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All Journal JPTK: Jurnal Pendidikan Teknologi dan Kejuruan JURNAL NASIONAL TEKNIK ELEKTRO Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Mekanova : Mekanikal, Inovasi dan Teknologi Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Rekayasa elektrika Suara Teknik : Jurnal Ilmiah Jurnal Polimesin Sriwijaya Electrical and Computer Engineering (Selco) Journal

Safrizal Razali

Universitas Syiah Kuala

Author-ID : 5839262

Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Other

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Articles

Pemetaan Potensi Pembangkit Listrik Tenaga Bayu di Perairan Indonesia Berdasarkan Data Satelit ASCAT Safrizal Safrizal; Haimi Ardiansyah; Dailami Dailami
Jurnal Mekanova : Mekanikal, Inovasi dan Teknologi Vol 7, No 2 (2021): Oktober
Publisher : universitas teuku umar

Kebutuhan energi listrik menjadi isu penting yang dapat mendorong daya saing Indonesia di kancah perekonomian dunia. Saat ini, Indonesia masih menggunakan energi yang bersumber dari fosil. Energi fosil adalah energi yang tidak terbarukan sehingga akan habis pada suatu masa. Kemampuan Indonesia dalam menghasilkan energi listrik terbarukan merupakan solusi dari permasalahan tersebut. Salah satu sumber energi listrik terbarukan berasal dari Pembangkit Listrik Tenaga Bayu (PLTB). Penelitian ini bertujuan memetakan sumber energi PLTB di perairan Indonesia dengan menggunakan data dari satelit ASCAT. Penelitian ini dimulai dengan mengumpulkan data harian kecepatan bayu periode 01 Januari 2017 sampai dengan 31 Desember 2018. Data tersebut merupakan data pada ketinggian 10 m, dengan menggunakan model matematis data tersebut kemudian diolah agar didapatkan kecepatan bayu serta power density pada ketinggian 120 m. Langkah selanjutnya adalah pembuatan peta potensi PLTB di perairan Indonesia. Dari peta tersebut, diketahui bahwa perairan Indonesia di Samudera Hindia dan Laut Arafura memiliki potensi yang lebih baik dari pada perairan lainnya. Kecepatan bayu rata-rata pada ketinggian 120 m adalah 9,24 m/s, sedangkan rata-rata power density sebesar 955,64 W/m2. Jumlah turbin yang dapat dibangun di wilayah ZEE Indonesia adalah sebanyak 4.800.292 unit dengan jumlah tersebut maka dapat menghasilkan energi listrik sebesar 10.080 GW.

Vocational Students' Perception of Online Learning during the Covid-19 Pandemic Hilma Erliana; Safrizal Safrizal; Rahmad Nuthihar; Luthfi Luthfi; Wahdaniah Wahdaniah; Ilham Jaya; RN Herman
Jurnal Pendidikan Teknologi dan Kejuruan Vol 27, No 1 (2021): (May)
Publisher : Faculty of Engineering, Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jptk.v27i1.34283

COVID-19 pandemic impacts on vocational education. Lectures that were originally conducted face-to-face learning are diverted to online learning to avoid the spread of the pandemic. Online learning is very difficult to apply for courses conducted in the laboratory. This study discusses vocational students’ responses to the practice of online learning during the COVID-19 pandemic. Data were collected through a questionnaire created on Google form consisting of 20 questions. The questionnaire used a Likert scale to find out the attitudes and students’ perceptions of the implementation of online learning. The number of research respondents was 107 people consisting of 45 respondents from the West Aceh State Community Academy and 62 respondents from Lhokseumawe State Polytechnic, Aceh, Indonesia. The results of this study found that 59.81% of students disagree with online learning. The results also showed a score of 76.95% of the students agree that internet access is the main obstacle in online learning. However, students’ satisfaction with the current online learning system for students shows a score of 67.50%. Opinions related to online learning from 107 respondents showed that 45.42% of them less agree if online learning is still applied when the COVID-19 pandemic ends.

