Jurnal Ilmu Komputer dan Informasi最新文献_第2页

LexID: The Metadata and Semantic Knowledge Graph Construction of Indonesian Legal Document 印尼法律文件元数据与语义知识图谱构建

Jurnal Ilmu Komputer dan Informasi Pub Date : 2023-03-01 DOI: 10.21609/jiki.v16i1.1096

Nur Siti Muninggar, Adila Alfa Krisnadhi

{"title":"LexID: The Metadata and Semantic Knowledge Graph Construction of Indonesian Legal Document","authors":"Nur Siti Muninggar, Adila Alfa Krisnadhi","doi":"10.21609/jiki.v16i1.1096","DOIUrl":"https://doi.org/10.21609/jiki.v16i1.1096","url":null,"abstract":"The Legal Fiction principle stipulates that the government needs to ensure the public availability of all of their legal documents. Unfortunately, the text-based search services they provide cannot return satisfactory answers in retrieval scenarios requiring proper representation of relationships between various legal documents. A key problem here is the lack of explicit representation of such relationships behind the employed retrieval engines. We aim to address this problem by proposing LexID knowledge graph (KG) that provides an explicit knowledge representation for Indonesian legal domain usable for such retrieval purposes. The KG contains both legal metadata information and semantic content of the legal clauses of the legal document's articles, modeled using formal vocabulary from the LexID ontology also presented in this paper. The KG is constructed from thousands of Indonesian legal documents. Since the procedure of writing a legal document regulated by the government is clear and detailed, we use a rule-based approach to construct our KG. At the end, we describe several use cases of the KG to address different retrieval needs. In Addition, we evaluated the quality of our KG by measuring its ability to answer questions and got that LexID can answer questions with the macro average F1 score is about 0.91.","PeriodicalId":31392,"journal":{"name":"Jurnal Ilmu Komputer dan Informasi","volume":"379 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73889314","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

Face Spoofing Detection using Inception-v3 on RGB Modal and Depth Modal 基于RGB模态和深度模态的Inception-v3人脸欺骗检测

Jurnal Ilmu Komputer dan Informasi Pub Date : 2023-03-01 DOI: 10.21609/jiki.v16i1.1100

Yuni Arti, A. M. Arymurthy

引用次数: 1

Improved mask RCNN and cosine similarity using RGBD segmentation for Occlusion handling in Multi Object Tracking 改进掩模RCNN和余弦相似度使用RGBD分割在多目标跟踪遮挡处理

Jurnal Ilmu Komputer dan Informasi Pub Date : 2023-03-01 DOI: 10.21609/jiki.v16i1.1073

Siti Hadiyan Pratiwi, Putri Shaniya, G. Jati, W. Jatmiko

{"title":"Improved mask RCNN and cosine similarity using RGBD segmentation for Occlusion handling in Multi Object Tracking","authors":"Siti Hadiyan Pratiwi, Putri Shaniya, G. Jati, W. Jatmiko","doi":"10.21609/jiki.v16i1.1073","DOIUrl":"https://doi.org/10.21609/jiki.v16i1.1073","url":null,"abstract":"In this study, additional depth images were used to enrich the information in each image pixel. Segmentation, by its nature capable to process image up to pixel level. So, it can detect up to the smallest part of the object, even when it’s overlapped with another object. By using segmentation, the main goal is to be able to maintain the tracking process longer when the object starts to be occluded until it is severely occluded right before it is completely disappeared. Object tracking based on object detection was developed by modifying the Mask R-CNN architecture to process RGBD images. The detection results feature extracted using HOG, and each of them got compared to the target objects. The comparison was using cosine similarity calculation, and the maximum value of the detected object would update the target object for the next frame. The evaluation of the model was using mAP calculation. Mask R-CNN RGBD late fusion had a higher value by 5% than Mask R-CNN RGB. It was 68,234% and 63,668%, respectively. Meanwhile, the tracking evaluation uses the traditional method of calculating the id switching during the tracking process. Out of 295 frames, the original Mask R-CNN method had ten switching ID times. On the other hand, the proposed method Mask R-CNN RGBD had much better tracking results with switching ids close to 0. Keywords—Occlusion, RGBD, Mask R-CNN, Late fusion, Cosine similarity","PeriodicalId":31392,"journal":{"name":"Jurnal Ilmu Komputer dan Informasi","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83255861","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

