IJCCS Indonesian Journal of Computing and Cybernetics Systems最新文献_第5页

Forecasting Indonesian Oil, Non-Oil and Gas Import Export with Fuzzy Time Series 用模糊时间序列预测印尼石油、非石油和天然气进出口

IJCCS Indonesian Journal of Computing and Cybernetics Systems Pub Date : 2022-10-31 DOI: 10.22146/ijccs.78399

Syalam Ali Wira Dinata, Ayuning Arum Purbosari, P. Hasanah

{"title":"Forecasting Indonesian Oil, Non-Oil and Gas Import Export with Fuzzy Time Series","authors":"Syalam Ali Wira Dinata, Ayuning Arum Purbosari, P. Hasanah","doi":"10.22146/ijccs.78399","DOIUrl":"https://doi.org/10.22146/ijccs.78399","url":null,"abstract":" Indonesia is active in export and import activities. Some of the commodities traded are oil and gas, as well as food and other industrial materials. Export and import activities play a role in determining the stability of the country's economy seen from its trade balance. According to the Central Statistics Agency, Indonesia experienced a deficit of USD 864 million due to a decline in exports at the beginning of 2020. Based on the state of the trade balance, the government needs to make policies in order to maintain the stability of the Indonesian economy. The right decision-making must be supported by accurate information, therefore, through this research, the value of Indonesia's exports and imports will be forecasted in the oil and gas and non-oil and gas sectors for the next period using the Fuzzy Time Series (FTS). FTS was chosen as the forecasting method because it is able to predict free real time data with arbitrary patterns. The data used is data on the value of exports and imports of oil and gas and non-oil and gas sectors for 2011-2020. To overcome the problem of stationary data variance and reduce the error value, a Box Cox transformation will be applied. The research stages include data transformation with Box Cox, forming universe and linguistic sets, determining interval length, fuzzification, forming FLR and FLR, defuzzification and forecasting. The final forecast results estimate that exports and imports in the oil and gas sector in 2021 will decline, while for the non-oil and gas sector will fluctuate and increase from the previous year. Forecasting with Box Cox transform data is more accurate with MAPE 19.56% and RMSE 121.52 compared to forecasting with original data with MAPE 74.89% and RMSE 132.09.","PeriodicalId":31625,"journal":{"name":"IJCCS Indonesian Journal of Computing and Cybernetics Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49353360","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

Automatic Essay Scoring Using Data Augmentation in Bahasa Indonesia 使用数据增强的印尼语自动作文评分

IJCCS Indonesian Journal of Computing and Cybernetics Systems Pub Date : 2022-10-31 DOI: 10.22146/ijccs.76396

Nurul Fadilah, Sigit Priyanta

引用次数: 3

Real-Time Face Recognition Civil Servant Presence System Using DNN Algorithm 基于DNN算法的公务员实时人脸识别系统

IJCCS Indonesian Journal of Computing and Cybernetics Systems Pub Date : 2022-10-31 DOI: 10.22146/ijccs.77026

Yogi Angga Putra, Imelda Imelda

{"title":"Real-Time Face Recognition Civil Servant Presence System Using DNN Algorithm","authors":"Yogi Angga Putra, Imelda Imelda","doi":"10.22146/ijccs.77026","DOIUrl":"https://doi.org/10.22146/ijccs.77026","url":null,"abstract":"Facial recognition has become a growing topic among Computer Vision researchers because it can solve real-life problems, including during the COVID-19 pandemic. The pandemic is why the Indonesian government has imposed social restrictions and physical contact in public places. Before the pandemic, most touch-based attendance systems used fingerprints or Radio Frequency Identification (RFID) cards. The solution proposed in this study is to identify real-time facial recognition of the Civil Service presence system using a Deep Neural Network. The goal is to minimize physical contact. The research stages include data collection, augmentation and preprocessing, CNN modeling and training, model evaluation, converting to OpenCV DNN, implementation of transfer learning, and identification of test data. This research contributes to testing variations in distance and position so it can recognize a person's face even when wearing a mask and glasses. This DNN model produces a validation accuracy value of 99.48% and a validation loss of 0.0273 with a data training process of 10 times. Tests for variations in distance, position, use of masks, and glasses on MTCNN detection provide an average accuracy for each trial of 100%, 96%, and 100%, respectively. Therefore, the average accuracy of the Haar Cascades detection test is 100%, 85%, and 100%.","PeriodicalId":31625,"journal":{"name":"IJCCS Indonesian Journal of Computing and Cybernetics Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48364916","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

