Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)最新文献_第4页

Application of Deep Convolutional Generative Adversarial Networks to Generate Pose Invariant Facial Image Synthesis Data 深度卷积生成对抗网络在姿态不变人脸图像合成数据中的应用

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-09-30 DOI: 10.29207/resti.v7i5.5112

None Jagad Nabil Tuah Imanda, Fitra Bachtiar, None Achmad Ridok

{"title":"Application of Deep Convolutional Generative Adversarial Networks to Generate Pose Invariant Facial Image Synthesis Data","authors":"None Jagad Nabil Tuah Imanda, Fitra Bachtiar, None Achmad Ridok","doi":"10.29207/resti.v7i5.5112","DOIUrl":"https://doi.org/10.29207/resti.v7i5.5112","url":null,"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","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136344229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Implementation of a Production Monitoring System Using IIoT Based on Mobile Application 基于移动应用的工业物联网生产监控系统的实现

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-09-30 DOI: 10.29207/resti.v7i5.5221

None Gun Gun Maulana, None Siti Aminah, Berlliyanto Aji Nugraha

{"title":"Implementation of a Production Monitoring System Using IIoT Based on Mobile Application","authors":"None Gun Gun Maulana, None Siti Aminah, Berlliyanto Aji Nugraha","doi":"10.29207/resti.v7i5.5221","DOIUrl":"https://doi.org/10.29207/resti.v7i5.5221","url":null,"abstract":"Productivity is a key factor in the success of a company, and real-time monitoring systems are necessary to achieve this goal. Manual data collection is time-consuming and exhausting. Industrial Internet of Things (IIoT) technology has been rapidly advancing in monitoring and optimizing industrial processes. Production processes can be disrupted due to machine problems; hence, the need to analyze machine efficiency using the overall equipment effectiveness (OEE) method. This study implements a system that uses Industrial Internet of Things technology based on mobile application to monitor production processes, report production results, assess machine performance using the OEE method and provide maintenance notifications based on time-based maintenance. Research findings indicate that the production monitoring system implemented on a prototype press machine based on an interactive mobile application interface is capable of monitoring production processes and reporting production results. The system can also assess machine performance using the OEE method, with a calculation accuracy of 99.95% and maintenance notifications with a delay time of 1.04 seconds.","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136278103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Q-Madaline: Madaline Based On Qubit Q-Madaline:基于量子比特的Madaline

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-08-30 DOI: 10.29207/resti.v7i5.5080

K. Hulliyah, Solikhun Solikhun

引用次数: 0

Knowledge Management System Adoption Approach and the Critical Success Factors in Small Medium Enterprise: A Systematic Literature Review 中小企业知识管理系统采用途径与关键成功因素:系统文献综述

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-08-30 DOI: 10.29207/resti.v7i5.4954

Agnes, Ajie Tri Hutama, D. I. Sensuse, Sofian Lusa

{"title":"Knowledge Management System Adoption Approach and the Critical Success Factors in Small Medium Enterprise: A Systematic Literature Review","authors":"Agnes, Ajie Tri Hutama, D. I. Sensuse, Sofian Lusa","doi":"10.29207/resti.v7i5.4954","DOIUrl":"https://doi.org/10.29207/resti.v7i5.4954","url":null,"abstract":"Knowledge is a substantial factor in an organization, therefore successful implementation of Knowledge Management (KM) or Knowledge Management System (KMS) is important thing for many organizations. This applies for both for large companies, as well as for companies categorized as Small Medium Enterprise (SME). How each companies find solution to deal with KM problems, how to adopt KMS in their company’s structure, and what the Critical Success Factors (CSF) need to be highlighted to implement those KMS often vary depending on the size of the organization. Regarding to this issue, this study is aimed to find out how the adoption approach and CSF in the implementation of KM / KMS in SME. On the other hand, this study also can improve the state-of-the-art for KM / KMS implementation in SME and the important CSF in implementing it. A systematic review was performed in this literature review, with the steps as follows: (1) structure the research question, (2) define inclusion-exclusion criteria, (3) paper quality assessment, and (4) data extraction. The study found that in the last 5 years from the time when this research is conducted, TABLE 1which is from 2016 to 2021, SME has been using many methods like training, meeting, sharing session, repository, and research as a part of their KM / KMS adoption approach. We found also in the last 5 years the CSF for implementing KM / KMS in SME are as follows: organization structure and flexibility, organization culture towards KM adoption, the quality of the knowledge, and communication within and across areas in the organization. communication within and across areas of the organization, and team works within and across areas in the organization. SME can use this research as guideline for implementing KM / KMS in their organization.","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131942568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Classification of Secondary School Destination for Inclusive Students using Decision Tree Algorithm 基于决策树算法的包容性学生中学目的地分类

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-08-30 DOI: 10.29207/resti.v7i5.5081