Embedded Deep Learning System for Classification of Car Make and Model 汽车品牌与车型分类的嵌入式深度学习系统

Jurnal Ilmu Komputer dan Informasi Pub Date : 2023-03-01 DOI: 10.21609/jiki.v16i1.1118

A. Wibisono, Hanif Arief Wisesa, Satria Bagus Wicaksono, Puteri Khatya Fahira

{"title":"Embedded Deep Learning System for Classification of Car Make and Model","authors":"A. Wibisono, Hanif Arief Wisesa, Satria Bagus Wicaksono, Puteri Khatya Fahira","doi":"10.21609/jiki.v16i1.1118","DOIUrl":"https://doi.org/10.21609/jiki.v16i1.1118","url":null,"abstract":"Automatic car make, and model classification is essential to support activities of intelligent traffic systems in urban areas, such as surveillance, traffic information collection, statistics, etc. In order to classify this data, we need an embedded system approach for real-time car recognition. Many approaches could be made, from image processing to machine learning. Recently, the development of the Convolutional Neural Network has spurred various research in the Area. ResNet, Inception, DenseNet, and NasNet are some of the most commonly used Neural Network based method that is used to classify images. In this research, these Neural Network methods are going to be compared in classifying vehicle make and model in the Stanford dataset. The dataset contains 196 different labels. Several evaluation metrics are used to compare the performance of the methods. From the experiment, the InceptionV3 method achieved the best performance of the AUROC ratio for training the dataset under 50 epochs. Other methods that achieve a high AUROC value tends to have a higher computational time. Real-time simulations have shown that the embedded system is capable of classifying a 100 % success rate for six concurrent users.","PeriodicalId":31392,"journal":{"name":"Jurnal Ilmu Komputer dan Informasi","volume":"34 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89472505","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

Poetry Generation for Indonesian Pantun Using SeqGAN and GPT-2 基于SeqGAN和GPT-2的印尼语潘顿语诗歌生成

Jurnal Ilmu Komputer dan Informasi Pub Date : 2023-03-01 DOI: 10.21609/jiki.v16i1.1113

Emmanuella Anggi Siallagan, Ika Alfina

引用次数: 0

Bimodal Keystroke Dynamics-Based Authentication for Mobile Application Using Anagram 基于双峰击键动态的基于变位词的移动应用认证

Jurnal Ilmu Komputer dan Informasi Pub Date : 2022-07-02 DOI: 10.21609/jiki.v15i2.1015

Prasti Eko Yunanto, A. Barmawi

{"title":"Bimodal Keystroke Dynamics-Based Authentication for Mobile Application Using Anagram","authors":"Prasti Eko Yunanto, A. Barmawi","doi":"10.21609/jiki.v15i2.1015","DOIUrl":"https://doi.org/10.21609/jiki.v15i2.1015","url":null,"abstract":"Currently, most of the smartphones recognize uses based on static biometrics, such as face and fingerprint. However, those traits were vulnerable against spoofing attack. For overcoming this problem, dynamic biometrics like the keystroke and gaze are introduced since it is more resistant against spoofing attack. This research focuses on keystroke dynamics for strengthening the user recognition system against spoofing attacks. For recognizing a user, the user keystrokes feature used in the login process is compared with keystroke features stored in the keystroke features database. For evaluating the accuracy of the proposed system, words generated based on the Indonesian anagram are used. Furthermore, for conducting the experiment, 34 participants were asked to type a set of words using the smartphone keyboard. Then, each user’s keystroke is recorded. The keystroke dynamic feature consists of latency and digraph which are extracted from the record. According to the experiment result, the error of the proposed method is decreased by 23.075% of EER with FAR and FRR are decreased by 16.381% and 10.41% respectively, compared with Kim’s method. It means that the proposed method is successful increase the biometrics performance by reducing the error rates","PeriodicalId":31392,"journal":{"name":"Jurnal Ilmu Komputer dan Informasi","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74814702","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