Traditional Music Regional Classification using Convolutional Neural Network (CNN) 基于卷积神经网络(CNN)的传统音乐区域分类

IJCCS Indonesian Journal of Computing and Cybernetics Systems Pub Date : 2022-10-31 DOI: 10.22146/ijccs.73910

Raymond Luis, N. Rokhman

引用次数: 0

Topic Modeling on Online News.Portal Using Latent Dirichlet Allocation (LDA) 网络新闻的话题建模。基于潜在Dirichlet分配(LDA)的门户

IJCCS Indonesian Journal of Computing and Cybernetics Systems Pub Date : 2022-10-31 DOI: 10.22146/ijccs.74383

Mohammad Rezza Fahlevvi, Azhari Sn

引用次数: 2

Automatic Detection of Helmets on Motorcyclists Using Faster - RCNN 基于RCNN的摩托车头盔自动检测技术

IJCCS Indonesian Journal of Computing and Cybernetics Systems Pub Date : 2022-10-31 DOI: 10.22146/ijccs.68245

Aliyyah Nur Azhari, W. Wahyono

引用次数: 0

Neural Network Pruning in Unsupervised Aspect Detection based on Aspect Embedding 基于方面嵌入的无监督方面检测中的神经网络修剪

IJCCS Indonesian Journal of Computing and Cybernetics Systems Pub Date : 2022-10-31 DOI: 10.22146/ijccs.72981

Muhammad Haris Maulana, M. L. Khodra

{"title":"Neural Network Pruning in Unsupervised Aspect Detection based on Aspect Embedding","authors":"Muhammad Haris Maulana, M. L. Khodra","doi":"10.22146/ijccs.72981","DOIUrl":"https://doi.org/10.22146/ijccs.72981","url":null,"abstract":" Aspect detection systems for online reviews, especially based on unsupervised models, are considered better strategically to process online reviews, generally a very large collection of unstructured data. Aspect embedding-based deep learning models are designed for this problem however they still rely on redundant word embedding and they are sensitive to initialization which may have a significant impact on model performance. In this research, a pruning approach is used to reduce the redundancy of deep learning model connections and is expected to produce a model with similar or better performance. This research includes several experiments and comparisons of the results of pruning the model network weights based on the general neural network pruning strategy and the lottery ticket hypothesis. The result of this research is that pruning of the unsupervised aspect detection model, in general, can produce smaller submodels with similar performance even with a significant amount of weights pruned. Our sparse model with 80% of its total weight pruned has a similar performance to the original model. Our current pruning implementation, however, has not been able to produce sparse models with better performance.","PeriodicalId":31625,"journal":{"name":"IJCCS Indonesian Journal of Computing and Cybernetics Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44460836","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

The usefulness of an Augmented Reality-based Interactive 3D Furniture Catalog as a Tool to Aid Furniture Store Sales Operations 基于增强现实的交互式3D家具目录作为辅助家具商店销售运营的工具的有用性

IJCCS Indonesian Journal of Computing and Cybernetics Systems Pub Date : 2022-10-31 DOI: 10.22146/ijccs.69570

Irwan Ismail, Evan Syaputra, B. D. Leonanda, Nurul Iksan, Azmi Shawkat Abdulbaqie, M. Husin, H. Ahmad, I. Y. Panessai

