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All Journal International Journal of Electrical and Computer Engineering Seminar Nasional Aplikasi Teknologi Informasi (SNATI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) JETT (Jurnal Elektro dan Telekomunikasi Terapan) IT JOURNAL RESEARCH AND DEVELOPMENT TECHNO-SOCIO EKONOMIKA Jurnal Nasional Teknik Elektro dan Teknologi Informasi eProceedings of Applied Science eProceedings of Engineering Jurnal Rekayasa elektrika Jurnal INFOTEL Jurnal Hukum, Administrasi Publik dan Negara Proceeding of Community Service and Engagement
Suci Aulia
Telkom Univeristy
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Desain Prototype Sistem Kendali dan Pelacakan Pada Mesin Boat Rizky Edi Saputra; Suci Aulia; Syahban Rangkuti
Jurnal Rekayasa Elektrika Vol 17, No 2 (2021)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (815.344 KB) | DOI: 10.17529/jre.v17i2.19900

Abstract

Indonesia is an archipelago country with more than 70% of its territory consisting of water. Due to these geographical conditions, many Indonesian people rely on water transportation as a means of crossing transportation. However, many of the crossings in Indonesia still use a manual control system in determining the direction of the boat. In this study, a prototype control and tracking system designed for a boat engine can be used as an automatic control system (autopilot) in water transportation. This system is created using a waypoint control system that can navigate automatically to a predetermined location. This control system is designed with an electric control system that utilizes a microcontroller, GPS (Global Positioning System) module, and compass module as a navigation control device. From the test results, it can be concluded that the level of accuracy of the GPS coordinates reading is as far as 4.8 meters and based on the test of the waypoint navigation system , the system accuracy level is 10.8 meters.
Human height and weight classification based on footprint using gabor wavelet and K-NN methods Ryan Bagus Wicaksono; Suci Aulia; Sugondo Hadiyoso; Bambang Hidayat
JURNAL INFOTEL Vol 14 No 2 (2022): May 2022
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v14i2.728

Abstract

Height and weight are parameters to identify a person, especially for a forensic. To identify height and weight is usually done manually. In addition to manually using height measuring devices and scales, you can also use information related to the foot length. There is a relationship between height and foot length can be expressed in the correlation coefficient (r) as same as for weight. Therefore, in this study, a system for measuring human height and weight based on images of the footprint is implemented on Android. The methods used in this study are Gabor Wavelet and k-Nearest Neighbor (k-NN). The simulation results generate the best accuracy of 75%. The system can also used to categorize the ideal body level according to the Body Mass Index (BMI). The system is able to process images with an average computation time of 8.92 seconds.
Classification of Koilonychia, Beaus Lines, and Leukonychia based on Nail Image using Transfer Learning VGG-16 Sugondo Hadiyoso; Suci Aulia
Jurnal Rekayasa Elektrika Vol 18, No 2 (2022)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v18i2.25694

Abstract

Human nail disease is usually ignored since it does not reveal clinical signs that are harmful to one's health. Nail disease, on the other hand, can be an early sign of a health issue. Some types of nail disease can cause infection, injury, or even the loss of the nail itself. It can reduce a person's aesthetics and beauty. Nail disease is very varied, so it is often difficult for clinicians to diagnose because several types have high similarities. Therefore, an automatic nail disease classification method based on nail photos was proposed in this study. The proposed method was based on the VGG-16 neural network architecture with an Adam optimizer. Nail diseases including Koilonychia, Beaus Lines, Leukonychia have been classified in this study. The model in this study is simulated in Python programming. The simulation results show that the highest classification accuracy is 96%, achieved with epoch-10. The transfer learning method based on a neural network simulated in this study is expected to support the clinical diagnosis of nail disease.
Abnormal ECG Classification using Empirical Mode Decomposition and Entropy Suci Aulia; Sugondo Hadiyoso
Jurnal Rekayasa Elektrika Vol 17, No 3 (2021)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v17i3.22070

Abstract

Heart disease is one of the leading causes of death in the world. Early detection followed by therapy is one of the efforts to reduce the mortality rate of this disease. One of the leading medical instruments for diagnosing heart disorders is the electrocardiogram (ECG). The shape of the ECG signal represents normal or abnormal heart conditions. Some of the most common heart defects are atrial fibrillation and left bundle branch block. Detection or classification can be difficult if performed visually. Therefore in this study, we propose a method for the automatic classification of ECG signals. This method generally consists of feature extraction and classification. The feature extraction used is based on information theory, namely Fuzzy entropy and Shannon entropy, which is calculated on the decomposed signal. The simulated ECG signals are of three types: normal sinus rhythm, atrial fibrillation, and left bundle branch block. Support vector machine and k-Nearest Neighbor algorithms were employed for the validation performance of the proposed method. From the test results obtained, the highest accuracy is 81.1%. With specificity and sensitivity of 79.4% and 89.8%, respectively. It is hoped that this proposed method can be further developed to assist clinical diagnosis.
Pengenalan Pola Berbasis OCR untuk Pengambilan Data Bursa Saham M. Dyovan Uidy Okta; Suci Aulia; Burhanuddin Burhanuddin
Jurnal Rekayasa Elektrika Vol 17, No 2 (2021)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v17i2.19656