Myers-Briggs Type Indicator Personality Model Classification in English Text using Convolutional Neural Network Method 基于卷积神经网络的英语文本Myers-Briggs类型指标人格模型分类

Jurnal Ilmu Komputer dan Informasi Pub Date : 2022-07-02 DOI: 10.21609/jiki.v15i2.1052

Joseph Ananda Sugihdharma, F. A. Bachtiar

{"title":"Myers-Briggs Type Indicator Personality Model Classification in English Text using Convolutional Neural Network Method","authors":"Joseph Ananda Sugihdharma, F. A. Bachtiar","doi":"10.21609/jiki.v15i2.1052","DOIUrl":"https://doi.org/10.21609/jiki.v15i2.1052","url":null,"abstract":"Myers-Briggs Type Indicator (MBTI) is a personality model developed by Katharine Cooks Briggs and Isabel Briggs Myers in 1940. It displays a combination of preferences from four domains. Generally, test takers need to answer about 50 to 70 questions, and it is relatively expensive to know MBTI personality. The researcher developed a personality classification system using the Convolutional Neural Network (CNN) method and GloVe (Global Vectors for Word Representation) word embedding to solve this problem. The dataset used in this research consists of 8,675 data from the Kaggle site. The steps in this research are downloading the dataset from Kaggle, text preprocessing, GloVe weighting, classification using the CNN method, and evaluation using accuracy from the Confusion Matrix. Based on the tests carried out, using GloVe weighting can improve the model accuracy rather than random weighting. The best GloVe word dimensions depend on the metrics used to measure the model performance and the data of the classes contained in the dataset. From the CNN hyperparameter tuning test, the Adamax optimizer performs better and produces higher accuracy than the Adam optimizer. In addition, the CNN hyperparameter tuning increased model accuracy more significantly compared with the best GloVe word embedding dimensions.","PeriodicalId":31392,"journal":{"name":"Jurnal Ilmu Komputer dan Informasi","volume":"53 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88953234","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

Towards Erlang-based ABS Microservices Framework for Software Product Line Development 面向软件产品线开发的基于erlang的ABS微服务框架

Jurnal Ilmu Komputer dan Informasi Pub Date : 2022-07-02 DOI: 10.21609/jiki.v15i2.1065

Adrika Novrialdi, Daya Adianto, Aulia Rosyida, Priambudi Lintang Bagaskara, A. Azurat

{"title":"Towards Erlang-based ABS Microservices Framework for Software Product Line Development","authors":"Adrika Novrialdi, Daya Adianto, Aulia Rosyida, Priambudi Lintang Bagaskara, A. Azurat","doi":"10.21609/jiki.v15i2.1065","DOIUrl":"https://doi.org/10.21609/jiki.v15i2.1065","url":null,"abstract":"The current widely used software system can be categorised as a large or very large decentralised control system with various requirements and continuous interchangeable elements. This characteristic leads to a need to control the variability to manage such systems. Software Product Line Engineering (SPLE) is one of the approaches that can manage the variability by developing sets of products. However, there is a need for support tools for development with software product line engineering. One language that supports the SPLE process is Abstract Behavioral Specification (ABS). Some SPLE research has used ABS to create frameworks that support the SPLE process. ABS Microservices is one research that utilises ABS to create a web framework that supports the SPLE process. This framework uses ABS to generate Java-based applications. The research interest in the web application is driven by the fact that it is one of the software types widely used by organisations and serves as the primary support of their business. Microservices are highly interoperable, thus enabling researchers to integrate different technology from other research. However, there is a need for renewal to the ABS Microservices framework. There is a need for more variants of SPLE-enabled frameworks that use more programming language as a specific programming language has its strength and weakness. Deprecation of the Java backend of the ABS opens a new exploration of another web framework that uses other ABS backend languages. We present the ABS microservices web framework based on Erlang OTP. We choose Erlang because it promises more efficient resource usage and the Erlang backend is one of the ABS backends with the most available features. This research aims to create an entry point for ABS Microservices to support more language. This research shows that the Erlang variant of ABS Microservices has less resource usage than the Java variant. Hence, this promises more options to develop product lines using ABS Microservices.","PeriodicalId":31392,"journal":{"name":"Jurnal Ilmu Komputer dan Informasi","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79652128","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