{"title":"The usefulness of an Augmented Reality-based Interactive 3D Furniture Catalog as a Tool to Aid Furniture Store Sales Operations","authors":"Irwan Ismail, Evan Syaputra, B. D. Leonanda, Nurul Iksan, Azmi Shawkat Abdulbaqie, M. Husin, H. Ahmad, I. Y. Panessai","doi":"10.22146/ijccs.69570","DOIUrl":"https://doi.org/10.22146/ijccs.69570","url":null,"abstract":"The global crisis, that has resulted from the outbreak of Covid-19, influences all aspects of daily life. Due to the people's poor purchasing power, several major stores, such as Furniture Store-XYZ, were forced to close several branches. To counter this, it will be required to adopt unique initiatives that will assist attract visitors and enhance sales while still adhering to the established health protocols. AR-Furniture is the ideal technology to solve this problem. AR-Furniture is an Augmented Reality-based technology that enables a 3D furniture catalog to present a complete picture of a piece of furniture in a virtual form that appears natural and identical to the original. The MDLC development process used in the AR-Furniture Mobile App. According to the study's findings, 100% of respondents agree that AR-Furniture helps to sell and to buy process be done effectively and productively and gives the users innovative ideas. 70% of respondents strongly agree that AR-Furniture makes it easier for users to reach their goals and that AR-Furniture allows users to do whatever they want. 100% of respondents strongly believe that AR-Furniture is helpful and that shoppers can save time while picking the right furniture. Furthermore, AR-Furniture makes it simple for consumers to select preferred furniture without engaging with shopkeeper workers.","PeriodicalId":31625,"journal":{"name":"IJCCS Indonesian Journal of Computing and Cybernetics Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49048083","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

Sentiment Analysis Using Backpropagation Method to Recognize the Public Opinion 用反向传播法进行情绪分析以识别舆论

IJCCS Indonesian Journal of Computing and Cybernetics Systems Pub Date : 2022-10-31 DOI: 10.22146/ijccs.78664

I. A. Wiguna, P. Sugiartawan, I. Sudipa, I. P. Y. Pratama

引用次数: 0

Naive Bayes Method and C4.5 in Classification of Birth Data 出生数据分类中的朴素贝叶斯方法和C4.5

IJCCS Indonesian Journal of Computing and Cybernetics Systems Pub Date : 2022-10-31 DOI: 10.22146/ijccs.78198

Asep Afandi, Noviana Noviana, Deti Nurdianah

{"title":"Naive Bayes Method and C4.5 in Classification of Birth Data","authors":"Asep Afandi, Noviana Noviana, Deti Nurdianah","doi":"10.22146/ijccs.78198","DOIUrl":"https://doi.org/10.22146/ijccs.78198","url":null,"abstract":"Data on the birth and productive age of a mother to get pregnant in Lampung is still high. to find out the comparison of the productive age of pregnant women and whether they have met the minimum and maximum requirements for a mother to become pregnant, and the criteria for babies born. Where the results of data processing will be used as a source of data for counseling mothers, especially for residents of Banjar Kertahayu village. The data processing requires a special method so that the results become a benchmark for a decision later, such as Data Mining. The method used for data processing used is Naive Bayes and C4.5 Algorithm. The data used is birth data in 2017-2021, the source of data from the Banjar Village Midwife-Central Lampung Regency. Research Results Method C 4.5 Middle age has a dominant age category value of 0.3324138. where the highest value is in 2017, and accuracy is 100 percent from the 2017-2021 data. The baby weight criterion using the Naïve Bayes Class Method has a dominant Middle-aged category value of 0.09675, the highest value in 2017, The results of accuracy for 5 years have accuracy of 92.84% based on 2017-2021 birth data","PeriodicalId":31625,"journal":{"name":"IJCCS Indonesian Journal of Computing and Cybernetics Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41952882","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: 1