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Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Published by Ikatan Ahli Informatika Indonesia
ISSN : 25800760     EISSN : 25800760     DOI : https://doi.org/10.29207/resti.v2i3.606
Core Subject : Science, Engineering,
Computer Science & IT Engineering
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) dimaksudkan sebagai media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai penelitian Rekayasa Sistem, Teknik Informatika/Teknologi Informasi, Manajemen Informatika dan Sistem Informasi. Sebagai bagian dari semangat menyebarluaskan ilmu pengetahuan hasil dari penelitian dan pemikiran untuk pengabdian pada Masyarakat luas dan sebagai sumber referensi akademisi di bidang Teknologi dan Informasi. Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) menerima artikel ilmiah dengan lingkup penelitian pada: Rekayasa Perangkat Lunak Rekayasa Perangkat Keras Keamanan Informasi Rekayasa Sistem Sistem Pakar Sistem Penunjang Keputusan Data Mining Sistem Kecerdasan Buatan/Artificial Intelligent System Jaringan Komputer Teknik Komputer Pengolahan Citra Algoritma Genetik Sistem Informasi Business Intelligence and Knowledge Management Database System Big Data Internet of Things Enterprise Computing Machine Learning Topik kajian lainnya yang relevan
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 1,046 Documents
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Robust Digital Watermarking pada Arsip Vital Mnggunakan Metode Hybrid SVD Dengan DWT Alita Wulan Dini; Shelvie Nidya Neyman; Toto Haryanto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 5 (2023): October 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i5.5003

Abstract

The development of Internet technology affects the dissemination of data, especially in vital government archives. This research uses a hybrid singular value decomposition (SVD) and discrete wavelet transform (DWT) method, which aims to protect the copyright of vital archives. The stages of the insertion and extraction process are carried out to test the effect of the alpha value on the quality (imperceptibility) and robustness of the inserted image by measuring the Peak Signal-to-Noise Ratio (PSNR), verifying similarity by measuring the Normalized Cross-Correlation (NC) and Structural Similarity Index (SSIM). The results of research with ten vital archives and a watermark protection logo in JPEG format with a size of 512x512 pixels obtained a maximum PSNR with a value of α = 0.01 of 41.0567 dB, NC of 0.98904, and SSIM of 0.98023 in the Cibereum Land Certificate. So, it can be proven that this method produces vital archive watermarks that can be extracted and are robust to JPEG compression attacks of 75%, median filtering 3x3, Gaussian noise 0.01, speckle noise 0.01, and salt and pepper noise 0.01 but not resistant to rotation 80 and cropping attacks 2%.
Service Automation Implementation for Delivering CaaS at the Ministry of Finance of Indonesia Achmad Farid Rusdi; Bob Hardian; Teguh Raharjo; Tiarma Simanugkalit
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 5 (2023): October 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i5.5032

Abstract

Evaluation is an essential aspect of service improvement. Within the Ministry of Finance, there is an organization responsible for providing IT services to various units and employees. One of the services offered by this organization is cloud computing, which supports the development of information systems. However, there are several challenges related to service fulfillment. For instance, the time required to fulfill a service is relatively long, taking two days, in contrast to public cloud providers, which can deliver their services in minutes. Additionally, there is a potential for human errors in the manual process carried out by the Request Fulfillment Team (RFT) during service delivery. This study aims to explore the design and implementation of automated container service fulfillment, transforming them into self-service products. The author employs the Finite-State Automata (FSA) model to test the input and output of the automation system using seven states and inputs. The results indicate that the container service cycle, when compiled and tested with FSA using predetermined inputs, can generate containers according to user-selected specifications. As a result, the implementation of an automated and self-service model is proposed to reduce delivery time and mitigate potential errors in the container-as-a-service (CaaS) offering.
Deteksi Logo Kendaraan dengan MSER-Vertical Sobel Gamma Kosala; Agus Harjoko; Sri Hartati
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 5 (2023): October 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i5.5034