Pengenalan Aksara Jawi Tulisan Tangan Menggunakan Freemen Chain Code (FCC), Support Vector Machine (SVM) dan Aturan Pengambilan Keputusan Safrizal .; Fitri Arnia; Rusdha Muharar
JURNAL NASIONAL TEKNIK ELEKTRO Vol 5 No 1: Maret 2016
Publisher : Jurusan Teknik Elektro Universitas Andalas

Jawi is one variant of Arabic script consists of 35 characters. Some of Jawi characters have the same main shape, but different number of dots in different location. Thus, recognition process of Jawi characters can be done by performing a classification based on the main shape. In recognition process, feature extraction plays an important role. In this research, Freeman Chain Code (FCC) was used as feature extraction and Support Vector Machine (SVM) as classifier. Then we apply the decision rules to classifySVMresult into Jawi characters. FCC is used to represent the boundary of Jawi characters into a chain code. Then the chain code is used bySVMto classify the characters into 19 groups. Feature of location and the number of dots are used by decision rules to classify the groups into Jawi characters. The Jawi characters are handwritten and generated by 10 writers from different backgrounds and ages. The recognition rate of this research was 80.00%.Keywords : Jawi script, handwriting, FCC, SVM, decision rules.Abstrak—Aksara Jawi merupakan salah satu varian dari aksara Arab yang terdiri dari 35 aksara. Dari 35 aksara Jawi tersebut terdapat beberapa aksara dengan bentuk bagian utama yang sama namun memiliki letak dan jumlah titik yang berbeda. Karena perbedaan tersebut maka proses pengenalan aksara Jawi dapat dilakukan dengan melakukan klasifikasi berdasarkan perbedaan bentuk bagian utama. Pada penelitian ini Freeman Chain Code (FCC) digunakan sebagai ekstraksi fitur dan Support Vector Machine (SVM). FCC digunakan untuk merepresentasikan garis batas (boundary) aksara Jawi kedalam kode rantai. Kode rantai tersebut diklasifikasi dengan menggunakan SVM kedalam 19 kelompok. Fitur letak titik dan jumlah titik digunakan sebagai aturan pengambilan keputusan terhadap 19 kelompok hasil klasifikasi SVM kedalam aksara Jawi. Aksara Jawi yang digunakan merupakan tulisan tangan dari 10 orang penulis dari berbagai latar belakang dan umur. Tingkat keberhasilan klasifikasi penelitian ini mencapai 80,00%.Kata Kunci : aksara Jawi, tulisan tangan, FCC, SVM, aturan pengambilan keputusan

Improved Classification of Handwritten Jawi Script Based on Main Part of Script Body Safrizal Razali; Fitri Arnia; Rusdha Muharrar; Kahlil Muchtar; Akhyar Bintang
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 1 (2023): February 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i1.4600

Since the entry of Islam, many ancient relics in the archipelago were written using Jawi script. Due to human or natural factors, these ancient relics will be damaged or destroyed. To avoid the loss of this ancient heritage data, the data must be stored in digital documents. In order to convert digital documents into machine-readable text format, the use of Optical Character Recognition (OCR) technology is inevitable. In this research, OCR technology is implemented on isolated Jawi scripts. Freeman Chain Code (FCC) is used to extract the isolated Jawi script features. Subsequently, the FCC feature is fed into Support Vector Machine (SVM) in order to classify the character. The decision rule classification is applied to the class of SVM classification in the Jawi script form. The results of the SVM classification into 19 classes reached 81.58%, while the results for merging into 15 classes produced better results with the accuracy 84.21%. Feature extraction of dot location is divided into the top, middle, and bottom. Feature extraction of the number of dotss is done by counting the number of dots, while feature extraction of the presence of holes is carried out by detecting the presence of holes in the characters. These features are applied to the class of results from SVM classification with decision-making rules. The percentage of success in applying the decision rules to the results of the classification of incorporation into 15 classes by SVM reached 92.86%. Further research will be conducted to determine the effect of the feature of the location of the dot and the number of dots on the shape of the main part of the character.

