International Journal on Information and Communication Technology (IJoICT)最新文献_第3页

Safety Requirements Analysis using Misuse Cases Method 用误用案例法分析安全需求

International Journal on Information and Communication Technology (IJoICT) Pub Date : 2021-06-17 DOI: 10.21108/ijoict.v7i1.543

R. A. Ramadhan, D. S. Kusumo, Jati H. Husen

引用次数: 0

The Foreign Exchange Rate Prediction Using Long-Short Term Memory 基于长短期记忆的汇率预测

International Journal on Information and Communication Technology (IJoICT) Pub Date : 2021-01-05 DOI: 10.21108/ijoict.2020.62.538

Hasna Haifa Zahrah, S. Sa'adah, Rita Rismala

{"title":"The Foreign Exchange Rate Prediction Using Long-Short Term Memory","authors":"Hasna Haifa Zahrah, S. Sa'adah, Rita Rismala","doi":"10.21108/ijoict.2020.62.538","DOIUrl":"https://doi.org/10.21108/ijoict.2020.62.538","url":null,"abstract":"The foreign exchange market is a global financial market that is influenced by economic, political, and psychological factors that are interconnected in complex ways. This complexity makes the foreign exchange market a difficult time-series prediction. At the end of 2019, the world was faced with the COVID-19 pandemic that has not only affected public health but also the foreign exchange market, which makes the trading behaviour affected. Long Short-Term Memory network (LSTM) is a type of recurrent neural network (RNN) that can solve long-term dependencies and is suitable to be a financial time-series model. This study implemented the LSTM model to predict the foreign exchange rate at a timeframe of 1 hour and daily in 2020 to get the best hyperparameter based on the RMSE evaluation results. Furthermore, with the obtained hyperparameters, the prediction result of 2020 was then compared with the 2018 and 2019 prediction results. The best RMSE result was obtained in 1-hour timeframe and when 2020’s RMSE result was compared to 2018’s and 2019’s RMSE result, the prediction of 2019 gave the best RMSE result. The LSTM model is able to achieve good results in the 2020 prediction, proven by the RMSE result which is 0.00135.","PeriodicalId":137090,"journal":{"name":"International Journal on Information and Communication Technology (IJoICT)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114407843","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

Sales Demand Forecasting Using One of Multivariate Markov Chain Model Parameter 基于多元马尔可夫链模型参数的销售需求预测

International Journal on Information and Communication Technology (IJoICT) Pub Date : 2020-12-31 DOI: 10.21108/ijoict.2020.62.533

Annisa Martina

{"title":"Sales Demand Forecasting Using One of Multivariate Markov Chain Model Parameter","authors":"Annisa Martina","doi":"10.21108/ijoict.2020.62.533","DOIUrl":"https://doi.org/10.21108/ijoict.2020.62.533","url":null,"abstract":"The imbalance between demand and supply is frequently occurred in a market. This is due to the availability of goods that cannot match with the demand or the growth rate of customer. This is not preferable since the profit is not on the track. In contrast, the goods are probably over supplied so that company has to expense additional cost for extra storage. Both situations can be anticipated if the demand is precisely estimated. Therefore, in this study we will estimate demand in market situation by implementing multivariate Markov chain model. Multivariate Markov chain model is popular model for forecasting by observing current state in various applications. This model is compatible with 5 data sequences (product types) defined as product A, product B, product C, product D and product E, with 6 conditions (no sales volume, very slow-moving, slow-moving, standard, fast moving, and very fast moving). As the result, the highest transition probability value for the sales demand in a company is found at the transition probability matrix from product C to product C, from very fast moving to very fast-moving condition, which had the highest probability value 0.625 with the highest frequency 105 times.","PeriodicalId":137090,"journal":{"name":"International Journal on Information and Communication Technology (IJoICT)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132053796","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

A Forensic Analysis Visualization Tool for Mobile Instant Messaging Apps 用于移动即时通讯应用程序的取证分析可视化工具

International Journal on Information and Communication Technology (IJoICT) Pub Date : 2020-11-21 DOI: 10.21108/ijoict.2020.62.530

Wee Sern Ong, Nurul Hidayah Ab Rahman

{"title":"A Forensic Analysis Visualization Tool for Mobile Instant Messaging Apps","authors":"Wee Sern Ong, Nurul Hidayah Ab Rahman","doi":"10.21108/ijoict.2020.62.530","DOIUrl":"https://doi.org/10.21108/ijoict.2020.62.530","url":null,"abstract":"In this study, we demonstrate the role of visualization to facilitate forensic analysis goal in interpreting metadata of evidence of interest to answer who, what, why, when, where, and how an incident occurred. Two mobile Instant Messaging (IM) applications (i.e. WhatsApp and Line) were deployed as a case study. Subsequently, a tool – W*W Visualizer – was designed and developed with the aims to analyze and visualize the connection of evidence metadata, text frequency and word count, and display report of analysis activities. The tool is developed by adopting Object-Oriented Software Development Model with Visual Studio platform and C# language were used to develop the system. Our findings show that W*W Visualizer could transform the data of the chat database into a visual form, for example graph, chart and word cloud. The tool also allows the user to perform search feature such as searching based on keyword and timestamp from the IM chat history. It is expected that outcomes from this study would significantly influence digital forensics practitioners in analyzing and interpreting evidence data, and judicial authorities in understanding the presentation of evidence. ","PeriodicalId":137090,"journal":{"name":"International Journal on Information and Communication Technology (IJoICT)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133874716","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