Abstract

Detecting a vehicle logo is the first step before realizing the identity of the logo. However, the detection of logos can pose difficulties due to various factors, including logo variations, differing scales and orientations, background interference, varying lighting conditions, and partial obstruction. This paper presents a vehicle logo detection method using hand-crafted features. We used a combination of Maximally Stable Extremal Region (MSER) and Vertical Sobel. We combine vertical Sobel with MSER to overcome MSER's limitation in recognizing objects of different sizes. These two features are merged using a closing morphology operation to form blobs selected as logo candidate areas. Moreover, a Support Vector Machine (SVM) is implemented to choose a logo area by analyzing each candidate's Histogram of Oriented Gradient (HOG). The proposed method was compared with other methods by implementing them on the same dataset. The significant advantage of using MSER-Vertical Sobel is its fast computation time. It is faster than other approaches that use non-handcrafted features. The test results show that the MSER-Vertical Sobel can achieve high accuracy and the fastest computation time.
Implementation of System Development Life Cycle (SDLC) on IoT-Based Lending Locker Application Melinda Melinda; Shaquille Rizki Ramadhan Na; Yudha Nurdin; Yunidar Yunidar
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 4 (2023): August 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i4.5047

Abstract

Libraries are social institutions that provide information services that can be accessed publicly to meet the information needs of librarians. Based on the results of a survey conducted on 58 students who have visited the library of the Electrical and Computer Engineering Department of the Universitas Syiah Kuala, an information system was needed that provided research book information related to the author's name, year of writing, field concentration, and abstract of the research book, and there was a division of categories based on field concentration, and there was an online borrowing feature. Based on these problems, this study aims to implement an Android application system with IoT-based lending lockers using the SDLC (system development life cycle) prototyping method. This study produces an application with a locker-based online lending feature, several other features as the user desires, and one prototype lending locker. The locker-based online lending system integrated with ESP32-WROOM-32 can connect to Firebase storage and send locker key codes to Firebase so that the application can access them. Through experiments and tests conducted on the application, it is obtained that the application can access the locker key code and display it to the user. The application has also been validated using black-box and white-box testing and can be accepted by users based on the System Usability Scale (SUS) average score with a very feasible interpretation category.
Q-Madaline: Madaline Based On Qubit Khodijah Hulliyah; Solikhun Solikhun
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 5 (2023): October 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i5.5080

Abstract

This research focuses on developing the MADALINE algorithm using quantum computing. Quantum computing uses binary numbers 0 or 1 or a combination of 0 and 1. The main problem in this research is how to find other alternatives to the MADALINE algorithm to solve pattern recognition problems with a quantum computing approach. The data used in this study are heart failure data to predict whether a patient is at risk of death. The data source comes from KAGGLE, consisting of 299 data with 12 symptoms and one target, alive or dead. The result of this study is an alternative to the MADALINE algorithm that uses quantum computing. The precision of the test results with MADALINE with a learning rate of 0.1 = 100% with 2 epochs. The accuracy of the test results using a quantum approach with a learning rate of 0.1 is 85.71%. The results of this study can be an alternative to the MADALINE algorithm with a quantum computing approach, although it has not shown better accuracy than the classical MADALINE algorithm. More research is needed to produce better accuracy with larger data.
Classification of Secondary School Destination for Inclusive Students using Decision Tree Algorithm Rizal Prabaswara; Julianto Lemantara; Jusak Jusak
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 5 (2023): October 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i5.5081

Abstract

Inclusive student education has become one of the most important agendas of UNESCO and the Indonesian government. Developing an inclusive education for children is critical to adapt to their abilities while attending school. However, most parents and educators who help students select their future secondary school after finishing primary school are often unaware of their real potential. The problem is mainly because the decision is not based on objective assessments such as IQ, average, and mental scores. In this study, our objective is to create a school-type decision support system using data mining as a factor-analytic approach to extract rules for the knowledge model. The system uses some variables as the basic principles for building school-type classification rules using the ID3 decision tree method. This system can also assist educators in making decisions based on existing graduate data. The evaluation showed that the proposed system produced an accuracy of 90% by allocating 75% of the data for training and 25% for testing. The accuracy value from the evaluation phase stated that the ID3 decision tree algorithm performs well. This system can also dynamically create new decision trees based on newly added datasets. More research is expected to result in a more variable and dynamic system that can have a more accurate result for the inclusive student classification of secondary school.
Penerapan E-Test Pada Mata Pelajaran Bahasa Inggris Menggunakan Model View Controller Sri Restu Ningsih; Erdisna Erdisna; Febriyanno Suryana; Yenni Desnelita; Silfia Andini
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 5 (2023): October 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i5.5090

