Journal of Applied Intelligent System最新文献_第2页

Conditional Matting For Post-Segmentation Refinement Segment Anything Model 分段后细化的条件匹配任何分段模型

Journal of Applied Intelligent System Pub Date : 2023-11-30 DOI: 10.33633/jais.v8i3.9024

Al Birr Karim Susanto, M. Soeleman, Fikri Budiman

{"title":"Conditional Matting For Post-Segmentation Refinement Segment Anything Model","authors":"Al Birr Karim Susanto, M. Soeleman, Fikri Budiman","doi":"10.33633/jais.v8i3.9024","DOIUrl":"https://doi.org/10.33633/jais.v8i3.9024","url":null,"abstract":"Segment Anything Model (SAM) is a model capable of performing object segmentation in images without requiring any additional training. Although the segmentation produced by SAM lacks high precision, this model holds interesting potential for more accurate segmentation tasks. In this study, we propose a Post-Processing method called Conditional Matting 4 (CM4) to enhance high-precision object segmentation, including prominent, occluded, and complex boundary objects in the segmentation results from SAM. The proposed CM4 Post-Processing method incorporates the use of morphological operations, DistilBERT, InSPyReNet, Grounding DINO, and ViTMatte. We combine these methods to improve the object segmentation produced by SAM. Evaluation is conducted using metrics such as IoU, SAD, MAD, Grad, and Conn. The results of this study show that the proposed CM4 Post-Processing method successfully improves object segmentation with a SAD evaluation score of 20.42 (a 27% improvement from the previous study) and an MSE evaluation score of 21.64 (a 45% improvement from the previous study) compared to the previous research on the AIM-500 dataset. The significant improvement in evaluation scores demonstrates the enhanced capability of CM4 in achieving high precision and overcoming the limitations of the initial segmentation produced by SAM. The contribution of this research lies in the development of an effective CM4 Post-Processing method for enhancing object segmentation in images with high precision. This method holds potential for various computer vision applications that require accurate and detailed object segmentation.","PeriodicalId":289013,"journal":{"name":"Journal of Applied Intelligent System","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139208640","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

Enhancing Augmentation-Based Resnet50 for Car Brand Classification 增强基于增强的 Resnet50，用于汽车品牌分类

Journal of Applied Intelligent System Pub Date : 2023-11-30 DOI: 10.33633/jais.v8i3.9385

Triga Agus Sugiarto, M. Soeleman, Pujiono Pujiono

{"title":"Enhancing Augmentation-Based Resnet50 for Car Brand Classification","authors":"Triga Agus Sugiarto, M. Soeleman, Pujiono Pujiono","doi":"10.33633/jais.v8i3.9385","DOIUrl":"https://doi.org/10.33633/jais.v8i3.9385","url":null,"abstract":"This research focuses on car classification and the use of the ResNet-50 neural network architecture to improve the accuracy and reliability of car detection systems. Indonesia, as one of the countries with high daily mobility, has a majority of the population using cars as the main mode of transportation. Along with the increasing use of cars in Indonesia, many automotive industries have built factories in this country, so the cars used are either local or imported. The importance of car classification in traffic management is a major concern, and vehicle make and model recognition plays an important role in traffic monitoring. This study uses the Vehicle images dataset which contains high-resolution images of cars taken from the highway with varying viewing angles and frame rates. This data is used to analyze the best- selling car brands and build car classifications based on output or categories that consumers are interested in. Digital image processing methods, machine learning, and artificial neural networks are used in the development of automatic and real-time car detection systems.The ResNet-50 architecture was chosen because of its ability to overcome performance degradation problems and study complex and abstract features from car images. Residual blocks in the ResNet architecture allow a direct flow of information from the input layer to the output layer, overcoming the performance degradation problem common in neural networks. In this paper, we explain the basic concepts of ResNet-50 in car detection and popular techniques such as optimization, augmentation, and learning rate to improve performance and accuracy. in this study, it is proved that ResNet has a fairly high accuracy of 95%, 92% precision, 93% recall, and 92% F1-Score.","PeriodicalId":289013,"journal":{"name":"Journal of Applied Intelligent System","volume":"57 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139205882","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 Chatbot on Discord for Information Assistance and Conflict Prevention 在 Discord 上实施聊天机器人，以提供信息援助和预防冲突

Journal of Applied Intelligent System Pub Date : 2023-11-30 DOI: 10.33633/jais.v8i3.9089