Analysis of Voice Changes in Anti Forensic Activities Case Study: Voice Changer with Telephone Effect 反取证活动中的语音变化分析——以具有电话效应的语音变化为例

International Journal on Information and Communication Technology (IJoICT) Pub Date : 2020-10-21 DOI: 10.21108/ijoict.v6i2.508

Abiyan Bagus Baskoro, N. Cahyani, Aji Gautama Putrada

{"title":"Analysis of Voice Changes in Anti Forensic Activities Case Study: Voice Changer with Telephone Effect","authors":"Abiyan Bagus Baskoro, N. Cahyani, Aji Gautama Putrada","doi":"10.21108/ijoict.v6i2.508","DOIUrl":"https://doi.org/10.21108/ijoict.v6i2.508","url":null,"abstract":"Voice recordings can be changed in various ways, either intentionally or unintentionally, one of which is by using a voice changer. Reference voice recordings and suspect voice recordings will be more difficult to analyze if suspect voice recordings are changed using a voice changer application under certain effects such as telephone effect. Voice Changer can be one form of activity that can be carried out by anti-forensics, making it difficult for investigators to investigate if the voice recording is changed with telephone effect. This study has two types of recordings, namely the reference voice recording (unknown sample) and suspect voice recording (known sample) that has been changed using a voice changer application with telephone effect. Investigations were carried out based on data results extraction and analysis using pitch, formant, and spectrogram using the Analysis of variance (ANOVA) method and the likelihood ratio method. The results of this study indicate that the application of voice changer can be one form of activity that can be carried out by anti-forensics so that it can be difficult for investigators to conduct investigations on sound recording evidence. This research may help forensic communities, especially investigators to conduct investigations on sound recording.","PeriodicalId":137090,"journal":{"name":"International Journal on Information and Communication Technology (IJoICT)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114494984","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: 4

Tone Classification Matches Kodàly Handsign with the K-Nearest Neighbor Method at Leap Motion Controller 在Leap运动控制器上用k近邻方法匹配Kodàly手势的音调分类

International Journal on Information and Communication Technology (IJoICT) Pub Date : 2020-06-10 DOI: 10.21108/ijoict.2019.52.283

Muhammad Croassacipto, M. Ichwan, Dina Budhi Utami

{"title":"Tone Classification Matches Kodàly Handsign with the K-Nearest Neighbor Method at Leap Motion Controller","authors":"Muhammad Croassacipto, M. Ichwan, Dina Budhi Utami","doi":"10.21108/ijoict.2019.52.283","DOIUrl":"https://doi.org/10.21108/ijoict.2019.52.283","url":null,"abstract":"Hands can produce a variety of poses in which each pose can have a meaning or purpose that can be used as a form of communication determined according to a general agreement or who communicate. Hand pose can be used as human interaction with the computer is faster, intuitive, and in line with the natural function of the human body called Handsign. One of them is Kodàly Handsign, made by a Hungarian composer named Zoltán Kodály, which is a concept in music education in Hungary. This hand sign is used in interactive angklung performances in determining the tone that will be played by the K-Nearest Neighbor (KNN) algorithm classification process based on hand poses. This classification process is performed on the extracted data from Leap Motion Controller, which takes Pitch, Roll, and Yaw values based on basic aircraft principle. The results of the research were conducted five times with the value of k periodically 1,3,5,7,9 with test data consisting pose of 874 Do', 702 Si, 913 La, 612 Sol, 661 Fa, 526 Mi, 891 Re, and 1004 Do punctuation on 21099 training data. The test results can recognize hand poses with the optimal k value k=1 with an accuracy level of 94.87%.","PeriodicalId":137090,"journal":{"name":"International Journal on Information and Communication Technology (IJoICT)","volume":"287 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127555315","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

Wind Wave Prediction by using Autoregressive Integrated Moving Average model : Case Study in Jakarta Bay 基于自回归综合移动平均模式的风浪预测:以雅加达湾为例

International Journal on Information and Communication Technology (IJoICT) Pub Date : 2019-04-02 DOI: 10.21108/IJOICT.2018.42.300