Perencanaan Pompa Air Tenaga Surya Untuk Kebutuhan Non Domestik. (Studi Kasus: Masjid Al-Amin, Kota Subulussalam) Safrizal Safrizal; Riki Effendi
Suara Teknik : Jurnal Ilmiah Vol 12, No 2 (2021): Suara Teknik: Jurnal Ilmiah
Publisher : Fakultas Teknik UM Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29406/stek.v12i2.3127

Air merupakan kebutuhan utama manusia untuk menjaga kesehatan dan keperluan non domestik. Dalam upaya memenuhi kebutuhan air tersebut, beberapa wilayah tidak memiliki sumber air yang layak. Masjid merupakan tempat beribadah orang Islam, kebutuhan air di masjid di kategorikan kebutuhan air non domestik. Salah satu masjid yang memiliki permasalahan air bersih adalah Masjid Al-Amin di Desa Cepu, Kecamatan Penanggalan, Kota Subulussalam, Provinsi Aceh. Dalam upaya memenuhi kebutuhan air bersih di masjid tersebut di desain sebuah Pompa Air Tenaga Surya (PATS). PATS menggunakan energi surya untuk menggerakkan pompa. Alasan desain pompa air bertenaga surya ini untuk memenuhi kebutuhan air masjid serta tidak membebani masjid terhadap tagihan listrik. PATS juga menggunakan sumber energi terbarukan. Tujuan penelitian secara spesifik adalah membuat perencanaan pompa air non domestik berbasis energi surya. Analisis yang dilakukan penelitian ini meliputi radiasi matahari dan kebutuhan daya pompa. Dari analisis tersebut diketahui bahwa kebutuhan air non domestik di masjid Al-Amin adalah sebesar 3.000 liter/hari. Untuk memenuhi kebutuhan air tersebut maka dibutuhkan daya sebesar 0,236 kW yang di suplai dari modul surya. Kata kunci: PATS; air bersih; pompa; modul surya; radiasi matahari.

Penerapan Sistem IoT Berbasis Energi Surya untuk Pemberian Pakan Otomatis dan Pemantauan Kualitas Air pada Budidaya Udang Vaname Razali, Safrizal; Rahman, Aulia; Damora, Adrian
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 1 (2025): JANUARI-MARET 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i1.3346

Vannamei shrimp (Litopenaeus vannamei) merupakan salah satu komoditas utama akuakultur nnasional di Indonesia dengan potensi?ekonomi yang besar. Nonetheless, obstacles like poor water quality and inadequate feed practices prevent sustainable aquaculture. This study aims to design an automatic feeding system for the Internet of Things (IoT) equipped for real-time monitoring of water pH and temperature, powered by solar energy. The system consists of a pH sensor (PH-4502C), a temperature sensor (DS18B20), an ESP32 microcontroller and a Blynk application, which serves as the main interface for the system. The testing was done to prove that this whole system works fine with 2 nos of 100Wp monocrystalline solar panels with 12V 100Ah batter. The system successfully enhances farm operational efficiency, boosts energy sustainability, and offers a novel solution for vannamei shrimp farm management.

Application of the Savitzky-Golay filter in multi-spectral signal processing Syahrial Syahrial; Melinda Melinda; Junidar Junidar; Safrizal Razali; Zulhelmi Zulhelmi
Sriwijaya Electrical and Computer Engineering Journal Vol. 1 No. 1 (2024): Sriwijaya Electrical and Computer Engineering Journal
Publisher : Control and Computational Intelligent System (CoCIS) Research Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62420/selco.v1i1.5

Multi-spectral signals are the result of the interaction between electromagnetic energy and the test material, which is then displayed by the signal fluctuation pattern of the test material. Signal fluctuations are inaccuracies in the peak amplitude of a signal caused by noise in the data. This fluctuation pattern reflects the properties of the test material, especially in this case H2O. To overcome this problem, it is necessary to use the right filter to smooth the signal and reduce the noise in the data so that the fluctuation pattern obtained is clearer and more accurate. This research involves the segmentation of HF fluctuation patterns, followed by the application of a Savitzky-Golay filter for signal smoothing. Signal quality is assessed objectively by calculating the Signal to Noise Ratio (SNR) and Mean Square Error (MSE). The research results show that the Savitzky-Golay filter succeeded in reducing noise and producing clearer fluctuation patterns. The SNR value varies, with the largest value reaching 16.6146 dB, and the smallest value being 3.0171 dB. This research contributes to a new method, namely the Savitzky-Golay adaptive filter, to identify multi-spectral signal fluctuation patterns more effectively, thereby enabling more accurate identification of fluctuation patterns. Apart from that, this research also provides insight into the characteristics of H2O which can be identified through fluctuation patterns, especially in certain segments with high amplitude. This method has potential for applications in various fields, especially in precise multi-spectral signal analysis.

