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IJoICT (International Journal on Information and Communication Technology)
Published by Universitas Telkom
ISSN : -     EISSN : 23565462     DOI : -
Core Subject : Science,
Computer Science & IT
International Journal on Information and Communication Technology (IJoICT) is a peer-reviewed journal in the field of computing that published twice a year; scheduled in December and June.
Arjuna Subject : -
Articles 70 Documents
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Keyword Indexing And Searching Tool (KIST): A Tool to Assist the Forensics Analysis of WhatsApp Chat Syafiqah Hanisah Shahrol Nizam; Nurul Hidayah Ab Rahman; Niken Dwi Wahyu Cahyani
International Journal on Information and Communication Technology (IJoICT) Vol. 6 No. 1 (2020): June 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2020.61.481

Abstract

Digital forensics is a field that concerned with finding and presenting evidence sourced from digital devices, such as computers and mobile phones. Most of the forensic analysis software is proprietary, and eventually, specialized analysis software is developed in both the private and public sectors. This paper presents an alternative of forensic analysis tools for digital forensics, which specifically to analyze evidence through keyword indexing and searching. Keyword Indexing and Searching Tool (KIST) is proposed to analyze evidence of interest from WhatsApp chat text files using keyword searching techniques and based on incident types. The tool was developed by adopting the Prototyping model as its methodology. KIST includes modules such as add, edit, remove, display the indexed files, and to add WhatsApp chat text files. Subsequently, the tool is tested using functionality testing and user testing. Functionality testing shows all key functions are working as intended, while users testing indicates the majority of respondents are agree that the tool is able to index and search keyword and display forensic analysis results.
Non-Line of Sight LoRa –Based Localization using RSSI-Kalman-Filter and Trilateration Thirafi Wian Anugrah; Andrian Rakhmatsyah; Aulia Arif Wardana
International Journal on Information and Communication Technology (IJoICT) Vol. 6 No. 2 (2020): December 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2020.00.495

Abstract

The method that analyzes in this research is the combination of the Received Signal Strength Indicator (RSSI) with the Trilateration Method. This research also filtered the RSSI value using the Kalman filter method for smoothing data. The localization system traditionally based on Global Positioning System (GPS) device. However, GPS technology not working well in Non-line-of-sight (NLOS) like an indoor location or mountain area. The other way to implement the localization system is by using LoRa technology. This technology used radio frequency to communicate with each other node. The radiofrequency has a measurement value in the form of signal strength. These parameters, when combined with the trilateration method, can be used as a localization system. After implementation and testing, the system can work well compared with the GPS system for localization. RMSE is used to calculate error distance on these methods, the result from three methods used, the value from RSSI with Kalman filter have a close result to actual position, then value GPS follows with close result from Kalman filter, and the last one is RSSI without Kalman filter.
Analysis of Voice Changes in Anti Forensic Activities Case Study: Voice Changer with Telephone Effect Abiyan Bagus Baskoro; Niken Cahyani; Aji Gautama Putrada
International Journal on Information and Communication Technology (IJoICT) Vol. 6 No. 2 (2020): December 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/ijoict.v6i2.508

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.
A Forensic Analysis Visualization Tool for Mobile Instant Messaging Apps Wee Sern Ong; Nurul Hidayah Ab Rahman
International Journal on Information and Communication Technology (IJoICT) Vol. 6 No. 2 (2020): December 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2020.62.530

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.
Sales Demand Forecasting Using One of Multivariate Markov Chain Model Parameter Annisa Martina
International Journal on Information and Communication Technology (IJoICT) Vol. 6 No. 2 (2020): December 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2020.62.533

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.
The Foreign Exchange Rate Prediction Using Long-Short Term Memory: A Case Study in COVID-19 Pandemic Hasna Haifa Zahrah; Siti Sa’adah; Rita Rismala
International Journal on Information and Communication Technology (IJoICT) Vol. 6 No. 2 (2020): December 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/IJOICT.2020.62.538