Abstract

The investor must be able to use instinct to evaluate when to sell and buy stocks. This is, of fact, a weakness for inexperienced investors, in addition to the decision's inaccuracy and the time it takes to evaluate a slew of ineffective results. So that, a support system is needed to help the investors make decisions in buying and selling shares. This support system creates an online analysis curve display through text data in the BEI stock price application. The data processing based on pattern recognition will be carried out so that a buying and selling decision can be made to calculate the profit and loss by investors. As the first step of the whole system, this research has built an image-to-text conversion system based on OCR (Optical Character Recognition) that can convert the non-editable text (.jpg) to be editable (.text) online. After obtaining this .text data, the will used the system in further research to analyze stock buying and selling decisions. According to research on eight companies, the OCR-based image to text conversion has a 96.8% accuracy rate. Meanwhile, using Droid serif, Takao PGhotic, and Waree fonts at 12pt font sizes, it has 100 percent accuracy in Libre Office. 
Multi-Class Heart Abnormalities Detection Based on ECG Graph Using Transfer Learning Method Sugondo Hadiyoso; Suci Aulia; Indrarini Dyah Irawati
Jurnal Rekayasa Elektrika Vol 19, No 1 (2023)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v19i1.28637

Abstract

The heart is one of the vital organs in the circulatory system. Regular checkups are very important to prevent heart disease. The most basic examination is blood pressure then further examination is related to the evaluation of the electrical activity of the heart using an electrocardiogram (ECG). The ECG carries important information regarding various abnormalities of heart function. Several automated classification techniques have been proposed to facilitate diagnosis. However, not all digital ECG devices provide raw data for analysis. ECG classification method based on images can be an alternative in classification. Therefore, in this study, it is proposed to classify ECG based on signal images. The proposed classification method uses transfer learning with VGG, AlexNet, and DenseNet architectures. The method used for the classification of multi-class ECG consists of normal, PVC, Atrial Fibrilation, AFL, Bigeminy, LBBB, and APB. The simulation results generate the best accuracy of 92% and F1-score of 92%. Best performance is achieved using DenseNet architecture at 60 epochs. This study is expected to be a new reference technique in the classification of ECG signals.
A Prototype of Parking Space Information System based on Image Processing Aaron Abel; Suci Aulia; Dadan Nur Ramadhan; Sugondo Hadiyoso
Jurnal Rekayasa Elektrika Vol 17, No 3 (2021)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v17i3.21556

Abstract

An automatic parking system has been proposed to make the car parking process more efficient in terms of time and cost. The absence of information on the position of the parking lot makes the car driver take longer to find it. In multi-story parking lots, officers cannot constantly monitor the available parking conditions directly, so prospective parking users do not know the position of the open parking space. In addition, many parking lots use automatic door latch, but no parking space information display. Parking system automation can be based on hardware, software, or a combination of hardware and software. To the best of our knowledge, no software-based framework is entirely used on this system. Therefore, this study proposes an automatic parking system based on camera sensors and software, which is combined into an information system. The proposed method uses simple morphological operations. Based on the test results, the detection accuracy achieved is 100% with a light intensity of 3 lux, 15 lux, 30 lux, 60 lux, 120 lux, and 250 lux. The average processing time is 1.59 seconds. From this study, it is hoped that this prototype can be tested on relevant environmental conditions so that the prototype can be implemented in parking lots.
Deteksi Kantuk pada Pengemudi Berdasarkan Penginderaan Wajah Menggunakan PCA dan SVM Nur Ramadhani; Suci Aulia; Efri Suhartono; Sugondo Hadiyoso
Jurnal Rekayasa Elektrika Vol 17, No 2 (2021)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v17i2.19884

Abstract

Drowsiness while driving is one of the main causes of traffic accidents it affects the level of focus of the driver. Therefore, we need an automatic drowsiness detection mechanism for the driver to provide a warning or alarm so that an accident can be avoided. In this study, we design and simulate a system to detect drowsiness through the driver’s yawn expression. The acquisition is made by recording the face from two shooting points including the dashboard and front mirrors in the car. From the video recording, then it is taken into several images with a size of 128x82 pixels which are used as training and testing data. This image is then processed using Principal Component Analysis (PCA) for feature extraction and classified using a Support Vector Machine (SVM). From the tests carried out, the system generates the highest accuracy of 98%. This best performance is obtained by SVM with polynomial kernel in the camera position on the dashboard. Meanwhile, based on compression testing, the image that can still meet system requirements is 25% of the original size. It is hoped that the proposed drowsiness detection method in this study can be applied for real-time drowsiness detection in vehicles. 
Desain Prototype Sistem Kendali dan Pelacakan Pada Mesin Boat Rizky Edi Saputra; Suci Aulia; Syahban Rangkuti
Jurnal Rekayasa Elektrika Vol 17, No 2 (2021)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v17i2.19900

