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All Journal JOURNAL OF ELECTRICAL AND SYSTEM CONTROL ENGINEERING MIND (Multimedia Artificial Intelligent Networking Database) Journal TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Jurnal Teknik Informatika (JUTIF) eProceedings of Engineering Ranah Research : Journal of Multidisciplinary Research and Development Journal of Computer Engineering, Electronics and Information Technology Jurnal INFOTEL JRTI (Jurnal Riset Tindakan Indonesia) Biodiversitas Journal of Biological Diversity
Syamsul Rizal
Universitas Telkom
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Transportation Other

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Deteksi Pelanggaran Marka Jalan Berbasis Pengolahan Citra Menggunakan Metode Deteksi Garis Tepi Canny Dan Transformasi Hough Iqbal Muhammadin; Iwan Iwut Tritoasmoro; Syamsul Rizal
eProceedings of Engineering Vol 7, No 2 (2020): Agustus 2020
Publisher : eProceedings of Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Pada tahun 2018, Indonesia tercatat sebagai negara peringkat ke -3 yang memiliki angka kecelakaan lalu lintas tertinggi di seluruh dunia. Salah satu faktor penyebab kecelakaan lalu lintas yaitu pelanggaran lalu lintas yang dilakukan oleh pengendara dengan tidak mengindahkan peraturan lalu lintas khususnya pada peraturan melintasi marka jalan yang terlarang. Maka dari itu, diperlukan sistem yang dapat memantau arus lalu lintas secara intensif untuk mempermudah pihak aparatur negara yang berwenang dalam membuat kebijakan berlalu lintas yang lebih baik dimasa yang akan datang. Penelitian ini menggunakan data rekaman video CCTV untuk mendeteksi pelanggaran marka jalan berbasis pengolahan citra. Pemrosesan sistem menggunakan perangkat lunak pengolah citra. Proses pengolahan citra dalam mendeteksi garis marka jalan menggunakan metode deteksi garis tepi Canny. Selain itu juga dilakukan pembandingan hasil pengujian terhadap metode deteksi garis tepi Prewitt, Roberts, dan Sobel. Metode transformasi Hough digunakan untuk membuat plotting garis lurus diatas marka jalan yang telah terdeteksi sebagai penanda pada area yang digunakan sebagai bahan pengujian. Sistem akan mendeteksi telah terjadi pelanggaran marka jalan apabila nilai piksel garis marka jalan pada citra video kurang dari nilai piksel citra background. Pengujian dilakukan dengan menggunakan 4 buah video bahan uji untuk setiap metode deteksi garis tepi. Setiap video memiliki 450 frame dengan spesifikasi durasi 15 detik dan frame rate sebesar 30 fps. Sistem mendapatkan hasil pengujian terhadap nilai akurasi dalam mendeteksi jumlah kendaraan yang melanggar marka jalan sebesar 100% untuk pengujian pada seluruh metode deteksi garis tepi yang digunakan dalam proses pengujian. Metode deteksi garis tepi yang memiliki kinerja terbaik dalam proses deteksi pelanggaran marka jalan yaitu metode deteksi garis tepi Roberts dengan nilai error rate sebesar 0 % untuk pengujian data video ke-1, 20,89 % untuk pengujian data video ke-2, 41,78 % untuk pengujian data video ke-3 dan 53,33 % untuk pengujian data video ke-4.Kata Kunci: lampu lalu lintas, suara sirene, sistem kontrol, MFCC, Euclidean Distance, Arduino.
Application of Neural Network for ECG-based Biometrics System Using QRS Features Ana Rahma Yuniarti; Syamsul Rizal; Ferdinand Aprillian Manurung
Journal of Computer Engineering, Electronics and Information Technology Vol 1, No 2 (2022): COELITE: Volume 1, Issue 2, 2022
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (780.059 KB) | DOI: 10.17509/coelite.v1i2.43823

