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All Journal Jurnal Pilar Nusa Mandiri SPIRIT Jurnal Abdi Panca Marga Journal of Informatics Development
Murni, Cahyasari Kartika
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Journal : Journal of Informatics Development

 1 
Product Demand Forecasting in E-Commerce with Big Data Analytics: Personalization, Decision Making and Optimization Murni, Cahyasari Kartika; Choiri, Achmad Firman; Rahmawati, Febriane Devi
Journal of Informatics Development Vol. 3 No. 2 (2025): April 2025
Publisher : Institut Teknologi dan Bisnis Widya Gama Lumajang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30741/jid.v3i2.1548

Abstract

This study explores the role of Big Data in forecasting product demand in the e-commerce sector through the application of machine learning and time series methods. A quantitative descriptive approach is used, involving data collection, preprocessing, analysis, and model evaluation. Forecasting techniques applied include ARIMA for time series prediction and XGBoost for supervised learning to identify key demand factors. Model performance is evaluated using accuracy metrics such as RMSE, MAE, and MAPE. The results indicate that the XGBoost model provides the highest forecasting accuracy at 89%, while the ARIMA model achieves 78%. These findings demonstrate that Big Data significantly supports strategic decision-making in e-commerce by enhancing personalization, optimizing inventory, and enabling data-driven marketing strategies.
Implementation of Artificial Neural Network for IoT-Based Water Quality Classification in Fish Ponds Choiri, Achmad Firman; Murni, Cahyasari Kartika
Journal of Informatics Development Vol. 4 No. 1 (2025): Oktober 2025
Publisher : Institut Teknologi dan Bisnis Widya Gama Lumajang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30741/jid.v4i1.1752

Abstract

This study presents the implementation of an Artificial Neural Network (ANN) to classify water quality in fish ponds using a dataset derived from a fuzzy inference-based IoT system. The previous fuzzy system utilized three sensor parameters—pH, Total Dissolved Solids (TDS), and temperature—to determine water quality (good, moderate, poor) through rule-based reasoning. Although the fuzzy approach produced accurate and interpretable results, it lacked adaptability to new data variations and required manual rule adjustments. In this research, the ANN model was trained using MATLAB’s Neural Network Toolbox with 120 dataset samples obtained from the fuzzy system’s outputs. The model architecture consisted of three input neurons (pH, TDS, temperature), one hidden layer with ten neurons using a tansig activation function, and one output neuron with purelin. Training of the model was conducted using the Levenberg–Marquardt backpropagation algorithm, employing a dataset split of 80% for training, 10% for validation, and 10% for testing. The results showed that the ANN achieved a classification accuracy of 94.8%, with a Mean Squared Error (MSE) of 0.85942 and a regression coefficient (R) of 0.94, indicating a strong correlation between predicted and actual data. Compared to the fuzzy inference method, the ANN model demonstrated better adaptability to unseen data and a higher level of generalization. This system can be integrated into IoT-based monitoring platforms for real-time, intelligent, and adaptive water quality prediction to support sustainable aquaculture.
The Impact of TikTok Technology Transformation in the Digitalization Era Using SmartPLS Murni, Cahyasari Kartika
Journal of Informatics Development Vol. 2 No. 1 (2023): October 2023
Publisher : Institut Teknologi dan Bisnis Widya Gama Lumajang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30741/jid.v2i1.1191

Abstract

The utilization of technology has become the foundation for many businesses striving to remain competitive in the current digital era, where online shopping is increasingly dominant. TikTok, as a popular social media platform, has been employed as a marketing tool to reach a wider audience by offline businesses. This research seeks to understand the impact of TikTok technology utilization on online purchasing decisions. The sustainability of offline businesses depends on adapting to the changing consumer behavior, which is increasingly inclined towards online shopping. This study highlights the importance of using TikTok as a creative and innovative marketing tool to reach online customers. The research results indicate that the more intensive the use of TikTok technology, the more likely customers are to opt for online shopping. Subsequently, the ease of shopping on TikTok mediates the influence of technology utilization on online purchasing decisions. However, online product prices do not play a significant mediating role in purchase decision-making. In order to compete in an increasingly interconnected digital era, offline businesses need to consider more innovative marketing strategies and focus on providing a better user experience. The utilization of technology and creativity in TikTok content becomes the key to influencing online purchase decisions by digitally connected customers.
Co-Authors Ahmad Iskandar Rahmansyah Bahri, Mohammad Saiful Choiri, Achmad Firman Herdiansyah, Muhammad Rizal Hizham, Fadhel Akhmad Hudzafidah, Khusnik Husin, Muhammad Syauqi Krisnawati, Titin Rahmawati, Febriane Devi