Rizal Prabaswara, Julianto Lemantara, J. Jusak

{"title":"Classification of Secondary School Destination for Inclusive Students using Decision Tree Algorithm","authors":"Rizal Prabaswara, Julianto Lemantara, J. Jusak","doi":"10.29207/resti.v7i5.5081","DOIUrl":"https://doi.org/10.29207/resti.v7i5.5081","url":null,"abstract":"Inclusive student education has become one of the most important agendas for UNESCO and the Indonesian government. Developing inclusive children's education is critical to adjust their abilities while attending school. However, most parents and educators who assist students in selecting their future secondary school after finishing primary school are frequently not aware of their genuine ability. The problem is mainly because the decision is not based on objective assessments like IQ, average and mental scores. In this study, we aims to create a school-type decision support system using data mining as a factor analytic approach in extracting 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. Evaluation showed that the proposed system produced an accuracy of 90% by allocating 75% of data for training and 25% for testing. The accuracy value from evaluation phase stated that the ID3 Decision tree algorithm have a good peformance. This system also can dynamically create new decision trees based on newly added datasets. Further research is expected to have more variable and more dynamic system that can have more accurate result for the inclusive student classification of secondary school.","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121307488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Combination of K-NN and PCA Algorithms on Image Classification of Fish Species 结合K-NN和PCA算法的鱼类图像分类

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-08-30 DOI: 10.29207/resti.v7i5.5178

Rini Nuraini, Adi Wibowo, B. Warsito, W. Syafei, I. Jaya

引用次数: 0

Fatigue Detection Through Car Driver’s Face Using Boosting Local Binary Patterns 基于增强局部二值模式的驾驶员面部疲劳检测

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-08-30 DOI: 10.29207/resti.v7i5.4798

Grandhys Setyo Utomo, Ema Rachmawati, Febryanti Sthevanie

引用次数: 0

Using Histogram Extracted from Satelite Imagery and Convolutional Network to Predict GRDP in Java Region 基于卫星图像直方图和卷积网络的Java地区GRDP预测

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-08-30 DOI: 10.29207/resti.v7i5.5092

Oemar Syarief Wibisono, A. M. Arymurthy, socio-Oemar Syarief, Aniati Murni Wibisono, Arymurthy

{"title":"Using Histogram Extracted from Satelite Imagery and Convolutional Network to Predict GRDP in Java Region","authors":"Oemar Syarief Wibisono, A. M. Arymurthy, socio-Oemar Syarief, Aniati Murni Wibisono, Arymurthy","doi":"10.29207/resti.v7i5.5092","DOIUrl":"https://doi.org/10.29207/resti.v7i5.5092","url":null,"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 uses GRDP data. However, the GRDP data issued by BPS has a deficiency, it was released after the current year, and this figure is provisional. So, 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 development inequality in a region. Night-time Light (NTL) satellite imagery data can be an alternative to see socio-economic activity in an area and has been shown to have a strong correlation with socio-economic 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. By using a histogram, we don’t 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 accuracy with an R square value of 0.8549, beating the baseline method with two-dimensional convolutional networks. The use of Huber loss function can improve the performance of the model, which has a smaller total loss and have smoother gradient.","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127846544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Implementation of System Development Life Cycle (SDLC) on IoT-Based Lending Locker Application 系统开发生命周期(SDLC)在物联网借贷柜应用中的实现

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-08-22 DOI: 10.29207/resti.v7i4.5047

M. Melinda, Shaquille Rizki Ramadhan Na, Yudha Nurdin, Yunidar Yunidar

{"title":"Implementation of System Development Life Cycle (SDLC) on IoT-Based Lending Locker Application","authors":"M. Melinda, Shaquille Rizki Ramadhan Na, Yudha Nurdin, Yunidar Yunidar","doi":"10.29207/resti.v7i4.5047","DOIUrl":"https://doi.org/10.29207/resti.v7i4.5047","url":null,"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 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 1 prototype lending locker. The locker-based online lending system integrated with ESP32-WROOM-32 can connect with Firebase storage and send locker key codes to Firebase so 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 System Usability Scale (SUS) average score with a very feasible interpretation category","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123324676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploring Research Trends and Impact: A Bibliometric Analysis of RESTI Journal from 2018 to 2022 研究趋势与影响:2018 - 2022年RESTI期刊文献计量分析

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-08-13 DOI: 10.29207/resti.v7i4.5101

Ronal Watrianthos, Yuhefizar Yuhefizar

{"title":"Exploring Research Trends and Impact: A Bibliometric Analysis of RESTI Journal from 2018 to 2022","authors":"Ronal Watrianthos, Yuhefizar Yuhefizar","doi":"10.29207/resti.v7i4.5101","DOIUrl":"https://doi.org/10.29207/resti.v7i4.5101","url":null,"abstract":"This study provides a comprehensive analysis of the RESTI Journal, a prominent publication in the field of systems engineering and information technology. The analysis aims to evaluate the journal's publication output, citation impact, and overall contribution to the field. The study utilizes data from the Dimensions database, focusing on articles published between 2018 and 2022, resulting in a dataset of 594 articles. To analyze the collected data, the study employs bibliometric and network visualization tools such as Bibliometrix and VOSviewer. The analysis reveals a notable increase in the number of publications over time, indicating a growing interest and research activity in the field. Furthermore, the distribution of author productivity deviates from Lotka's law, highlighting variations in author patterns and productivity levels. An examination of institutional affiliations reveals Telkom University as the dominant institution, making a substantial contribution to the journal. Visualizations based on author-provided titles, abstracts, and keywords highlight research trends in image recognition and classification, with a particular emphasis on utilizing Convolutional Neural Networks (CNN) and Support Vector Machines (SVM). Overall, this study provides valuable insights into the performance and trends of the RESTI Journal. The findings contribute to a deeper understanding of the journal's impact and its role in advancing knowledge in systems engineering and information technology. These insights can inform researchers, practitioners, and stakeholders in the field, guiding future research directions and enhancing the scholarly impact of the RESTI Journal.","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116437974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0