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JOIV : International Journal on Informatics Visualization
ISSN : 25499610     EISSN : 25499904     DOI : -
Core Subject : Science,
JOIV : International Journal on Informatics Visualization is an international peer-reviewed journal dedicated to interchange for the results of high quality research in all aspect of Computer Science, Computer Engineering, Information Technology and Visualization. The journal publishes state-of-art papers in fundamental theory, experiments and simulation, as well as applications, with a systematic proposed method, sufficient review on previous works, expanded discussion and concise conclusion. As our commitment to the advancement of science and technology, the JOIV follows the open access policy that allows the published articles freely available online without any subscription.
Arjuna Subject : -
Articles 16 Documents
Search results for , issue "Vol 5, No 1 (2021)" : 16 Documents clear
Autonomous Agents in 3D Crowd Simulation Through BDI Architecture Sim Keng Wai; Cheah WaiShiang; Muhammad Asyraf bin Khairuddin; Yanti Rosmunie Binti Bujang; Rahmat Hidayat; Celine Haren Paschal
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.371

Abstract

Agent based simulation (ABS) is a paradigm to modelling systems included of autonomous and interacting agents. ABS has been tremendous growth and used by researchers in the social sciences to study socio-environmental complex systems. To date, various platforms have been introduced for agent-based social simulation. They are rule based in any logic, python based in SPADE and etc. Although those platforms have been introduced, there is still an insufficient to develop a crowd simulation in 3D platform. Having a 3D platform is needed to enabling the crowd simulation for training purposes. However, the current tools and platform still lack features to develop and simulate autonomous agents in the 3D world. This paper introduced a BDI plug in at Unity3D for crowd simulation. BDI is an intelligent agent architecture and it is able to develop autonomous agents in crowd environment. In this paper, we present the BDI plug with a case study of Australia bush fire and discuss a method to support autonomous agents' development in 3D crowd simulation. The tool allows the modeller to develop autonomous agents in 3D world by taking the advantages of Unity3D.
Single Image Dehazing Using Deep Learning Cahyo Adhi Hartanto; Laksmita Rahadianti
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.431

Abstract

Many real-world situations such as bad weather may result in hazy environments. Images captured in these hazy conditions will have low image quality due to microparticles in the air. The microparticles light to scatter and absorb, resulting in hazy images with various effects. In recent years, image dehazing has been researched in depth to handle images captured in these conditions. Various methods were developed, from traditional methods to deep learning methods. Traditional methods focus more on the use of statistical prior. These statistical prior have weaknesses in certain conditions. This paper proposes a novel architecture based on PDR-Net by using a pyramid dilated convolution and pre-processing modules, processing modules, post-processing modules, and attention applications. The proposed network is trained to minimize L1 loss and perceptual loss with the O-Haze dataset. To evaluate our architecture's result, we used structural similarity index measure (SSIM), peak signal-to-noise ratio (PSNR), and color difference as an objective assessment and psychovisual experiment as a subjective assessment. Our architecture obtained better results than the previous method using the O-Haze dataset with an SSIM of 0.798, a PSNR of 25.39, but not better on the color difference. The SSIM and PSNR results were strengthened by using subjective assessments and 65 respondents, most of whom chose the results of the restoration of the image produced by our architecture.
GDSS Prototype Model for Supplier Selection at MDM Cooperative Meri Azmi; Yance Sonatha; Indri Rahmayuni; Kristine Mae Paboreal Dunque; Dwi Sudarno Putra
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.473

Abstract

MDM is a trade cooperative business unit that supplies healthy food options for consumers around the Andalas University campus. So far, the selection of suppliers that provide supply goods to the stores is only based on the trust between both parties, which is the principle of mutual acquaintance and kinship. The problems that may arise from a process like this are the lack of the right supplier, unavailability of goods, relatively higher product prices, late delivery, and low-quality goods. Therefore, we need a GDSS that is capable of overcoming these problems. This GDSS helps in decision-making by determining the right supplier for each of the stores owned by the MDM Cooperative. The methods used are AHP, TOPSIS, and BORDA, involving six criteria and five tested alternatives. The AHP method is used to obtain the weight of each criterion taken from the pairwise comparison matrix. The TOPSIS method is used to determine which suppliers get priority for supply goods. Combining the AHP and TOPSIS methods can reduce the weaknesses of the TOPSIS itself by giving subjective weights. The use of the BORDA method can provide maximum results in selecting this supplier. This GDSS also involves three decision-making bodies: the head of the cooperative, the deputy, and the treasurer. The results of this prototype can show the best alternative selected based on the ranking method.
Application of Neural Network Time Series (NNAR) and ARIMA to Forecast Infection Fatality Rate (IFR) of COVID-19 in Brazil Ansari Saleh Ahmar; Eva Boj
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.372

