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JOIV : International Journal on Informatics Visualization
Published by Politeknik Negeri Padang
ISSN : 25499610     EISSN : 25499904     DOI : -
Core Subject : Science,
Computer Science & IT
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 1,172 Documents
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Applied Fuzzy and Analytic Hierarchy Process in Hybrid Recommendation Approaches for E-CRM Elham Abdulwahab Anaam; Su-Cheng Haw; Palanichamy Naveen
JOIV : International Journal on Informatics Visualization Vol 6, No 2-2 (2022): A New Frontier in Informatics
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.2-2.1043

Abstract

To create a personalized E-CRM recommendation system, the electronic customer relationship management system needs to investigate low accuracy and lack of personalization through applied hybrid recommendation system techniques such as fuzzy and AHP. The main purpose of this research is to enhance the accuracy and deep understanding of common recommendation techniques in E-CRM. The fuzzy and AHP techniques have been used in the current study to the available information of objects and to extend recommendation areas. The findings indicate that each of these strategies is appropriate for a recommendation system in a technological environment. The present study makes several noteworthy contributions to the fuzzy Analytic Hierarchy Process (AHP) and has the maximum accuracy of any of these approaches, with 66.67% of accuracy. However, AHP outperforms all others in terms of time complexity. We advocate the concept and implementation of an intelligent business recommendation system dependent on a hybrid approval algorithm that serves as a model for E–CRM recommendation systems. This recommendation system's whole design revolves on the hybrid recommendation system. The systems additionally incorporate the recommendation modules and the recommendation measurement updating framework. The recommendation modules include the formulation and development of material recommendation algorithms, element collaborative filtering recommendation algorithms, and demography-based recommendation algorithms.
A Study of Database Connection Pool in Microservice Architecture Nur Ayuni Nor Sobri; Mohamad Aqib Haqmi Abas; Ihsan Mohd Yassin; Megat Syahirul Amin Megat Ali; Nooritawati Md Tahir; Azlee Zabidi; Zairi Ismael Rizman
JOIV : International Journal on Informatics Visualization Vol 6, No 2-2 (2022): A New Frontier in Informatics
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.2-2.1094

Abstract

The growing number of Internet presents a higher requirement to backend application systems nowadays to be designed to handle thousands of users traffic concurrently. Microservice architecture is also in a rising trend which they allow for each service to scale horizontally by their throughput and load helps to scale the system efficiently without waste of resources like in the traditional monolithic application system. Among the many strategies to optimize delivery, database connection pool helps backend systems to access databases efficiently by reusing database connections, thus eliminating the computationally expensive need to open and close connections with new requests. Additionally, database connection pools can also help improve the connection reliability for applications. This paper aims to determine the most suitable maximum amount of database connections in a microservice setting, where multiple instances of the service are used for scalability and high availability purposes of the system. To tackle the issue of scalability and to achieve high availability of our services, we propose running multiple instances of each of our services in production, especially for services that we anticipate will be hit the most during runtime. This is to allow load balancing of request load between multiple instances and having backup instances to serve HTTP requests when one of the instances is down. The result obtained in this experiment shows that 5 database connections give the best result in microservice settings as described in our methodology.
Investigation on Java Mutation Testing Tools Abbas, Sara Tarek ElSayed; Hassan, Rohayanti; Halim, Shahliza Abd; Kasim, Shahreen; Ramlan, Rohaizan
JOIV : International Journal on Informatics Visualization Vol 6, No 2-2 (2022): A New Frontier in Informatics
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.2-2.1090

Abstract

Software Testing is one of the most significant phases within the software development life cycle since software bugs can be costly and traumatic. However, the traditional software testing process is not enough on its own as some undiscovered faults might still exist due to the test cases’ inability to detect all underlying faults. Amidst the various proposed techniques of test suites’ efficiency detection comes mutation testing, one of the most effective approaches as declared by many researchers. Nevertheless, there is not enough research on how well the mutation testing tools adhere to the theory of mutation or how well their mutation operators are performing the tasks they were developed for. This research paper presents an investigative study on two different mutation testing tools for Java programming language, namely PIT and µJava. The study aims to point out the weaknesses and strengths of each tool involved through performing mutation testing on four different open-source Java programs to identify the best mutation tool among them. The study aims to further identify and compare the mutation operators of each tool by calculating the mutation score. That is, the operators’ performance is evaluated with the mutation score, with the presumption that the more prominent the number of killed mutants is, the higher the mutation score, thus the more effective the mutation operator and the affiliated tool. 
The Relevance of Bibliometric Analysis to Discover the Area’s Research Efforts: Root Exploit Evolution Che Akmal Che Yahaya; Ahmad Firdaus; Ferda Ernawan; Wan Isni Sofiah Wan Din
JOIV : International Journal on Informatics Visualization Vol 6, No 2-2 (2022): A New Frontier in Informatics
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.2-2.1095

