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All Journal Jurnal Teknologi Sistem Informasi dan Aplikasi PREDATECS: Public Research Journal of Engineering, Data Technology and Computer Science
Trisya, Cintia Putri
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Performance Comparison of ARIMA, LSTM and SVM Models for Electric Energy Consumption Analysis Azani, Nilam Wahdiaz; Trisya, Cintia Putri; Sari, Laras Mayangda; Handayani, Hani; Alhamid, Muhammad Rizki Miftha
Public Research Journal of Engineering, Data Technology and Computer Science Vol. 1 No. 2: PREDATECS January 2024
Publisher : Institute of Research and Publication Indonesia (IRPI).

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/predatecs.v1i2.869

Abstract

The changing needs of electrical energy result in the electrical power needed for everyday life being unstable, so planning and predicting how much electrical load is needed so that the electricity generated is always of good quality. So it is necessary to predict the consumption of electrical energy by using forecasting on the machine learning method. Support Vector Machine (SVM), Autoregressive Integrated Motion Average (ARIMA), and Long Short-Term Memory (LSTM) are models that are often used to overcome patterns in predictions. To find out the best models how to predict electricity consumption in the future and how the SVM, LSTM, and ARIMA algorithms perform in predicting electricity consumption. This research will look for the RMSE value and prediction time, then compare it with the best average value. The results of the study show that the ARIMA model is able to predict electricity usage for the next 1 year period, in the evaluation using the RMSE metric, where SVM shows a much lower value than ARIMA and LSTM. In this case, SVM achieved RMSE of 0.020, while ARIMA and LSTM achieved RMSE of 7.659 and 11.4183, respectively. Even though SVM has a lower RMSE, it is still unable to predict electricity usage for the next 1 year with sufficient accuracy.
Analisis Kepuasan Pengguna Aplikasi Jenius Menggunakan Metode End User Computing Satisfaction dan Importance Performance Analysis Trisya, Cintia Putri; Ahsyar, Tengku Khairil; Syaifullah, Syaifullah; Fronita, Mona
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 3 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i3.40802

Abstract

Jenius is a digital bank owned by BTPN since 2016 and licensed by OJK. The Jenius application allows users to make payments, transactions and save money in the form of long-term deposits. In 2023, Jenius will have 5.2 million users, up from 4.4 million the previous year. However, users still face a number of problems in accessing the application, such as stopped transactions, difficulty verifying to get the OTP code, and difficulty contacting customer service. This research aims to evaluate the level of user satisfaction with the Jenius application using the End User Computing Satisfaction (EUCS) and Importance Performance Analysis (IPA) methods. The research results indicate that the level of user satisfaction is correlated with a level of conformity of 83%, indicating that the Jenius application has met user expectations because it is in the very satisfied category. Based on GAP calculations, all indicators have a negative value with an average of -0.919375, an assessment of the Jenius application reveals a gap between the quality of the services offered and user expectations. IPA quadrant analysis identified Relevance (C1) and Consistency (A2) as aspects requiring improvement. To maintain user satisfaction, factors such as Information Availability (T2), Attractiveness (F1), Neatness (F2), Clarity (F3), and user ease of use (E2).
Co-Authors Ahsyar, Tengku Khairil Alhamid, Muhammad Rizki Miftha Azani, Nilam Wahdiaz Hani Handayani, Hani Mona Fronita, Mona Sari, Laras Mayangda Syaifullah Syaifullah