Zudha Pratama, Ery Mintorini, Karmila Karmila, Didik Hermanto

{"title":"Implementation Chatbot on Discord for Information Assistance and Conflict Prevention","authors":"Zudha Pratama, Ery Mintorini, Karmila Karmila, Didik Hermanto","doi":"10.33633/jais.v8i3.9089","DOIUrl":"https://doi.org/10.33633/jais.v8i3.9089","url":null,"abstract":"Discord, which was originally created for the gamer community, can now be found used by hobby groups and communities that are used for shared learning purposes. But the downside is the gamer culture that comes with it. Rude and toxic words that are synonymous with the gamer community should be avoided in study group communities. Meanwhile, the facilities for minimizing harsh and toxic words are still limited to word filters that can be tricked so that they can still be sent to the chat room. This can trigger conflict and interfere with learning activities together. This paper proposed an information assistance chatbot that is able to answer question, and conflict prevention with detection toxic sentences using pre-processing from NLP (Natural Language Processing) and text classification so that the chatbot is able to limit toxic sentences a little more accurately than the word filter feature alone. Also, Chatbots are given the ability to determine the value / level of toxic conversations so that they are had been able to determine the punishment action to be carried out by warning, suspending, or even being issued for the most severe cases. In addition, by looking at the frequency of sending messages from several senders, which indicates toxic, it was able to determine when the conflict occurs. The result shows that chatbot can work fine to answer question and detecting toxic include do punishment to toxic sender. With 10% error on detecting conflict and 30% error on answer question. That 30% error false positive on make an answer that should not be answered.","PeriodicalId":289013,"journal":{"name":"Journal of Applied Intelligent System","volume":"242 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139197620","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

Enhancing Default Prediction in P2P Lending using Random Forest and Grey Wolf Optimization-based Feature Selection 利用随机森林和基于灰狼优化的特征选择加强 P2P 借贷中的违约预测

Journal of Applied Intelligent System Pub Date : 2023-11-30 DOI: 10.33633/jais.v8i3.9234

Bagus Winarko Nugroho, Purwanto Purwanto, Heribertus Himawan

{"title":"Enhancing Default Prediction in P2P Lending using Random Forest and Grey Wolf Optimization-based Feature Selection","authors":"Bagus Winarko Nugroho, Purwanto Purwanto, Heribertus Himawan","doi":"10.33633/jais.v8i3.9234","DOIUrl":"https://doi.org/10.33633/jais.v8i3.9234","url":null,"abstract":"Online lending services such as Peer to Peer (P2P) loans provide convenience for lenders to transact directly without involving banks as intermediaries. Identifying potential loan recipients who are at risk of default is a crucial step in preventing financial losses, as lenders are responsible for default risk. However, predicting default risk becomes a challenge when P2P lending datasets have various complex features. Some features in P2P lending are redundant, while others do not significantly contribute to an effective solution. Therefore, feature selection is an important process to choose a relevant subset of features from input or target data. Traditional feature selection methods often fail to provide optimal results. A better approach is to use heuristic search algorithms capable of finding suboptimal feature subsets. We employ the Grey Wolf Optimization (GWO) technique, inspired by the hierarchy of leadership and grey wolf hunting mechanisms. Combined with Random Forest (RF), which has limitations in classifying data with very high dimensions, our GWO+RF combination has proven to enhance classification performance better than previous research. It achieves an accuracy score of 97.31%, compared to previous research with scores of only 67.72% for RBM+RF, 64% for Binary PSO+ERT, and 92% for GA+RF.","PeriodicalId":289013,"journal":{"name":"Journal of Applied Intelligent System","volume":"33 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139200414","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

A Comparative study of Transfer Learning CNN for Flower Type Classification 用于花卉类型分类的迁移学习 CNN 比较研究

Journal of Applied Intelligent System Pub Date : 2023-11-30 DOI: 10.33633/jais.v8i3.9380

Jaya Sumpena

引用次数: 0

Crypto-Stegano Color Image Based on Rivest Cipher 4 (RC4) and Least Significant Bit (LSB) 基于 Rivest Cipher 4 (RC4) 和最小有效位 (LSB) 的加密-Stegano 彩色图像

Journal of Applied Intelligent System Pub Date : 2023-07-31 DOI: 10.33633/jais.v8i2.8497

E. H. Rachmawanto, Hanif Maulana Hasbi, C. A. Sari, Candra Irawan, Reza Bayu Ahmad Inzaghi, Ilham Januar Akbar

引用次数: 0

Data Security Using Color Image Based on Beaufort Cipher, Column Transposition and Least Significant Bit (LSB) 基于波弗特密码、列移位和最小有效位 (LSB) 的彩色图像数据安全技术

Journal of Applied Intelligent System Pub Date : 2023-07-31 DOI: 10.33633/jais.v8i2.7863