Optimization of 2D-CNN Setting for the classification of covid disease using Lung CT Scan 肺部CT扫描用于covid - 19疾病分类的2D-CNN设置优化

Jurnal Ilmu Komputer dan Informasi Pub Date : 2022-07-02 DOI: 10.21609/jiki.v15i2.1083

K. Kirana, S. Wibawanto, Ahmad Hamdan, Wahyu Nur Hidayat

{"title":"Optimization of 2D-CNN Setting for the classification of covid disease using Lung CT Scan","authors":"K. Kirana, S. Wibawanto, Ahmad Hamdan, Wahyu Nur Hidayat","doi":"10.21609/jiki.v15i2.1083","DOIUrl":"https://doi.org/10.21609/jiki.v15i2.1083","url":null,"abstract":"RT-PCR is considered the best diagnostic tool. Previous studies have demonstrated the reliability of CNN in classifying classifications, but CNN requires a lot of training data. Meanwhile, at the CT Scan clinic, patients are limited. Therefore, exploration of 2D-CNN settings is proposed to optimize CNN performance on limited data. We compare: (1) activation models, (2) output shapes per layer, (3) dropout layers, and (4) early stopping values. The test results show that RELU activation is better than Sigmoid. Rescaling (128x128) is better for scala (64x64) and (256x256) which affects the output shape model of each layer. In this learning stage, the use of dropouts in the CNN architecture achieves robust accuracy than the architecture that ignores dropouts. The use of 15 early stoppings is better than other values compared. 20 images of pneumonia and 20 images of covid have been tested using the proposed method and achieved 87.50% accuracy, 80.00% precision, 100% recall, and 99.89% F1-Score. Our method is superior to the the comparison method in terms of accuracy, precision, recall, and f1-score, which achieves 85%, 70%, 100%, and 82.35%, respectively.","PeriodicalId":31392,"journal":{"name":"Jurnal Ilmu Komputer dan Informasi","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84564311","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

Improving Recognition of SIBI Gesture by Combining Skeleton and Hand Shape Features 结合骨架和手形特征改进SIBI手势识别

Jurnal Ilmu Komputer dan Informasi Pub Date : 2022-07-02 DOI: 10.21609/jiki.v15i2.1014

Erdefi Rakun, Noer FP Setyono

{"title":"Improving Recognition of SIBI Gesture by Combining Skeleton and Hand Shape Features","authors":"Erdefi Rakun, Noer FP Setyono","doi":"10.21609/jiki.v15i2.1014","DOIUrl":"https://doi.org/10.21609/jiki.v15i2.1014","url":null,"abstract":"SIBI (Sign System for Indonesian Language) is an official sign language system used in school for hearing impairment students in Indonesia. This work uses the skeleton and hand shape features to classify SIBI gestures. In order to improve the performance of the gesture classification system, we tried to fuse the features in several different ways. The accuracy results achieved by the feature fusion methods are, in descending order of accuracy: 88.016%, when using sequence-feature-vector concatenation, 85.448% when using Conneau feature vector concatenation, 83.723% when using feature-vector concatenation, and 49.618% when using simple feature concatenation. The sequence-feature-vector concatenation techniques yield noticeably better results than those achieved using single features (82.849% with skeleton feature only, 55.530% for the hand shape feature only). The experiment results show that the combined features of the whole gesture sequence can better distinguish one gesture from another in SIBI than the combined features of each gesture frame. In addition to finding the best feature combination technique, this study also found the most suitable Recurrent Neural Network (RNN) model for recognizing SIBI. The models tested are 1-layer, 2-layer LSTM, and GRU. The experimental results show that the 2-layer bidirectional LSTM has the best performance.","PeriodicalId":31392,"journal":{"name":"Jurnal Ilmu Komputer dan Informasi","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91298749","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: 2