Augmentation of Additional Arabic Dataset for Jawi Writing and Classification Using Deep Learning Razali, Safrizal; Muchtar, Kahlil; Rinaldi, Muhammad Hafiz; Nurdin, Yudha; Rahman, Aulia
Jurnal Rekayasa Elektrika Vol 20, No 1 (2024)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v20i1.33722

This research aims to create an additional dataset containing Arabic characters for writing Jawi script and to train classification models using deep learning architectures such as InceptionV3 and ResNet34. The initial stage of the study involves digital image processing to obtain the additional Arabic character dataset from several sources, including HMBD, AHAWP, and HUCD, encompassing various connected and disconnected forms of Jawi script. Image processing includes steps such as preprocessing to enhance image quality, segmentation to separate Arabic characters from the background, and augmentation to increase dataset variability. Once the dataset is formed, we train the models using appropriate training data for each InceptionV3 and ResNet34 architecture. The classification evaluation results indicate that the model with ResNet34 architecture achieved the best performance with an accuracy of 96%. This model successfully recognizes Jawi script accurately and consistently, even for classes with similar shapes. The main contribution of this research is the availability of the additional Arabic character dataset that can be utilized for Jawi script recognition and performance assessment of various deep learning models. The study also emphasizes the importance of selecting the appropriate architecture for specific character recognition tasks. The research findings affirm that the model with ResNet34 architecture has excellent capability in recognizing the additional Arabic characters for writing Jawi. The results of this research have the potential to support further developments in Jawi character recognition applications and provide valuable insights for researchers in the field of character recognition sourced from Arabic characters. Dataset augmentation results can be accessed at https://singkat.usk.ac.id/g/En0skCKGAR

Development of a self-driving RC car with lane-keeping system using a pure pursuit controller Rahman, Aulia; Alhamdi, Muhammad Jurej; Muchtar, Kahlil; Nurdin, Yudha; Roslidar, Roslidar; Razali, Safrizal; Effendi, Riki
Jurnal Polimesin Vol 23, No 4 (2025): August
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v23i4.6664

The development of autonomous vehicles is crucial for enhancing driving safety, comfort, and efficiency. This research presents the design of a self-driving Remote Controlled (RC) car at a 1:10 scale, equipped with a lane-keeping system and a pure pursuit controller. The primary objective is to evaluate the effectiveness of integrating computer vision techniques with trajectory tracking control to maintain lane stability. Lane detection was achieved using a sliding windows algorithm, while polynomial fitting estimated the lane centerline. A stereo camera provided spatial perception, capturing images that were processed to determine the steering angle needed to minimize deviation between the lookahead point and the viewpoint of the vehicle. Experimental results show that the system-maintained lane position with minimal deviation, achieving an average steering angle of 90.44° on straight paths, 65.4° on right turns, and 113.1° on left turns. These results demonstrate the feasibility of combining vision-based lane detection with a pure pursuit controller to improve path-tracking accuracy and stability in autonomous vehicles.

Co-Authors . Roslidar Adrian Damora Akhyar Bintang Alhamdi, Muhammad Jurej Aulia Rahman Dailami Dailami Fitri Arnia Haimi Ardiansyah Herman Rusli Hilma Erliana Ilham Jaya Junidar Junidar Kahlil Muchtar Luthfi Luthfi Melinda Melinda Muchtar, Kahlil Rahmad Nuthihar Riki Effendi Rinaldi, Muhammad Hafiz Rusdha Muharar Rusdha Muharrar Syahrial Syahrial Wahdaniah Wahyudi Yudha Nurdin Zulhelmi Zulhelmi

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