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All Journal Jurnal Ilmiah Manajemen dan Bisnis (JIMB) Jurnal ULTIMA Computing Optika : Jurnal Pendidikan Fisika Jurnal Abdimas Kartika Wijayakusuma
Putri, Nurulita Purnama
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Physics Social Sciences Other

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Journal : Jurnal ULTIMA Computing

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Analysis of Noise Removal Performance in Speech Signals through Comparison of Median Filter, Low FIR Filter, and Butterworth Filter: Simulation and Evaluation Putri, Nurulita Purnama; ., Martarizal
Ultima Computing : Jurnal Sistem Komputer Vol 16 No 2 (2024): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v16i2.3678

Abstract

This research aims to analyze the performance of three types of filters, namely median filters, low FIR filters, and Butterworth filters, in eliminating noise in sound signals. Evaluation is carried out through simulation and evaluation using the Mean Squared Error (MSE) and Signal-to-Noise Ratio (SNR) parameters. The simulation results show that the three filters are able to produce signal estimates that are close to the original signal with low MSE values. The median filter shows the best performance with an MSE of 0.015833 and the highest SNR of 51.6334 dB, indicating its ability to reduce noise without sacrificing signal clarity. FIR and Butterworth filters also provide good results, although with slightly lower levels of accuracy. In conclusion, median filters are the optimal choice for noise removal in speech signals, while FIR and Butterworth filters remain good alternatives depending on application requirements. Further research and practical testing are needed for validation in real-world situations
Long Term Prediction of Extreme Weather with Long Short Term Memory (LSTM) Model: Effect of Climate Change Putri, Nurulita Purnama; Harmoko Saputro, Adhi
ULTIMA Computing Vol 17 No 1 (2025): Ultima Computing: Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v17i1.4022

Abstract

Increasingly intense climate change has increased the frequency and intensity of extreme weather, making weather prediction critical for mitigation and adaptation. This research focuses on long-term prediction of extreme weather using the Long ShortTerm Memory (LSTM) model, as well as evaluating the influence of climate change on prediction accuracy. In this study, historical weather data is used to train and test an LSTM model combined with a RandomForestClassifier. Analysis was carried out using the Mean Squared Error (MSE) evaluation technique for 50 epochs and 8 trials at various threshold values (26, 29, 32, 35, 38, 41, 44, 47). The research results show that the LSTM model is able to predict extreme weather with an accuracy of up to 100%. Apart from that, this research also predicts daily rainfall in Bandung City through the process of data collection, preprocessing, normalization and evaluation using Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). This model produces an RMSE of 4.24 and MAE value of 2.72%, indicating quite good predictions. It is hoped that this research can make a significant contribution to the field of meteorology and can be developed further by adding parameters or other methods to improve the quality of predictions. Suggestions are given to increase the amount of data used to obtain better prediction results in the future.
Analysis of Noise Removal Performance in Speech Signals through Comparison of Median Filter, Low FIR Filter, and Butterworth Filter: Simulation and Evaluation: Median filter; FIR low filter; Butterworth filter; noise removal; signal noise; Mean Squared Error (MSE); Signal-to-Noise Ratio (SNR);simulation; evaluation Putri, Nurulita Purnama; ., Martarizal
ULTIMA Computing Vol 16 No 2 (2024): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v16i2.3678

Abstract

This research aims to analyze the performance of three types of filters, namely median filters, low FIR filters, and Butterworth filters, in eliminating noise in sound signals. Evaluation is carried out through simulation and evaluation using the Mean Squared Error (MSE) and Signal-to-Noise Ratio (SNR) parameters. The simulation results show that the three filters are able to produce signal estimates that are close to the original signal with low MSE values. The median filter shows the best performance with an MSE of 0.015833 and the highest SNR of 51.6334 dB, indicating its ability to reduce noise without sacrificing signal clarity. FIR and Butterworth filters also provide good results, although with slightly lower levels of accuracy. In conclusion, median filters are the optimal choice for noise removal in speech signals, while FIR and Butterworth filters remain good alternatives depending on application requirements. Further research and practical testing are needed for validation in real-world situations
Co-Authors ., Martarizal Adhi Harmoko Saputro Imam Yuwono Nasution, Ibnu Haris Rahmanti, Virzinia Nur Rahmat Rahmat Rakhmawati, Nur Endah Sardiyo Sardiyo, Sardiyo Sari, Ovi Hamidah Yuwanti, Destiyana