L. Handoko, Chaerul Umam

{"title":"Data Security Using Color Image Based on Beaufort Cipher, Column Transposition and Least Significant Bit (LSB)","authors":"L. Handoko, Chaerul Umam","doi":"10.33633/jais.v8i2.7863","DOIUrl":"https://doi.org/10.33633/jais.v8i2.7863","url":null,"abstract":"One of cryptography algorithm which used is beaufort cipher. Beaufort cipher has simple encryption procedure, but this algorithm has good enough endurance to attack. Unauthorized people cannot break up decrypt without know matrix key used. This algorithm used to encrypt data in the form of text called plaintext. The result of this algorithm is string called ciphertext which difficult to understood that can causing suspicious by other people. Beaufort cipher encryption tested with avalanche effect algorithm with modified one, two, three and all key matrix which resulting maximum 31.25% with all key modification so another algorithm is needed to get more secure. Least Significant Bit (LSB) used to insert ciphertext created to form of image. LSB chosen because easy to use and simple, just alter one of last bit image with bit from message. LSB tested with RGB, CMYK, CMY and YUV color modes inserted 6142 characters resulting highest PSNR value 51.2546 on YUV color mode. Applying steganography technique has much advantage in imperceptibility, for example the image product very similar with original cover image so the difference can not differentiate image with human eye vision. Image that tested as much ten images, that consist of five 512 x 512 and five 16 x 16 image. While string message that used is 240, 480 and 960 character to test 512 x 512 image and 24, 48 and 88 character to test 16 x 16 image. The result of experiment measured with Mean Square Error (MSE) and Peak Signal Ratio (PSNR) which has minimum PSNR 51.2907 dB it means stego image that produced hood enough. Computation time calculation using tic toc in matlab resulting fastest value 0.041636 to encrypt 2000 character and the longest time is 4.10699 second to encrypt 6000 character and inserting to image. Amount of character and amount of multi algorithm can affecting computation time calculation.","PeriodicalId":289013,"journal":{"name":"Journal of Applied Intelligent System","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139353211","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

Measuring User Experience Of Traveloka Hotel Using User Experience Questionnaire 使用用户体验问卷测量 Traveloka 酒店的用户体验

Journal of Applied Intelligent System Pub Date : 2023-07-31 DOI: 10.33633/jais.v8i2.8608

Majid Aminurdin, Donny Maulana, Tri Ngudi Wiyatno

{"title":"Measuring User Experience Of Traveloka Hotel Using User Experience Questionnaire","authors":"Majid Aminurdin, Donny Maulana, Tri Ngudi Wiyatno","doi":"10.33633/jais.v8i2.8608","DOIUrl":"https://doi.org/10.33633/jais.v8i2.8608","url":null,"abstract":"Nowadays, there are many online travel agencies (OTAs) in Indonesia that provide various options for their customers. Before choosing which OTA to use, customers usually check each platform to ensure that they offer the best service. Traveloka is the most preferred OTA app by 67.5% of respondents. Google Play Store reviews show that users are still confused with information such as pricing and proper payment. Some features do not work properly when making hotel reservations. User Experience Questionnaire is used to quickly measure the user experience level of the product. Attractiveness, perspiculty, efficiency, accuracy, stimulation, and novelty were the six UEQ scales used. A random sample of one hundred app users was selected. The results showed that each scale was overall excellent. The criteria of attractiveness 2.485 ? 1.750, perspiculty 2.290 ? 1.900, efficiency 2.448 ? 1.780, dependability 2.338 ? 1.650, stimulation 2.393 ? 1.550, and novelty 2.293 ? 1.400. This research achieves the objectives or features of the application in terms of design, systems, and services. the result is that the Traveloka application can improve perspiculty with existing functions, so that the hotel booking process becomes easier to understand, easy to learn, simple, and clear.","PeriodicalId":289013,"journal":{"name":"Journal of Applied Intelligent System","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139353190","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

File Cryptography Optimization Based on Vigenere Cipher and Advanced Encryption Standard (AES) 基于 Vigenere 密码和高级加密标准 (AES) 的文件加密优化

Journal of Applied Intelligent System Pub Date : 2023-07-31 DOI: 10.33633/jais.v8i2.7899

M. Muslih, L. Handoko, Aditya Rizqy

引用次数: 0

Dijkstra-based Official Motorcycle Repair Shop Application for Determining the Shortest Route 基于 Dijkstra 的官方摩托车修理店应用程序，用于确定最短路径

Journal of Applied Intelligent System Pub Date : 2023-07-31 DOI: 10.33633/jais.v8i2.8593

Adi Sucipto, Mohamed Doheir

引用次数: 0