D. Adytia, Alif Rizal Yonanta, N. Subasita

{"title":"Wind Wave Prediction by using Autoregressive Integrated Moving Average model : Case Study in Jakarta Bay","authors":"D. Adytia, Alif Rizal Yonanta, N. Subasita","doi":"10.21108/IJOICT.2018.42.300","DOIUrl":"https://doi.org/10.21108/IJOICT.2018.42.300","url":null,"abstract":"Prediction of wind wave is highly needed to support safe navigation, especially for ship. Besides that, loading and unloading activities in a harbour, as well as for design purpose of coastal and offshore structures, data of prediction of wave height are needed. Based on its nature, the wind wave has random behaviour that is highly depending on behaviour of wind as the main driving force. In this paper, we propose a prediction method for wind wave by using Autoregressive Integrated Moving Average or ARIMA. To obtain historical data of wind wave, we perform wave simulation by using a phase-averaged wave model SWAN (Simulating Wave Near Shore). From the simulation, time series of wind wave is obtained. The prediction of wind wave is performed to calculate forecast of 24 hours ahead. Here, we perform wind wave prediction in a location in Jakarta Bay, Indonesia. We perform several combination of ARIMA model to obtain best fit model for wind wave prediction in the location in Jakarta Bay. Results of prediction show that ARIMA model give an accurate prediction especially for short term prediction.","PeriodicalId":137090,"journal":{"name":"International Journal on Information and Communication Technology (IJoICT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115674616","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: 3

Increasing Feature Selection Accuracy through Recursive Method in Intrusion Detection System 利用递归方法提高入侵检测系统特征选择的准确性

International Journal on Information and Communication Technology (IJoICT) Pub Date : 2019-04-02 DOI: 10.21108/IJOICT.2018.42.216

Andreas Jonathan Silaban, Satria Mandala, Erwid Mustofa Jadied

引用次数: 4

Price Prediction of Chili Commodities in Bandung Regency Using Bayesian Network 基于贝叶斯网络的万隆市辣椒类商品价格预测

International Journal on Information and Communication Technology (IJoICT) Pub Date : 2019-04-02 DOI: 10.21108/IJOICT.2018.42.204

Putri Nuvaisiyah, F. Nhita, D. Saepudin

{"title":"Price Prediction of Chili Commodities in Bandung Regency Using Bayesian Network","authors":"Putri Nuvaisiyah, F. Nhita, D. Saepudin","doi":"10.21108/IJOICT.2018.42.204","DOIUrl":"https://doi.org/10.21108/IJOICT.2018.42.204","url":null,"abstract":"Chili is one of the agricultural commodities consumed by Indonesian people. Market data in recent years show that chili prices tend to fluctuate as supply and demand changes. One of the impacts of chili price changes for farmers is the production cost is higher than the selling price. In addition to supply and demand changes, the weather is also indicated as a factor of price changes due to the weather being considered by farmers to grow chili. Price prediction is needed to determine the condition of chili prices in the future to help farmers in making decisions to plant at the right time. One method that can be used to make prediction is Data Mining classification method. In this paper, Bayesian network algorithm was used as Data Mining classification method to predict the price of chili commodity in Bandung Regency based on weather information and classified the price into economic class and not economic class. The result shows that the prediction model obtained by the Bayesian Network gives a system’s performance for precision and recall that is 1 and 0.94 respectively with average accuracy of 85.5% in classifying the price.","PeriodicalId":137090,"journal":{"name":"International Journal on Information and Communication Technology (IJoICT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125237784","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: 10

Weather Forecasting in Bandung Regency based on FP-Growth Algorithm 基于FP-Growth算法的万隆县天气预报

International Journal on Information and Communication Technology (IJoICT) Pub Date : 2019-04-02 DOI: 10.21108/IJOICT.2018.42.203

F. Khasanah, F. Nhita

{"title":"Weather Forecasting in Bandung Regency based on FP-Growth Algorithm","authors":"F. Khasanah, F. Nhita","doi":"10.21108/IJOICT.2018.42.203","DOIUrl":"https://doi.org/10.21108/IJOICT.2018.42.203","url":null,"abstract":"Weather change is one of the things that can affect people around the world in doing activities, including in Indonesia. The area of Indonesia, especially in Bandung regency has a high intensity of rainfall, compared with other regions. The people of Bandung Regency mostly have livelihoods in the fields of industry and agriculture, both of which are closely related to the effects of weather. Weather prediction is used for reference, so the future of society can prepare all possible weather before the move. One method of data mining used to predict weather is the association rule method. In this method there is Frequent Pattern Growth (FP-Growth) algorithm, this algorithm is used to determine the pattern of linkage between attribute weather with rainfall. The result of the FP-Growth algorithm is an association rule, the result of the algorithm rules is then used as reference for data entry in the classification process, where the process is done to get the forecast based on the rainfall category to obtain maximum accuracy. The highest performance result of FP-Growth from the result of rules based on its confidence value is 92%.","PeriodicalId":137090,"journal":{"name":"International Journal on Information and Communication Technology (IJoICT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126293177","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: 4