Abstract

Forecasting is a method that is often used to view future events using past time data. Past time data have useful information to use in obtaining the future. The aim of this study was to forecast infection fatality rate (IFR) of COVID-19 in Brazil using NNAR and ARIMA. ARIMA and NNAR are used because (1) ARIMA is a simple stochastic time series method that can be used to train and predict future time points and ARIMA also capable of capturing dynamic interactions when it uses error terms and observations of lagged terms; (2) the Artificial Neural Network (ANN) is a technique capable of analyzing certain non-linear interactions between input regressor and responses, and Neural Network Time Series (NNAR) is one method of ANN in which lagged time series values were used as inputs to a neural network. Data included in this study were derived from the total data of confirmed cases and the total data of death of COVID-19. The data of COVID-19 in Brazil from February 15, 2020 to April 30, 2020 were collected from the Worldometer (https://www.worldometers.info/coronavirus/) and Microsoft Excel 2013 was used to build a time-series table. Forecasting was accomplished by means of a time series package (forecast package) in R Software.  Neural Network Time Series and ARIMA models were applied to a dataset consisting of 76 days. The accuracy of forecasting was examined by means of an MSE. The forecast of IFR of COVID-19 in Brazil from May 01, 2020 to May 10, 2020 with NNAR (1,1) model was around in 6,85% and ARIMA (0,2,1) was around in 7.11%.
Measuring the Quality of the Development Process Academic System with E-GQM Method - Sarwosri; Maidina Choirun Nisa; Siti Rochimah; Rizky Januar Akbar; Umi Laili Yuhana
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.424

Abstract

In a software development project, aspects of software quality are fundamental; all stakeholders expect high-quality software. To ensure the quality of software products, it is necessary to ensure the software quality process. A software process is essential to be assessed from their quality. In the software development process, the developer needs guidance in carrying out every aspect of it. The goals to achieve and the procedure to measure for each aspect's goals performance must be determined. One method that can be used is the Extended Goal Question Metric method. This method determines what aspects must be achieved for each development process. A few goals to measure are defined for each aspect. For each goal, one or more goals determine one or more relevant questions. For each question, an appropriate metric is  determined. The next step is mapping between G to Q and Q to M. The measurement was conducted by calculating the goal value obtained from the metric calculation. From this metric, each goal's value could be obtained, whether it is achieved or not. The tests were carried out on the software process to develop the academic Directorate of Technology and Information System Development of Institut Teknologi Sepuluh Nopember Surabaya, Indonesia. Each goal's value exceeded 0.51 (for a scale of 0-1), which achieved the Software development process's quality. The total average score was 0.889.
Social Media Engineering for Issues Feature Extraction using Categorization Knowledge Modelling and Rule-based Sentiment Analysis M Tafaquh Fiddin Al Islami; Ali Ridho Barakbah; Tri Harsono
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.397

Abstract

A company maintains and improves its quality services by paying attention to reviews and complaints from users. The complaints from users are commonly written using human natural language expression so that their messages are computationally difficult to extract and proceed. To overcome this difficulty, in this study, we presented a new system for issues feature extraction from users’ reviews and complaints from social media data. This system consists of four main functions: (1) Data Crawling and Preprocessing, (2) Categorization Knowledge Modelling, (3) Rule-based Sentiment Analysis, and (4) Application Environment. Data Crawling and Preprocessing provides data acquisition from users’ tweets on social media, crawls the data and applies the data preprocessing. Categorization Knowledge Modelling provides text mining of textual data, vector space transformation to create knowledge metadata, context recognition of keyword queries to the knowledge metadata, and similarity measurement for categorization. In the Rule-based Sentiment Analysis, we developed our own rules of computatioal linguistics to measure polarity of sentiment. Application Environment consists of 3 layers: database management, back-end services and front-end services. For applicability of our proposed system, we conducted two kinds of experimental study: (1) categorization performance, and (2) sentiment analysis performance. For categorization performance, we used 8743 tweet data and performed 82% of accuracy. For categorization performance, we made experiments on 217 tweet data and performed 92% of accuracy.
Developing Online Learning Applications for People with Hearing Impairment Hidra Amnur; Yandri Syanurdi; Rika Idmayanti; Aldo Erianda
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.457