Abstract

Malware steals, encrypts, and damages data of the targeted machines for private, money, or fame purposes. The types of malware are root exploit, cryptojacking, Trojan, worms, viruses, spyware, ransomware, and adware. Among these types, root exploit is one of the most destructive malware types since it disguises and obscures all types of malware and provides a mechanism for other malware to carry out malicious acts invisibly. In the interest to review the progress of root exploit efforts globally, there is a need to inspect all publications that involve root exploit. Among all malware reviews previously, to date, there is still no trace of any bibliometric analysis that demonstrates the research impacts of root exploit and trends in bibliometric analysis. Hence, this paper adopts bibliometric analysis specifically on root exploit studies which evaluate: (1) Wordcloud; (2) WordTreeMap; (3) Three fields plot; (4) Thematic evolution; (5) Thematic maps; (6) Correspondence analysis (CA); (7) Dendrogram; and (8) Multiple correspondence analysis (MCA). To conclude, our bibliometric discovers that; 1) Linux and Android become main interest in root exploit studies. 2) Types of root exploit in virtualization layer and studies to detect on this area are increasing. 3) USA and China have become the leaders in root exploit research. 4) Research studies are more towards memory forensics to detect root exploit, which is more promising. 5) Instead of researching new methods of root exploit in compromising victims, root exploit researchers were more focused on detecting root exploits.
An Improved Approach of Iris Biometric Authentication Performance and Security with Cryptography and Error Correction Codes Moi, Sim Hiew; Yong, Pang Yee; Hassan, Rohayanti; Asmuni, Hishammuddin; Mohamad, Radziah; Weng, Fong Cheng; Kasim, Shahreen
JOIV : International Journal on Informatics Visualization Vol 6, No 2-2 (2022): A New Frontier in Informatics
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.2-2.1091

Abstract

One of the most challenging parts of integrating biometrics and cryptography is the intra variation in acquired identifiers between the same users. Due to noise in the environment or different devices, features of the iris may differ when it is acquired at different time periods. This research focuses on improving the performance of iris biometric authentication and encrypting the binary code generated from the acquired identifiers. The proposed biometric authentication system incorporates the concepts of non-repudiation and privacy. These concepts are critical to the success of a biometric authentication system. Iris was chosen as the biometric identifier due to its characteristics of high accuracy and the permanent presence throughout an individual’s lifetime. This study seeks to find a method of reducing the noise and error associated with the nature of dissimilarity acquired by each biometric acquisition.  In our method, we used Reed Solomon error-correction codes to reduce dissimilarities and noise in iris data. The code is a block-based error correcting code that can be easily decoded and has excellent burst correction capabilities. Two different distance metric measurement functions were used to measure the accuracy of the iris pattern matching identification process, which are Hamming distance and weighted Euclidean distance. The experiments were conducted with the CASIA 1.0 iris database. The results showed that the False Acceptance Rate is 0%, the False Rejection Rate is 1.54%, and the Total Success Rate is 98.46%. The proposed approach appears to be more secure, as it is able to provide a low rate of false rejections and false acceptances.
Combination of Feature Extractions for Classification of Coral Reef Fish Types Using Backpropagation Neural Network Latumakulita, Luther Alexander; Arya Astawa, I Nyoman Gede; Mairi, Vitrail Gloria; Purnama, Fajar; Wibawa, Aji Prasetya; Jabari, Nida; Islam, Noorul
JOIV : International Journal on Informatics Visualization Vol 6, No 3 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.3.1082

Abstract

Feature extraction is important to obtain information in digital images, where feature extraction results are used in the classification process. The success of a study to classify digital images is highly dependent on the selection of the feature extraction method used, from several studies providing a combination of feature extraction solutions to produce a more accurate classification.  Classifying the types of marine fish is done by identifying fish based on special characteristics, and it can be through a description of the shape, fish body pattern, color, or other characteristics. This study aimed to classify coral reef fish species based on the characteristics contained in fish images using Backpropagation Neural Network (BPNN) method. Data used in this research was collected directly from Bunaken National Marine Park (BNMP) in Indonesia. The first stage was to extract shape features using the Geometric Invariant Moment (GIM) method, texture features using Gray Level Co-occurrence Matrix (GLCM) method, and color feature extraction using Hue Saturation Value (HSV) method. The third value of feature extraction was used as input for the next stage, namely the classification process using the BPNN method. The test results using 5-fold cross-validation found that the lowest test accuracy was 85%, the highest was 100%, and the average was 96%. This means that the intelligent model derived from the combination of the three feature extraction methods implemented in the BPNN training algorithm is very good for classifying coral reef fish.
A Real-Time Application for Road Conditions Detection based on the Internet of Things Sitanayah, Lanny; Angdresey, Apriandy; Kristalino, Evander
JOIV : International Journal on Informatics Visualization Vol 6, No 3 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.6.3.891

