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All Journal JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi)
Silvi Agustanti Bambang
Universitas AMIKOM Yogyakarta
Computer Science & IT Education

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Kombinasi Algoritma Sampling dengan Algoritma Klasifikasi untuk Meningkatkan Performa Klasifikasi Dataset Imbalance Gagah Gumelar; Norlaila2; Quratul Ain; Riza Marsuciati; Silvi Agustanti Bambang; Andi Sunyoto; M. Syukri Mustafa
Prosiding SISFOTEK Vol 5 No 1 (2021): SISFOTEK V 2021
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (368.284 KB)

Abstract

A class to be imbalanced when there is a class that has more data than other classes. A comparison between minority classes and the majority class is called Imbalance Ratio (IR). The greater the difference between the minority class and the majority class the value of the Imbalance Ratio (IR) is getting larger. Dataset imbalance in data mining is a serious problem. The application of the classification algorithm regardless of class balance resulted in a good prediction for the majority class and a neglected minority class. Therefore, in this research, the SMOTE algorithm was applied to balance the dataset. The study used 4 datasets with different Imbalance Ratio and used classification algorithms, C45, Naïve Bayes, K-NN, and SVM. Then compared before and after using SMOTE. The research results that have been done accuracy value and value G-mean Naïve Bayes algorithm is consistent with its performance at each level of imbalance ratio, before the implementation has no good performance, whereas after the implemented SMOTE algorithm Naïve Bayes has a consistent increase in accuracy. So it can be concluded that the combination SMOTE + Naïve Bayes most effectively used in the imbalance dataset with different levels in the scheme of 10 fold cross validation and 80% data testing tested as much as 50 times.
EVALUATION OF THE APPLICATION TECHNOLOGY ACCEPTANCE MODEL 3 IN DIGITAL LIBRARY SYSTEM Silvi Agustanti Bambang; Wing Wahyu Winarno; Asro Nasiri
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 3 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i3.6432

Abstract

This study aims to analyze the acceptance of the digital library system at the University of Muhammadiyah Palangkaraya using the Technology Acceptance Model (TAM) approach. Primary data were collected through an online questionnaire distributed to over 125 respondents, with 117 completing the survey. Data analysis was conducted using Structural Equation Modeling (SEM) with SmartPLS software, following the previously outlined SEM analysis stages. Measurement model evaluation included convergent validity, discriminant validity, and reliability using the Partial Least Squares (PLS) Algorithm. The results revealed that Behavioral Intention* (BI) does not significantly influence Use Behavior (UB). In contrast, Perceived Usefulness (PU) significantly impacts BI. Additionally, Perceived Ease of Use (PEOU) significantly affects both PU and BI. The factor Image (IMG) also contributes to PU, while Job Relevance (REL) influences PU moderated by Output Quality (OUT). Result Demonstrability (RES) affects PU, and Computer Self-Efficacy (CSE) impacts PEOU. Factors such as Computer Playfulness (CPLAY), Perceived Enjoyment (JOY), and Objective Usability (OU) also affect PEOU, with their effects moderated by Experience (EXP). This study provides insights into the factors influencing the acceptance of digital library systems and can serve as a foundation for future system improvements.
Co-Authors Andi Sunyoto Asro Nasiri Gagah Gumelar M. Syukri Mustafa Norlaila2 Quratul Ain Riza Marsuciati