Abstract

The problem that occurs in one of the high schools is that there is no online-based English exam system, and they still use paper for their assessments. This makes teachers unable to give exams to students if they do not attend school. The purpose of this research is to create an online exam system to facilitate exam administration using the Model View Controller (MVC) to assess online English exams. The analytical method uses the System Usability Scale (SUS), to collect data using an electronic test (e-Test).Unifield Modeling Language (UML), a visual modeling technique used in designing and building object-oriented software for E-Test applications.The results showed that the use of the E-test application in a comparison class in English subjects could improve student learning outcomes to a higher level, from a score of 81.7 to 90.9. Compared to the control class, there was a slight increase, namely an increase in value from 71.5 to 75.8. This proves that the E-test application is used effectively by students for English subjects.
Using Histogram Extracted From Satelite Imagery and Convolutional Network to Predict GRDP in Java Region Oemar Syarief Wibisono; Aniati Murni Arymurthy
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 5 (2023): October 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i5.5092

Abstract

Inequality is one of the problems faced by all countries in the world, including Indonesia. The data used to measure development inequality between regions mostly use GRDP data. However, the GRDP data issued by BPS has a deficiency, it was released after the current year, and this figure is provisional. Therefore, a new data source is needed that can be used to estimate the value of economic activity so that it can be used to measure the level of inequality in development in a region. Nighttime Light (NTL) satellite imagery data can be an alternative to see socioeconomic activity in an area and have been shown to have a strong correlation with socioeconomic activity. In this study, we used VIIRS NTL satellite imagery data and Dynamic World land cover data to estimate GRDP. Rather than using statistical features for each area of interest, we use features in the form of histograms extracted from NTL images and land cover images for each area of interest. Using a histogram, we do not lose spatial information from satellite imagery. Then we proposed a deep learning method in the form of a one-dimensional convolutional neural network using the Huber loss function. This model obtained good precision with an R-square value of 0.8549, beating the baseline method with two-dimensional convolutional networks. The use of the Huber loss function can improve the performance of the model, which has a smaller total loss and has a smoother gradient.
Faktor-faktor Utama untuk Meningkatkan Kualitas Kerja Tim di Startup Indonesia menggunakan Kerangka aTWQ Muhammad Fathin; Teguh Raharjo
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 5 (2023): October 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i5.5099

Abstract

Due to the ever-changing needs of IT in today's businesses, agile software development has become popular due to its adaptive capabilities. Startups are among those who continuously strive to meet changing needs. Despite the potential benefits of the Agile methodology, teamwork quality remains a challenge. Furthermore, the global recession has made it increasingly important for startups to have effective teamwork, given the high level of uncertainty that leads to challenges in surviving, especially with cost-cutting and downsizing efforts. Therefore, this study aims to evaluate teamwork quality in Indonesian startups using the Agile Teamwork Quality (aTWQ) approach. TWQ is a comprehensive set of criteria designed to assess teamwork quality in agile environments. The primary objective of this study is to identify the factors that most strongly increase the quality of teamwork of Indonesian startups. To achieve this objective, data will be collected from Indonesian companies using an online survey based on the aTWQ framework. The challenges were identified most on the dimensions of cohesion, balance of contribution, and effort. The findings of this study are consistent with previous research, which may hopefully help start-ups in Indonesia improve their teamwork quality and achieve greater success in their respective industries.
Application of Deep Convolutional Generative Adversarial Networks to Generate Pose Invariant Facial Image Synthesis Data Jagad Nabil Tuah Imanda; Fitra Bachtiar; Achmad Ridok
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 5 (2023): October 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i5.5112

Abstract

The field of technology is currently developing rapidly, one of the developments is artificial intelligence. Artificial intelligence can still find it difficult to solve problems that are easy for humans to do but difficult for computers to describe, such as facial recognition. There are still several problems related to the existing facial recognition model, namely, the facial recognition model is still unable to recognize facial shapes that are not in a perfect state due to several factors such as face position, lighting, expression, and obstacles covering the face. Among these several factors, the most influencing factor is the position of the face. Therefore, in this study, deep convolutional generative adversarial networks (DCGANs) will be applied to generate fake image data with varying face positions. This research will be carried out starting from collecting data, processing data, designing and training models, hyperparameter tuning, and lastly analyzing test results. Based on the results of hyperparameter tuning that were performed sequentially, the best hyperparameter combination produced is 200 epoch, 0.002 Generator learning rate, 0.5 Generator momentum/beta1, Adam as Generator optimizer, 0.0002 Discriminator learning rate, 0.5 Discriminator momentum/beta1, and Adam as Discriminator optimizer. The combination of hyperparameters gives a result with an FID score of 74.05. Based on testing with human observers, generated fake images have relatively good results, but there are still few bad fake image results

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