Sarini Abdullah