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INDONESIA
Indonesian Journal on Computing (Indo-JC)
Published by Universitas Telkom
ISSN : 24609056     EISSN : -     DOI : -
Core Subject : Science,
Computer Science & IT
Indonesian Journal on Computing (Indo-JC) is an open access scientific journal intended to bring together researchers and practitioners dealing with the general field of computing. Indo-JC is published by School of Computing, Telkom University (Indonesia).
Arjuna Subject : -
Articles 6 Documents
 1 
Search results for , issue "Vol. 6 No. 3 (2021): December, 2021" : 6 Documents clear
Application of User-centred Design Method in Laundry Management Application Development Rizki Pambudi; Gita Fadila Fitriana; Rifki Adhitama
Indonesia Journal on Computing (Indo-JC) Vol. 6 No. 3 (2021): December, 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2021.6.3.591

Abstract

On a system from the user side often experience difficulties in its operation. To solve this problem, the laundry management application development process applies the User Centered Design method. The stages taken include Specify the Context of Use and Specify User and Organizational Requirements to identify, determine who the user is and the characteristics of the system user by conducting interviews with laundry business owners. Next, the Produce Design Solution stage is carried out, which is the stage of making a system that can be used by users. The last stage is Evaluate Designs against User Requirements by using Usability Testing to measure the appropriateness and success of the application as well as black box testing to test system functionality. The results of application development and testing using Usability Testing on the aspects of Usefulness, Ease of Use, Ease of Learning and Satisfaction get a feasibility score of 79.8% which means that the development of a laundry management application using the User Centered Design method is feasible because this application is easy to use, easy to learn, provides satisfaction and as expected and is useful for laundry entrepreneurs to manage their transaction data.
Implementation of LSTM-RNN for Bitcoin Prediction Nur Ghaniaviyanto Ramadhan; Nia Annisa Ferani Tanjung; Faisal Dharma Adhinata
Indonesia Journal on Computing (Indo-JC) Vol. 6 No. 3 (2021): December, 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2021.6.3.592

Abstract

Bitcoin is a cryptocurrency that is used worldwide for digital payments or simply for investment purposes. Bitcoin is a new technology so there are currently very few prices prediction models available. Problems arise when someone uses bitcoin without understanding strong fundamentals. This can result in a lot of loss for the person. These problems certainly need to be overcome by predicting bitcoin prices using a machine learning approach. The purpose of this research is to predict the bitcoin USD price using the Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) model. The LSTM-RNN model was chosen because it is better than the traditional neural network model. Measurement of the results in this study using the Root Mean Square Error (RMSE). The RMSE results obtained on the application of the LSTM-RNN model 6461.14.
Comparative Analysis of K-Nearest Neighbor and Modified K-Nearest Neighbor Algorithm for Financial Well-Being Data Classification Ichwanul Muslim Karo Karo
Indonesia Journal on Computing (Indo-JC) Vol. 6 No. 3 (2021): December, 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2021.6.3.593

Abstract

Financial Well-Being is the condition that a person has been able to meet current and future financial obligations. There are many parameters in determining people who have obtained financial well-being. Classification is a data mining task that can be used to identify someone with financial well-being. One of the most popular classification algorithms is K Nearest Neighbor (KNN). However, there is also a Modified K Nearest Neighbor (MKNN) classification algorithm which is an extended KNN. In this paper, we will analyze a comparison of KNN and MKNN algorithms to classify financial well-being datasets. Comparative analysis is based on the accuracy and running time of both algorithms. Prior to the classification process, K-Fold Cross Validation was performed to find the optimal data modeling. The results of the K Fold Cross Validation modeling will be a model for the sample of training data and data testing. Evaluation of classification results based on precision, recall, and F-1. The test resulted in a higher KKN performance compared to MKNN in all test parameters, with an average gap of 25 percent. In addition, it was also found that the execution time of the KNN algorithm was faster than that of the MKNN
Trials and Progress Prediction of Covid-19 Vaccine Using Linear Regression and SIR Parameters Ananda Aulia Rizky; Novi Rahmawati; Adil El-Faruqi; Faisal Dharma Adhinata; Nur Ghaniaviyanto Ramadhan
Indonesia Journal on Computing (Indo-JC) Vol. 6 No. 3 (2021): December, 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2021.6.3.594

Abstract

This study aims to elucidate the worldwide effectiveness of the COVID-19 vaccine to reduce the number of COVID-19 patients. Currently, almost all countries in the world are trying to overcome COVID-19 by imposing a lockdown system. The government is also looking for a solution to suppress the spread of COVID-19 by administering a vaccine. Vaccination is one of the efforts that are considered effective in overcoming COVID-19 in affected countries. At least 85 types of vaccines are still in the development stage, while the vaccines that have been agreed upon are Pfizer-Biotech messenger RNA vaccines (bnt162b2) and Moderna (mRNA-1273). The hope is that the COVID-19 outbreak can be handled immediately to restore the residents' economy with vaccination. The methodology used in this study uses data mining with linear regression and SIR techniques to evaluate whether circulating vaccines can effectively suppress the spread of COVID-19.
Design of API Gateway as Middleware on Platform as a Service Dita Oktaria; Joel Andrew M. K. Ginting; Maman Abdurohman; Rahmat Yasirandi
Indonesia Journal on Computing (Indo-JC) Vol. 6 No. 3 (2021): December, 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2021.6.3.597

Abstract

The process of building a platform is a process that consists of various stages, there is a focus of work and requires different preparation, but until now there has been no awareness in utilizing data and information sources that have been available to be used as a basis for developing or creating a platform that is able to improve quality a system of integrity. For this reason, a Platform as a Service (PaaS) architecture was built which provides application development services to process data and information obtained from practicum activities during the lecture period based on cloud computing using the Service Oriented Architectural (SOA) method. The API gateway is used as middleware system. The results of the implementation and analysis carried out prove that the architecture using the API gateway as a built-in middleware can be considered to develop the Telkom University lab service system. Although there are adjustments to resources and needs, but the purpose of this architectural development has generally been realized. From the results of tests performed on a platform architecture that uses a gateway API, it produces RTT 2.081 seconds, 45 MB memory, and 8% CPU for each user in 100 users.
IT Asset Assessment Using Quantitative Risk Analysis (QRA) Method at XYZ Cafe Rahmat Yasirandi; Emiya Fefayosa Br Tarigan
Indonesia Journal on Computing (Indo-JC) Vol. 6 No. 3 (2021): December, 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2021.6.3.613

Abstract

Many companies are starting to invest in information technology (IT) assets to improve their business performance and services in this era. This includes modern cafes, which are becoming a promising business trend, especially if they have branches in various places. As with XYZ Cafe, IT Assets play an essential role in running the business. This research has succeeded in utilizing the Quantitative Risk Analysis (QRA) Method to perform calculations and tabulations for any potential risks. The results show the increase in the value of losses by 371.5% of the issued IT Asset investment capital, or 477,388,063 Rupiah. In detail, through Across Asset Analysis, Across Asset Value is at the top of the rank, namely Mini PC, with a loss value of 127,440,000 Rupiah. Through Across Risk Analysis, the Accidental Errors is in the first rank with a loss value of 184,038,000 Rupiah. This result implies that stakeholders can develop and plan mitigation actions to reduce potential losses for the company. Mitigation actions can be in the form of regulations, standard operating procedures (SOP), proposed monitoring applications, or strategic plan at top-level management so every threat and risk can be controlled and managed.

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