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All Journal Journal of Advances in Information Systems and Technology Journal of Information System Exploration and Research Scientific Journal of Informatics
Prasetya, Ananda
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Utilization of Business Intelligence in Sales Information Systems Nurdin, Alya Aulia; Salmi, Gading Nur; Sentosa, Kevin; Wijayanti, Annisa Rachma; Prasetya, Ananda
Journal of Information System Exploration and Research Vol. 1 No. 1 (2023): January 2023
Publisher : shmpublisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joiser.v1i1.101

Abstract

Business intelligence is one of the concepts that can facilitate the process of processing data of a company which will later become the basis for the decision-making process of the sales process. Distributor company needs an information system that can help the company in managing and analyzing data and can make sales and profit predictions in the future. This study aims to create an information system that can visualize data analysis and the results of forecasting sales data by avocado fruit distributor companies. In this study, we will apply the concept of Business Intelligence using Power BI Desktop which is equipped with sales prediction analysis on the sales information system. The data processing process in this study uses the process of integrating Excel tools with Power BI Desktop. The dataset of sales in this study was obtained from the Kaggle site and the software development in this study using the SDLC (system development life cycle) waterfall development method. In this study, we found that the development of business intelligence in the sales information system provides convenience that can be felt by distributors, namely in terms of revenue and time. In this case, forecasting is done with the forecast feature in Power BI Desktop with a confidence interval of 95%.
Analysis and Quality Measurement of SITEDI Sub-System Against User Satisfaction Using WebQual 4.0 and End-User Computing Satisfaction (EUCS) Methods Prasetya, Ananda; Efrilianda, Devi Ajeng
Journal of Advances in Information Systems and Technology Vol 5 No 2 (2023): October
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v5i2.72747

Abstract

One of the efforts in handling educational challenges in the era of technological development is the development of the Thesis Information System for Dissertation Thesis (SITEDI). SITEDI is an information system that facilitates the thesis administration process starting from the presentation of the subject matter to the final exam managed by Universitas Negeri Semarang (UNNES). Therefore, it is necessary to measure the quality of SITEDI performance based on user satisfaction to facilitate the evaluation process of SITEDI as a quality student service in the future. The research method used in this study is a combination of WebQual 4.0 and End-User Computing Satisfaction (EUCS). The variables used include usability quality, information quality, service interaction quality, format, and timeliness. The sample used was 135 respondents with purposive sampling technique. The results of the analysis that have been carried out conclude that simultaneously the variables of usability quality, information quality, service interaction quality, format, and timeliness have an influence on user satisfaction by 62.5%. WebQual 4.0 variables, namely service interaction quality, information quality, and usability quality sequentially have a significant influence on user satisfaction with an effect size of 0.092, 0.069, and 0.028. Meanwhile, the EUCS variables, namely format and timeliness, do not have a significant influence on user satisfaction.
Optimization of Mineral Fuel Export Forecasting Using Attention-based Long Short-Term Memory Prasetya, Ananda; Suseno, Jatmiko Endro; Sutikno
Scientific Journal of Informatics Vol. 13 No. 1: February 2026
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v13i1.38381

Abstract

Purpose: This study aims to optimize the forecasting of the Net Value of Indonesia's mineral fuel exports using the Attention-based Long Short-Term Memory (LSTM) model, supported by Dropout and Recurrent Dropout techniques that are combined to produce an optimal model. Methods: Modeling uses an LSTM architecture equipped with an Attention mechanism, as well as Dropout and Recurrent Dropout. The research procedure uses the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology. The research material used is the Indonesian mineral fuel export dataset with HS code 27 from 2014 to 2025. Model was built using the Random Search method to optimize hyperparameters such as the number of neurons (units), activation functions (Tanh, ReLu), and optimizers (Adam, Nadam, RMSprop). Result: The Attention-based LSTM model with Dropout and Recurrent Dropout techniques achieved a MAPE of 7.76%, which was better than the other models tested. Attention analysis shows that lag 12 has the greatest dominance, while lags 11 to 10 also contribute significantly, indicating an annual seasonal pattern. Projections for the next 12 months show a moderate decline in Net Value, in line with seasonal trends and historical data. Novelty: The main contribution of this research is the optimization of an Attention-based LSTM model using a combination of Dropout and Recurrent Dropout techniques, which is effective in forecasting Indonesia's mineral fuel export values because it is able to capture annual seasonal patterns, thereby improving the accuracy and stability of the forecast results.
Co-Authors Efrilianda, Devi Ajeng Jatmiko Endro Suseno Nurdin, Alya Aulia Salmi, Gading Nur Sentosa, Kevin SUTIKNO Wijayanti, Annisa Rachma