Abstract

Bad road conditions may lead to road accidents, especially when drivers are unaware of potholes. The presence of potholes can increase from time to time and may get worse due to road age and bad weather. With the Internet of Things technology, vehicles on the road can be a means of collecting road condition data, such as vibration. The raw vibration data are useful only after they are processed into meaningful information. Information about the condition of roads can help other road users be aware of potholes. This paper proposes an Internet of Things application for road conditions detection. We design and implement a device comprising one NodeMCU ESP8266, one accelerometer gyroscope sensor to detect the existence of potholes based on the amount of detected vibration, and a GPS module to get the information about potholes' locations. For the web service, we use REST API so that users can get real-time potholes' information in the Android application. To cluster potholes based on detected vibration, i.e., deep, medium, and shallow, we implement the k-means clustering algorithm with k = 3. The Android application utilizes a Google map to visualize potholes' locations and the result of clustering on a road map. We use colored pins to indicate the depth of potholes. Deep potholes are shown on the map using red pins, medium potholes using orange pins, and shallow potholes using green pins.
Blockchain-based Smart Contract for Decentralized Marketplace Yutia, Syifa Nurgaida; Zaini Fathiana, Rana; Zahrotul Fajriyah, Siti
JOIV : International Journal on Informatics Visualization Vol 6, No 2-2 (2022): A New Frontier in Informatics
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.2-2.1121

Abstract

The advance of information technology has a growing influence on one of the most popular social trends: online shopping. The rising popularity of online shopping among the general public, as indicated by the growth in the number of online purchasers each year, has prompted business owners to pursue online ventures. The marketplace is intrinsically tied to online buying activity that connects merchants and customers, allowing customers to search for various goods and services from various providers. However, service failures are vulnerable to centralized market systems that emerge frequently. When the company's services to customers fail to satisfy consumer expectations. A breakdown in purchasing and selling essential services, including product delivery and customer support, is referred to as service failure. As a result, not only does this harm confidence, but it may also cause clients to migrate to an alternative marketplace. The marketplace's competitiveness is based on consumer confidence. The decentralized marketplace can address this security concern. A decentralized marketplace is meant to build a system that does not require the confidence of a third party using blockchain technology and smart contracts that can record all transactions clearly and consistently, allowing them to serve as a single point of truth between distrusting entities. The findings largely support the feasibility of Ethereum Smart Contracts to construct a decentralized marketplace. However, there are some places where further study and development are needed.
Image Presentation Method for Human Machine Interface Using Deep Learning Object Recognition and P300 Brain Wave Nakajima, Rio; Rusydi, Muhammad Ilhamdi; Ramadhani, Salisa Asyarina; Muguro, Joseph; Matsushita, Kojiro; Sasaki, Minoru
JOIV : International Journal on Informatics Visualization Vol 6, No 3 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.3.949

Abstract

Welfare robots, as a category of robotics, seeks to improve the quality of life of the elderly and patients by availing a control mechanism to enable the participants to be self-dependent. This is achieved by using man-machine interfaces that manipulate certain external processes like feeding or communicating. This research aims to realize a man-machine interface using brainwave combined with object recognition applicable to patients with locked-in syndrome. The system utilizes a camera with pretrained object-detection system that recognizes the environment and displays the contents in an interface to solicit a choice using P300 signals. Being a camera-based system, field of view and luminance level were identified as possible influences. We designed six experiments by adapting the arrangement of stimuli (triangular or horizontal) and brightness/colour levels. The results showed that the horizontal arrangement had better accuracy than the triangular method. Further, colour was identified as a key parameter for the successful discrimination of target stimuli. From the paper, the precision of discrimination can be improved by adopting a harmonized arrangement and selecting the appropriate saturation/brightness of the interface.
Development of Automatic Real Time Inventory Monitoring System using RFID Technology in Warehouse Erlangga, Setyawan Bayu; Yunita, Ajeng; Satriana, Sekarjatiningrum Rasmaydiwa
JOIV : International Journal on Informatics Visualization Vol 6, No 3 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.3.1231

Abstract

RFID technology is one of the technologies in logistics as an important application in logistics operations and supply chain management. The application of RFID technology can be applied to the inventory control monitoring system in real-time. The inventory monitoring information system can replace the manual system with a computerized system so that the processing of monitoring data is more efficient, effective, and can be controlled directly and accurately. This study presents a case study of a real stock monitoring system based on RFID technology. The design of a real-time stock monitoring system is transitioning from manual to technology by involving computerization in its implementation. This study aims to design an RFID-based real-time stock monitoring system and integrate warehousing systems in the company. The real-time inventory stock monitoring system is still developing, so a simulation is carried out to compare the existing data with the data from the RFID system. We used the existing warehouse layout to try the efficiency of the RFID stock monitoring. Based on the research results, the RFID system increases the efficiency and effectiveness of inventory control. In further research, it is necessary to integrate the inventory optimization model with real-time inventory control with RFID. The integration of real-time monitoring technology can be used as input to the inventory optimization model to be more accurate in providing purchasing policies.

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