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A ROBUST WATERMARKING SCHEME AGAINTS VARIOUS ATTACKS BASED ON DCT IN FIVE DIFFERENT POSITIONS OF THE HOST IMAGE AREA Rosiyadi, Didi; Muttaqien, Furqon Hensan
Teknologi Indonesia Vol 36, No 3 (2013)
Publisher : LIPI Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/jti.v36i3.206

This paper proposed a robustness watermarking scheme against various attacks based on Discrete Cosine Transform (DCT) in fi ve different positions of the host image area. The scheme comprises the level of watermark resistance and the level of host image perceptibility against various attacks. Here, the level of resistance of a watermark image can be seen from the value of Normalized Correlation Coeffi cient (NC). Meanwhile, the level of perceptibility of an image of host image can be seen from the value of its Peak Signal to Noise Ratio (PSNR). In this proposed research, a method of the Non Blind Discrete in which a host image is required in the process of extraction is used. This watermark, furthermore, is positioned in a visible way in fi ve different positions of the host image; those are on the upper left, lower left, upper right, lower right and on the middle. For the type of attacks, this research uses geometric attacks consisting of Rotation, Scaling and Cropping. The result of this research then shows the level of resistance and the level of perceptibility for all images, and obtains the most robust watermark scheme against various attacks.

Identifikasi Pembicara Menggunakan Algoritme VFI5 dengan MFCC sebagai Pengekstraksi Ciri Zilvan, Vicky; Muttaqien, Furqon Hensan
INKOM Journal Vol 5, No 1 (2011)
Publisher : Pusat Penelitian Informatika - LIPI

Voting Feature Instervals (VFI) 5 memiliki akurasi yang cukup tinggi dalam mengklasifikasikan data berbasis teks dan citra. Berdasarkan hal tersebut dikembangkanlah metode identifikasi pembicara menggunakan algoritme VFI5 dengan Mel Frequency Ceptrum Coefficients (MFCC) sebagai pengekstraksi ciri suara untuk melihat keakuratan algoritme VFI5 dalam mengklasifikasikan data berbasis suara. Jenis identifikasi pembicara pada penelitian ini bersifat tertutup dan bergantung pada text. Pada penelitian ini juga dilakukan percobaan menggunakan suara ber-noise untuk melihat kehandalan VFI5 dalam mengklasifikasikan suara ber-noise. Dari hasil pengujian didapatkan bahwa metode yang telah dikembangkan ini memiliki akurasi cukup tinggi dengan akurasi tertinggi sebesar 97% untuk data suara tanpa noise. Â Selain itu juga diketahui bahwa jumlah data latih yang optimal untuk menghasilkan akurasi yang tinggi adalah 11. Sedangkan untuk suara bernoise dengan SNR sebesar 30 dB, akurasi tertinggi mencapai 81,5 % dan untuk suara bernoise dengan SNR sebesar 20 dB tingkat akurasi tertinggi mencapai 59 %.

Irregular Grid Interpolation using Radial Basis Function for Large Cylindrical Volume Syam Budi Iryanto; Furqon Hensan Muttaqien; Rifki Sadikin
Jurnal Ilmu Komputer dan Informasi Vol 13, No 1 (2020): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information
Publisher : Faculty of Computer Science - Universitas Indonesia

Irregular grid interpolation is one of the numerical functions that often used to approximate value on an arbitrary location in the area closed by non-regular grid pivot points. In this paper, we propose method for achieving efficient computation time of radial basis function-based non-regular grid interpolation on a cylindrical coordinate. Our method consist of two stages. The first stage is the computation of weights from solving linear RBF systems constructed by known pivot points. We divide the volume into many subvolumes. At second stages, interpolation on an arbitrary point could be done using weights calculated on the first stage. At first, we find the nearest point with the query point by structuring pivot points in a K-D tree structure. After that, using the closest pivot point, we could compute the interpolated value with RBF functions. We present the performance of our method based on computation time on two stages and its precision by calculating the mean square error between the interpolated values and analytic functions. Based on the performance evaluation, our method is acceptable.