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.
Comparative Analysis of QoE Multipath TCP Congestion Control LIA, CUBIC, and WVEGAS on Video Streaming Siti Amatullah Karimah; Fiqqih Maulana Susanto; Aji G. Putrada
International Journal on Information and Communication Technology (IJoICT) Vol. 7 No. 1 (2021): June 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/ijoict.v7i1.534

Abstract

Transmission Control Protocol (TCP) is a type of protocol that allows a collection of computers to communicate and exchange data within a network. Nowadays electronic devices such as tablets, personal computers and smartphones can use more than one network at the same time, but this is not supported by the characteristics of TCP which can only use one path on the network. To solve this condition there are several new generations of standardized network protocols. Multipath TCP is a development of TCP, Multipath which is a new generation network protocol that allows traffic to use multiple paths in the network. In addition to being able to use multiple paths on multipath TCP, there are several congestion control algorithms including LIA, CUBIC and WVEGAS congestion control algorithms. Tests conducted in this study were to compare the performance of congestion control LIA, CUBIC and WVEGAS to improve the quality of video streaming. From the test results, CUBIC is better than WVEGAS and LIA because the QoS and QoE video streaming test for CUBIC in all testing environment has better results than others.
Safety Requirements Analysis using Misuse Cases Method Ryo Alif Ramadhan; Dana Sulistyo Kusumo; Jati Hiliamsyah Husen
International Journal on Information and Communication Technology (IJoICT) Vol. 7 No. 1 (2021): June 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/ijoict.v7i1.543

Abstract

Safety requirements analysis is an activity inside software requirements engineering that focuses on finding and solving safety gaps inside a software product. One method to do safety requirements analysis is misuse cases, a technique adopted from the security analysis method. Misuse cases provide a safety analysis approach which allows detailed steps from different stakeholders' perspective. In this research, we evaluate the misuse cases method's understandability by implementing it to analyze safety requirements for an electric car's autopilot system. We assessed the developed models using the walkthrough method. We found differences between how the model understood from someone with experience in software development and those who don't.
Neural Network on Stock Prediction using the Stock Prices Feature and Indonesian Financial News Titles Nur Ghaniaviyanto Ramadhan; Imelda Atastina
International Journal on Information and Communication Technology (IJoICT) Vol. 7 No. 1 (2021): June 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/ijoict.v7i1.544

Abstract

Stocks are the most popular investments among entrepreneurs or other investors. When investing in stocks these investors tend to learn how to invest stocks correctly and when is the right time. For the problem of how to invest shares correctly can be used a variety of basic theories that already exist, but for the problem when the right time needs further learning. In this paper will purpose about stock price prediction using stock data indicators and financial headline data in Bahasa Indonesia. The machine learning model used is a multi-layer perceptron neural network (MLP-NN) with the highest accuracy produced by 80%.
Performance Comparison of Several Range-based Techniques for Indoor Localization Based on RSSI Dwi Joko Suroso; Farid Yuli Martin Adiyatma; Ahmad Eko Kurniawan; Panarat Cherntanomwong
International Journal on Information and Communication Technology (IJoICT) Vol. 7 No. 1 (2021): June 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/ijoict.v7i1.550

Abstract

The classical rang-based technique for position estimation is still reliably used for indoor localization. Trilateration and multilateration, which include three or more references to locate the indoor object, are two common examples. These techniques use at least three intersection-locations of the references' distance and conclude that the intersection is the object's position. However, some challenges have appeared when using a simple power-to-distance parameter, i.e., received signal strength indicator (RSSI). RSSI is known for its fluctuated values when used as the localization parameter. The improvement of classical range-based has been proposed, namely min-max and iRingLA algorithms. These algorithms or methods use the approximation in a bounding-box and rings for min-max and iRingLA, respectively. This paper discusses the comparison performance of min-max and iRingLA with multilateration as the classical method. We found that min-max gives the best performance, and in some positions, iRingLA gives the best accuracy error. Hence, the approximation method can be promising for indoor localization, especially when using a simple and straightforward RSSI parameter.

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