Abstract

Applications of Biometrics technology are extremely popular today, ranging from access control to automation. Fingerprint is the oldest and the most widely used biometrics technology. However, its key features are externally exposed which make it tend to be easily forged. This study investigates the possibility of electrocardiogram (ECG) signal as an alternative modality for biometrics systems. Besides that, the study is conducted using the ECG database under arrhythmia conditions to accommodate the real-world application since arrhythmia exists in large-scale world populations. In this study, a total of 8,972 datasets from 47 subjects were modeled using a machine learning technique (i.e., one-dimensional convolution neural network or 1-D CNN). The results showed that the accuracy (F1-score) of 92% and 0.25 of loss was achieved. Furthermore, we prove that the proposed model is a good fitting based on the visualization plot of the train-test. These findings show that the proposed model is reasonable enough for an ECG-based biometrics system though it's not the best in the literature.
Support Vector Regression untuk Prediksi Beban Listrik Jangka Pendek Menggunakan Metode Fraktal Khalisa Sasikirana Athaya; Jangkung Raharjo; Syamsul Rizal
Ranah Research : Journal of Multidisciplinary Research and Development Vol. 5 No. 4 (2023): Ranah Research : Journal Of Multidisciplinary Research and Development (Agustus
Publisher : Dinasti Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/rrj.v5i4.772

Abstract

In this era of globalization, electricity is one of the essential needs in human life. Electricity load prediction plays a crucial role in designing supply-demand operations to avoid losses from various aspects. In this study, short-term electricity load prediction is conducted per 30 minutes, aiming to achieve minimum prediction errors. Support Vector Regression (SVR) is used as the machine learning method for data classification, and fractal method is employed for dimension calculation and feature extraction from historical data. The results of this research are as follows: In the first experiment, short-term prediction was conducted without using the fractal method, resulting in a Mean Absolute Percentage Error (MAPE) of 2.85%. In the second experiment, short-term prediction was performed using the dataset that had undergone fractal calculation and feature extraction, leading to a lower MAPE of 2.32%. The prediction results using the fractal method obtained a lower MAPE compared to the non-fractal approach. Fractal significantly influences the calculation of short-term electricity load prediction using Support Vector Regression (SVR).
Construction of cardiac arrhythmia prediction model using deep learning and gradient boosting Dhanar Bintang Pratama; Favian Dewanta; Syamsul Rizal
JURNAL INFOTEL Vol 13 No 3 (2021): August 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v13i3.683

Abstract

Arrhythmia is a condition in which the rhythm of heartbeat becomes irregular. This condition in extreme cases can lead to fatal heart attack accidents. In order to reduce heart attack risk, appropriate early treatments should be conducted right after getting results of Arrhythmia condition, which is generated by electrocardiography ECG tools. However, reading ECG results should be done by qualified medical staff in order to diagnose the existence of arrhythmia accurately. This paper proposes a deep learning algorithm method to classify and detect the existence of arrhythmia from ECG reading. Our proposed method relies on Convolutional Neural Network (CNN) to extract feature from a single lead ECG signal and also Gradient Boosting algorithm to predict the final outcome of single lead ECG reading. This method achieved the accuracy of 96.18% and minimized the number of parameters used in CNN Layer.
Classification of eye diseases in fundus images using Convolutional Neural Network (CNN) method with EfficientNet architecture Zhafeni Arif; R. Yunendah Nur Fu’adah; Syamsul Rizal; Divo Ilhamdi
JRTI (Jurnal Riset Tindakan Indonesia) Vol. 8 No. 1 (2023): JRTI (Jurnal Riset Tindakan Indonesia)
Publisher : IICET (Indonesian Institute for Counseling, Education and Therapy)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/30032835000