Identifikasi Pembicara Menggunakan Algoritme VFI5 dengan MFCC sebagai Pengekstraksi Ciri Vicky Zilvan; Furqon Hensan Muttaqien
INKOM Journal Vol 5, No 1 (2011)
Publisher : Pusat Penelitian Informatika - LIPI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.inkom.97

Voting Feature Instervals (VFI) 5 memiliki akurasi yang cukup tinggi dalam mengklasifikasikan data berbasis teks dan citra. Berdasarkan hal tersebut dikembangkanlah metode identifikasi pembicara menggunakan algoritme VFI5 dengan Mel Frequency Ceptrum Coefficients (MFCC) sebagai pengekstraksi ciri suara untuk melihat keakuratan algoritme VFI5 dalam mengklasifikasikan data berbasis suara. Jenis identifikasi pembicara pada penelitian ini bersifat tertutup dan bergantung pada text. Pada penelitian ini juga dilakukan percobaan menggunakan suara ber-noise untuk melihat kehandalan VFI5 dalam mengklasifikasikan suara ber-noise. Dari hasil pengujian didapatkan bahwa metode yang telah dikembangkan ini memiliki akurasi cukup tinggi dengan akurasi tertinggi sebesar 97% untuk data suara tanpa noise. Â Selain itu juga diketahui bahwa jumlah data latih yang optimal untuk menghasilkan akurasi yang tinggi adalah 11. Sedangkan untuk suara bernoise dengan SNR sebesar 30 dB, akurasi tertinggi mencapai 81,5 % dan untuk suara bernoise dengan SNR sebesar 20 dB tingkat akurasi tertinggi mencapai 59 %.

Time-Series Model for Climatological Forest Fire Prediction over Borneo Arnida Lailatul Latifah; Furqon Hensan Muttaqien; Inna Syafarina; Intan Nuni Wahyuni
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol 13 No 1 (2022): Vol. 13, No. 1 April 2022
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/LKJITI.2022.v13.i01.p04

Areas covered by tropical forests, such as Borneo, are vulnerable to fires. Previous studies have shown that climate data is one of the critical factors affecting forest fire. This study aims to predict the forest fire over Borneo by considering the temporal aspects of the climate data. A time seriesbased model, Long Short-Term Memory (LSTM), is used. Three LSTM models are applied: Basic LSTM, Bidirectional LSTM, and Stacked LSTM. Three different experiments from January 1998 to December 2015 are conducted by examining climate data, Oceanic Nino Index (ONI), and Indian Ocean Dipole (IOD) index. The proposed model is evaluated by Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and correlation number. As a result, all models can capture the spatial and temporal pattern of the forest fires for all three experiments, in which the best prediction occurs in September with a spatial correlation of more than 0.75. Based on the evaluation metrics, Stacked LSTM in Experiment 1 is slightly superior, with the highest annual pattern correlation (0.89) and lowest error (MAE= 0.71 and RMSE=1.32). This finding reveals that an additional ONI and IOD index as the prediction features would not improve the model performance generally, but it specifically improves the extreme event value.

Performance Evaluation of NAS Parallel and High-Performance Conjugate Gradient Benchmarks in Mahameru Wirahman, Taufiq; Latifah, Arnida L; Muttaqien, Furqon Hensan; Swardiana, I Wayan Aditya; Arisal, Andria; Iryanto, Syam Budi; Sadikin, Rifki
JOIN (Jurnal Online Informatika) Vol 10 No 2 (2025)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v10i2.1557

High-Performance Computing (HPC) plays a crucial role in accelerating scientific advancement across numerous fields of research and in effectively implementing various complex scientific applications. Mahameru is one of the largest national HPC systems in Indonesia and has been utilized by many sectors. However, it has not undergone proper benchmarking evaluation, which is vital for identifying issues related to hardware and software configurations and confirming system reliability. Therefore, this study aims to evaluate the performance, efficiency, and capabilities of Mahameru. We present a benchmarking system on Mahameru utilizing two benchmark suites: the NAS Parallel Benchmarks (NPB) and the high-performance conjugate gradient (HPCG) benchmark. Our results indicate that the NPB exhibits a lower speedup in Message Passing Interface (MPI) compared to OpenMP, which can be attributed to the communication overhead and the nature of the computational tasks. Additionally, the HPCG benchmark demonstrates that Mahameru performance can compete with the lower tiers of the Top 500 supercomputers. When operating at full capacity, Mahameru can achieve approximately 2.5% of its theoretical peak performance. While the system generally performs reliably with parallel algorithms, it may not fully leverage hyperthreading with certain algorithms. This benchmark result can serve as a basis for decision-making regarding potential upgrades or changes to a system.

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