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All Journal Jurnal Riset Informatika TIERS Information Technology Journal Journal of Information Systems and Technology Research
Dwi Arman Prasetya
UPN Veteran Jawa Timur
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Improving Performance of RNN-Based Models With Genetic Algorithm Optimization For Time Series Data Muhammad Muharrom Al Haromainy; Dwi Arman Prasetya; Anggraini Puspita Sari
TIERS Information Technology Journal Vol. 4 No. 1 (2023)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/tiers.v4i1.4326

Abstract

Stock price data or similar time series data can be used to carry out forecasting processes using past data. The method that can be used is like a neural network, one type of neural network that is used is the Recurrent Neural Network. When using the Recurrent Neural Network (RNN) method, we need to determine the appropriate parameters in order to get the best forecasting results. It takes experience or . In this study, this problem can be solved using optimization algorithms, such as Genetic Algorithms. With genetic algorithms, neural networks can be trained to get the best objective function. So that after implementing the RNN which was optimized using the Genetic Algorithm on stock time series data, when the trial was carried out without optimization the Genetic Algorithm got an RMSE value of 0.108, after being combined using the genetic algorithm it got an RMSE value of 0.106.    
Shapley Additive Explanations Interpretation of the XGBoost Model in Predicting Air Quality in Jakarta Adhisa Shilfadianis Iffadah; Trimono; Dwi Arman Prasetya
Jurnal Riset Informatika Vol. 7 No. 3 (2025): Juni 2025
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1286.5 KB) | DOI: 10.34288/jri.v7i3.366

Abstract

Air quality degradation has become an increasing global problem since 2008, including in Jakarta. By 2024, air pollution in Jakarta is estimated to cause 8,400 deaths and losses of around 34 billion rupiah. To address air pollution, air quality prediction is needed using historical data of Jakarta Air Quality Index from January 2021 to May 2024. The XGBoost ensemble model was chosen for its ability to handle complex data and prevent overfitting. And Shapley Additive Explanations (SHAP) to understand how the model makes decisions. Results showed the XGBoost model achieved MAPE 4.44%. Analysis with Shapley Additive Explanations (SHAP) identified PM2.5 was significantly affected by max and PM10 features, while O3, CO, SO2, and NO2 remained relevant. An increase in PM10 tends to increase PM2.5 concentrations, suggesting the need to control this parameter to improve air quality. These results are important to provide a better understanding of the dynamics of air quality as well as provide a reference for the government in formulating more effective policies or preventive measures in Jakarta.
OPTICS-Based Clustering of East Java Regencies and Cities by Divorce Factors Cesaria Deby Nurhalizah; Aviolla Terza Damaliana; Dwi Arman Prasetya
Journal of Information Systems and Technology Research Vol. 4 No. 3 (2025): September 2025
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v4i3.1227

Abstract

Divorce is a social phenomenon that occurs when a married couple decides to legally end their marriage. This decision is influenced by various factors such as conflict, economic pressure, domestic violence, and deviant behavior. The aim of this study is to group regencies and cities in East Java Province that share similarities in the main causes of divorce, in order to understand the patterns that emerge across regions. The OPTICS (Ordering Points to Identify the Clustering Structure) clustering method was chosen for its ability to identify cluster structures with varying densities. The modeling process was conducted using a proportion-based approach for each causal factor, with optimal parameters obtained through manual grid search using min_samples = 2, xi = 0.05, and min_cluster_size = 0.1. The analysis identified three main clusters, each dominated by conflict, economic hardship, and deviant behavior, respectively. The quality of the clustering was evaluated using a Silhouette Score of 0.588, indicating reasonably good results. These findings are expected to serve as an initial understanding of divorce causes in East Java and can be used as input for the formulation of more targeted social policies.
Co-Authors Adhisa Shilfadianis Iffadah Anggraini Puspita Sari Aviolla Terza Damaliana Cesaria Deby Nurhalizah Muhammad Muharrom Al Haromainy Trimono