Abstract

To make a communication with a hearing-impaired person, who is someone who has a problem with hearing ability, a special form of communication using sign language is required in order to make the purpose of the conversation convey properly. It is clearly that providing a proper and appropriate education for hearing impaired person is very important. Android technology is the best and useful solution for hearing-impaired person in learning as today's technological developments. The purpose of this research was to make an Android-based application for hearing impaired person. Scrum method was used to find and utilize existing libraries as well as the needs for application development. This application provides various kinds of subject from videos and documents uploaded by the teachers. It can be downloaded of it, if it is needed. It means that the users can study anytime and anywhere without concerning of limited time and internet access. Other features of the application are quiz, make schedule, event, chat, memory game, and other features to maximize the online learning process for hearing-impaired person.
How is The Adoption of Digital Marketing Services for Smart City Application Users? Regina Eka Riantini; Viany Utami Tjhin; Robertus Nugroho Perwiro Atmojo
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.438

Abstract

Smart City Mobile Apps is currently being developed by property developers in major cities in Indonesia and is used by businesses to market their products through the application. Technology integration in city governance is possible, thanks to the internet of things, a network of electronic devices interconnected and capable of sending data or following up with minimal human intervention. This study aims to identify the characteristics of Smart City Mobile Apps users in the South Tangerang area. The method used to see how well the implementation of digital marketing in Smart City Mobile Apps combines the TAM (Technology Acceptance Model) and UTAUT (Unified Theory of Acceptance and Use of Technology) models. Questionnaire data were processed using the Structural Equation Modelling (SEM) method. The study results state that the company's digital marketing strategy through Smart City Mobile Apps is already satisfying. It can be seen from the value of adoption of Smart City Mobile Apps users in utilizing this application, which is considerably large at 0.764 based on the coefficient of determination. The attitude variable influences consumers to use the application in finding trade information in the Smart City, with an influence value of 0.412 and the behavior intention to use with an influence value of 0.726, which shows that the intended behavior of the application and the trust in the benefits of the application can encourage users to use this application for purchasing their daily needs.
Improving the Response Time of Online Letter Management Application Users: an Application of Social Representation Theory of Shame Jefri Marzal; Wahyu Budiman; - Adrefiza; Benetika F. Hutabarat; Wawan Kurniawan
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.442

Abstract

One of the most important and potential problems encountered in an official online letter management application is the recipients' late response. This action research aims to improve the recipients' response time and determine the central core of shyness according to response time categories: less than 24 hours (green zone); between 24 hours to 48 hours (orange zone); and more than 48 hours (red zone) in managing formal online letter management system at Jambi University. Using the social representation theory of shyness as the basis of action adopted from Moscovici theory [1], it is hypothesized that response time displaying will impact response time improvement. A survey questionnaire distributed to 129 respondents showed a significant improvement in the participants' response time, respectively, in cycles 1 and 2. The zone group increased percentage sed from 22.44% to 52.49 % in the first cycle, and it ultimately raised to 62.38% at the end of the second cycle. Such an increase might be due to the users' efforts to avoid the level of shyness, which were classified into: (1) slow to respond and (2) personal or work unit late response time – both marked in red. It is recommended that social shyness incorporated in improving response time in a formal online letter can be further implemented with other social and psychological parameters. The application will illustrate computer systems' interaction on social society to implement regulations both in institutions and in government.
Hesitant Fuzzy-Stochastic Data Envelopment Analysis (HF-SDEA) Model for Benchmarking Dahlan Abdullah; - Hartono; Cut Ita Erliana
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.405

Abstract

The Data Envelopment Analysis (DEA) method is a method commonly used in benchmarking. The Dynamic Data Envelopment Analysis (DDEA) method was proposed to improve the DEA method in the benchmarking process. The DDEA method proposed can determine the effectiveness of the Decision Making Unit (DMU). The disadvantage of the DDEA model is that it cannot handle problems that involve benchmarking for stochastic data. To improve the DDEA method, the Stochastic Data Envelopment Analysis (SDEA) method is proposed which can be used for benchmarking involving stochastic data. The SDEA method itself has weaknesses in dealing with noise and uncertainty problems that will appear in the assessment process. The purpose of the research conducted by the researcher was to use the Hesitant Fuzzy method in optimizing the SDEA method so that the Hesitant Fuzzy model - Stochastic Data Envelopment Analysis (HF-SDEA) could be carried out benchmarking process in a situation where the assessment contained many elements of uncertainty. The results of this study are benchmarking methods that can do benchmarking for stochastic data on conditions that contain elements of uncertainty.

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