Indra Hermawan

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Compositional manipulation in hybrid metal Sulfide nanocomposite: An effective strategy to boost the electromagnetic wave dissipation performance

Ceramics International

Hierarchical 3D MoSe2 and 1D MnFe2O4 Wrapped with MnO2 nanocomposites toward high-performance Bi-layer microwave absorber

Ceramics International

Denoising Noisy ECG Signal Based on Adaptive Fourier Decomposition

2018 3rd International Seminar on Sensors, Instrumentation, Measurement and Metrology (ISSIMM), 2018

An electrocardiogram (ECG) is the result of measuring the electrical activity of the heart. Analy... more An electrocardiogram (ECG) is the result of measuring the electrical activity of the heart. Analysis of ECG signal is very useful for detecting abnormalities in the heart by a cardiologist. However, the results of the analysis are affected by the conditions of the Electrocardiogram signal. Electrocardiogram signal has the characteristics of nonstationary, nonlinear and susceptible to noise. This noise can damage the ECG signal, causing damage to the ECG signal which makes it difficult for the cardiologist to analyze the electrocardiogram signal. That noise can be sourced from respiration, mode movement, lack of electrode contact, and another electronic device. To overcome this problem, in this paper filtering is done to eliminate noise on ECG signals. The filter method developed in this study is based on Adaptive Fourier Decomposition (AFD). The ECG signal will be decomposed by that method into several components based on their energy distribution. Therefore, AFD has good performance in separate original ECG signal from noise that has different energy distribution. This AFD method is robust with computation time that is not much different from the Discrete Fourier transform method. To measure the performance of AFD based method, several tests have done by using the MIT-BIH Arrhythmia database. Based on tests result the AFD method has a better performance on almost all recordings than the EMD and Wavelet Transform methods.

Multicodebook Neural Network Using Intelligent K-Means Clustering Based on Histogram Information for Multimodal Data Classification

2018 International Workshop on Big Data and Information Security (IWBIS), 2018

Multimodal distribution makes classification more challenging. In some cases, it will cause a dec... more Multimodal distribution makes classification more challenging. In some cases, it will cause a decrease in performance of the classifier. Therefore, we must select and utilize an appropriate classifier for this kind of data. In addition, multimodal distribution causes classification result of single-codebook-based classifiers fail to classify the data accurately. Some research has been conducted to build multicodebook-based classifier. In this study, we propose an enhancement of Multicodebook Fuzzy Neuro Generalized Learning Vector Quantization method using Intelligent K-Means clustering based on Histogram Information. First, We used Intelligent K-Means Clustering using histogram information as the number of cluster parameter. Next, We applied the clustering method to FNGLVQ in order to generate codebook candidate before the training process. The experiment is conducted using synthetic and benchmark datasets. Overall, the proposed method achieved a better accuracy compared to multi codebook FNGLVQ using IK-Means clustering based on anomalous pattern and original FNGLVQ with a margin of 4.14% and 17.29% respectively.

Pengaruh Model Praktek Kerja Industri (Block Week Release Dan Block Month Release ) Terhadap Kompetensi Membubut Siswa Sekolah Menengah Kejuruan (Studi Kasus: SMK N 2 Medan)

Kegiatan Praktek kerja industri (prakerin) yang dilaksanakan diharapkan mampu meningkatkan kompet... more Kegiatan Praktek kerja industri (prakerin) yang dilaksanakan diharapkan mampu meningkatkan kompetensi siswa, ternyata sebahagian dari nilai mata Diklat kejuruan siswa yang telah melakukan prakerin tetap rendah terutama nilai mata Diklat kompetensi membubut. Untuk mengatasi hambatan-hambatan tersebut, dalam pengelolaan pendidikan dan pengajaran dapat dibuat berbagai kebijaksanaan, antara lain melaksanakan Prakerin dengan model block week release atau model block month release. Tujuan dari penelitian ini secara umum adalah mengetahui Pengaruh Model Praktek Kerja Industri (Block Week Release Dan Block Month Release) Terhadap Kompetensi Membubut Siswa SMK. Sedangkan tujuan khususnya adalah mengetahui keunggulan Prakerin model block week release dalam kompetensi membubut dibandingkan dengan model block month release. Metode penelitian ini adalah quasi eksperimen dengan rancangan faktorial 2 x 2 dan teknik analisis data menggunakan ANAVA. Tes perbedaan antar sel digunakan dengan menggunak...

Indra Hermawan

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