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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 5 Documents
 1 
Search results for , issue "Vol. 6 No. 1 (2020): June 2020" : 5 Documents clear
A Persuasive Technology for Managing Waste Disposal through Smart Trash Bin and Waste Disposal Tracker Oscar Karnalim; Oscar Wongso; Vincent Elbert Budiman; Felix Christian Jonathan; Bertha Alan Manuel; Marlina Marlina
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.2020.61.117

Abstract

Waste management issue is a relevant topic that had been focused on many persuasive technologies. This issue is not only related to getting disposed of waste in proper places but also reducing waste disposal volume. This paper proposes a persuasive system that aims both goals by providing a smart trash bin and waste disposal tracker. The smart trash bin is an IoT-featured trash bin whereas waste disposal tracker is a mobile application which can record user daily waste disposal volume statistic. Based on the evaluation, our proposed system has achieved both goals. Additionally, it also solves several impediments such as incapability of moral background to encourage people to dispose waste on the trash bin, boring and monotonous waste disposal activity, and discouragement for disposing waste due to full trash bin. In order to attract people, our system includes attractive mechanisms such as playful experience, reflective experience, and gamification. Playful experience is applied to a smart trash bin, whereas the other two are applied to the waste disposal tracker.
Increasing the Security of RFID-based Classroom Attendance System with Shamir Secret Share Aji Gautama Putrada; Maman Abdurohman
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.2020.61.480

Abstract

This paper proposes an attendance system for increasing the security based on Shamir Secret Share algorithm. The use of RFID devices for classroom attendance is still vulnerable to certain attacks. Students usually make use of existing loopholes for prohibited things, such as forged attendance. Shamir Secret Share is a security method based on the Secure Multiparty Computation (SMC) concept. The SMC guarantees not only the confidentiality of external attacks but also of each member in the secure system. In the attendance scenario using Shamir Secret Share, a student and a lecturer must do tapping at the same time; otherwise, the secret that opens the lock for attendance at that class will not be opened. To realize this system, this paper uses two RFID modules, each of which is connected to one nodeMCU microcontroller. Both systems are connected to a database where the Shamir Shared Secret calculation is performed. Some experiment has been implemented for proving the concept. The result shows that some scenarios of fraud in RFID based attendance can be prevented.
Prediction and Simulation Spatio-Temporal Support Vector Regression for Nonlinear Data Khalilur Rahman; Margaretha Ari Anggorowati; Agung Andiojaya
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.2020.61.477

Abstract

Spatio-temporal model forecasting method is a forecasting model that combines forecasting with a function of time and space.  This method is expected to be able to answer the challenge to produce more accurate and representative forecasting. Using the ability of method Support Vector Regression in dealing with data that is mostly patterned non-linear premises n adding a spatial element in the model of forecasting in the form of a model forecasting Spatio- Temporal. Some simulations have done with generating data that follows the Threshold Autoregressive model. The models are correlated into spatial points generated by several sampling methods. Simulation models are generated to comparing the accuracy between model Spatio-Temporal Support Vector Regression and model  ARIMA  based on  Mean  Error,  Mean Average Error, Root Mean Square Error, and Mean Average Percentage Error. Based on the evaluation results, it is shown that forecasting with the Spatio-Temporal Support Vector Regression model has better accuracy than forecasting ARIMA.
WhatsApp Chat Visualizer: A Visualization of WhatsApp Messenger’s Artifact Using the Timeline Method Hardiansyah Shidek; Niken Cahyani; Aulia Arif Wardana
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.2020.61.489

Abstract

WhatsApp is a medium that everyone can use to interact and to share information effectively and efficiently. However, it can be misused for criminal activities. Analyzing WhatsApp' artifacts is quite challenging as the suspect may have a lot of random conversational data to be considered. This makes it difficult for the trial process to obtain digital traces that can be identified in malicious activities such as knowing who was involved when the conversation was held and the timespan. Therefore, in this research, a social media investigation of WhatsApp was carried out by acquiring data from rooted Android devices that were used as target devices for forensic activities. A python-based application is developed to show the content of the conversation, and a web-based application is presented to visualize the data using the Timeline method. Experimental results in this research display important timeline information such as information about who was involved when and what time the conversation was carried out with the suspect.
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.

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