Abstract

This research is designed to classify eye disease conditions into three classes, namely normal, cataract, and glaucoma using a system. The system will use Convolutional Neural Network (CNN) with EfficientNet architecture. The EfficientNet that will be used is EfficientNet-B0. The dataset in this paper is obtained from Kaggle totaling 300 images. From this data, augmentation is carried out so that 3.600 images are obtained consisting of "normal" (1200 images), "cataract" (1200 images), and "glaucoma" (1200 images). This data is processed into 4 different datasets, namely the original dataset, augmentation dataset, augmentation dataset that has been preprocessed grayscale, and augmentation dataset that has been preprocessed thresholding. The best results are obtained using the Adam optimizer, learning rate 0.00001, and batch size 32, and iterations of 20 epochs. The best dataset is the augmentation dataset that has been preprocessed grayscale with an accuracy of 79.22%, precision value of 80.3%, recall value of 79.22%, F1-Score of 78.87%.
Short Communication: Plant diversity utilization and land cover composition in the Subak Jatiluwih, Bali, Indonesia Sutomo Sutomo; Rajif Iryadi; I Dewa Putu Darma; I Putu Agus Hendra Wibawa; Ayyu Rahayu; Siti Fatimah Hanum; Syamsul Rizal; Ledya Novamizanti; Jangkung Raharjo
Biodiversitas Journal of Biological Diversity Vol. 22 No. 3 (2021)
Publisher : Society for Indonesian Biodiversity

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/biodiv/d220345

Abstract

Abstract. Sutomo, Iryadi R, Darma ID, Wibawa IPAH, Rahayu A, Hanum SF, Rizal S, Novamizanti L, Raharjo J. 2021. Short Communication: Plant diversity utilization, and land cover composition in the Subak Jatiluwih, Bali, Indonesia. Biodiversitas 22: 1424-1432. Subak is water management or irrigation system for paddy fields in Bali Island and it has been assigned as a UNESCO’s World Heritage Site. At a landscape level, it comprises several components which are forests, terraced paddy landscape, rice fields, villages and temples. Subak in Jatiluwih Village, Tabanan Regency depicts an area characterized by its natural appearance in the form of a vast rice valley with a dike in stratum following its natural contours (frequent terraces). This paper aimed to explore plant diversity in various vegetations around Subak Jatiluwih as well as their usage in the daily living of the local community. We also explore the potential application of drone for classifying the landscape patterns of the Subak.Vegetation sampling to record plant diversity was done using purposive sampling, and drone or Unmanned Aerial Vehicle (UAV) was used to map the Subak Jatiluwih landscape. The potential usage of each species was obtained through interview with key respondents, and the level of usage of each species was analyzed using the BIV (Benefit Index Value). Tegalan area shows the highest number plant diversity in Subak Jatiluwih area. Furthermore, there are four species of plants that have the highest BIV namely: Cocos nucifera L., Psidium guajava L., Areca catechu L. and Musa × paradisiaca L.. Various plant uses by the locals include for animal feed, building, ceremony, craft, and food and medicinal purposes. The landscape in Subak Jatiluwih is dominated the vast valley of rice fields that has strata following its natural contours. These conditions provide opportunities to applied the conservation strategy based on cultural and custom values.
Co-Authors Achmad Rizal Ana Rahma Yuniarti Ayyu Rahayu Dhanar Bintang Pratama Dieny Rofiatul Mardiyah Divo Ilhamdi Fajar Kurniawan Alhamal FAUZI FRAHMA TALININGSIH Favian Dewanta Ferdinand Aprillian Manurung Gelar Budiman Hilman Fauzi, Hilman Hurianti Vidya I Dewa Putu Darma I Putu Agus Hendra Wibawa Iqbal Muhammadin Iwan Iwut Tritoasmoro Jangkung Raharjo Khalisa Sasikirana Athaya Ledya Novamizanti Mochamad Dandi Muhamad Rokhmat Isnaini MUHAMMAD ADNAN PRAMUDITO Nor Kumalasari Caecar Pratiwi Novelita Dwi Miranda Nugraeni Kholifaturrofiah Nur Ibrahim R. Yunendah Nur Fu’adah Rajif Iryadi Rendi Bagus Oklanri Rita Magdalena Siti Fatimah Hanum SOFIA SAIDAH Sutomo Sutomo Utari Nur Ramadhani Yora Zhafeni Arif