Abstract

Indonesia is an archipelago country with more than 70% of its territory consisting of water. Due to these geographical conditions, many Indonesian people rely on water transportation as a means of crossing transportation. However, many of the crossings in Indonesia still use a manual control system in determining the direction of the boat. In this study, a prototype control and tracking system designed for a boat engine can be used as an automatic control system (autopilot) in water transportation. This system is created using a waypoint control system that can navigate automatically to a predetermined location. This control system is designed with an electric control system that utilizes a microcontroller, GPS (Global Positioning System) module, and compass module as a navigation control device. From the test results, it can be concluded that the level of accuracy of the GPS coordinates reading is as far as 4.8 meters and based on the test of the waypoint navigation system , the system accuracy level is 10.8 meters.
Analisis Pengawasan Melekat (WASKAT) terhadap Kinerja Pegawai di Kantor Lurah Bukit Kapur Kota Dumai Dwi Nuha Nabilah; Siti Nurlaila; Suci Aulia; Nurmala Sari
Jurnal Hukum, Administrasi Publik dan Negara Vol. 3 No. 1 (2026): Januari: Jurnal Hukum, Administrasi Publik dan Negara
Publisher : Asosiasi Peneliti Dan Pengajar Ilmu Sosial Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/hukum.v3i1.852

Abstract

This study analyzes the effectiveness of installed supervision (Waskat) by the Sub-district Head on the performance of employees at the Bukit Kapur District Office, Dumai City, in the midst of the demands of public service accountability. The background involves local bureaucratic challenges such as resource constraints and employee resistance. Using a qualitative approach with field observation for two weeks (15-29 December 2025), including in-depth interviews with 5 employees and 2 community informants, plus data triangulation from attendance records and performance reports, it was analyzed thematically. The results revealed attendance increased to 95%, absenteeism decreased by 2%, and work output increased from 50 to 65 permit documents each week. Quotes such as "Direct supervision motivates me" (Employee A, 2025) affirm the preventive role of Waskat, despite obstacles such as over-tasking, in line with Fauzan (2024) on civil servant governance. The discussion highlighted Waskat as a tool for local bureaucratic reform. This conclusion affirms the effectiveness of Waskat in improving performance, recommending humanistic and digital adaptation. Policy implications for local governments, with suggestions for future studies using a larger sample.
Co-Authors Aaron Abel Abraham Caesar Yanuar Putra Adri Achmad Farhan Agus Gunarso Alvinas Deva Sih Illahi Alya Khalisa Nadira Amri Khurniawan Anatasya Bella Andik Wijanarko Angga Rusdinar Ardyandrea Erstya Surya Arif Setiawan Arif Setiawan Asep Mulyana ATIK NOVIANTI Audry Stevany Aulia Ayu Dyah Aulia Ayu Dyah Lestari Aulya Ellanda Bagus Budhi L. Bambang Hidayat Bayuaji Kurniadhani Burhanuddin Burhanuddin Burhanuddin D. Dadan Nur Ramadan Dadan Nur Ramadhan Della Oktriani Denny Darlis Didin Yulian Dimitri Mahayana Diovani Estidia Akbar Dwi Nuha Nabilah Efri Suhartono Erizka Banuwati Candrasari Erty Kasdiantika Fony Ferliana Widianingrum Galuh Laksmita Ranggi Gelar Budiman Grislend Gloria Natalies Hafiddudin Hafiddudin Hafidudin Hafiidh As Syahidulhaq Hafiz Adriansyah Handoko Supeno Hengki Setiadi Indrarini Dyah Irawati Inung Wijayanto Jean Pierre Uwiringiyimana Khairunnisa Alfiyanti Suharja Kusumawardhani, Eka Ledya Novamizanti Lestari Lestari M. Dyovan Uidy Okta Meidi Mahendra Rahmatullah Melina Melina Muhammad Alfachri Akbar Muhammad Arly Gunawan Muhammad Biyan Priatama Muhammad Iqbal Muhammad Iqbal Muhammad Obi Nugraha Muhammad Obi Nugraha Muhammad Panji Kusuma Praja Muhammad Rafki Nur Ramadhani Nuril Amri Ependi Nurmala Sari Patricia Lovenia Garcia Raditiana Patmasari Rahmat Sopian Rajali Ginting Ratri Dwi Atmaja Raymond Y. Purba Reivind P. Persada Restu Wardani Ridha Muldina Negara Rita Magdalena Rita Purnamasari Rizky Edi Saputra Rudy Gunawan Ryan Bagus Wicaksana Ryan Bagus Wicaksono Ryandhika Gumelar Siti Nurlaila Siti Syahnah Siti Syahnah Syahrial Sri Dewi Sartika Sugondo Hadiyoso Syahban Rangkuti Syahrial Thoriq Dharmawan Unang Sunarya Viona Apryaleva Yafis Sukma Kurniawan YULI SUN HARIYANI Yuyun Siti R. YUYUN SITI ROHMAH