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CommIT (Communication & Information Technology)
Published by Universitas Bina Nusantara
ISSN : 19792484     EISSN : 24607010     DOI : -
Core Subject : Science,
Computer Science & IT
Journal of Communication and Information Technology (CommIT) focuses on various issues spanning: software engineering, mobile technology and applications, robotics, database system, information engineering, artificial intelligent, interactive multimedia, computer networking, information system audit, accounting information system, information technology investment, information system development methodology, strategic information system (business intelligence, decision support system, executive information system, enterprise system, knowledge management), e-learning, and e-business (e-health, e-commerce, e-supply chain management, e-customer relationship management, e-marketing, and e-government). The journal is published in affiliation with Research Directorate, Bina Nusantara University in online and free access mode.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 478 Documents
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Analyzing the Effects of Combining Gradient Conflict Mitigation Methods in Multi-Task Learning Alison, Richard; Jonathan, Welly; Suhartono, Derwin
CommIT (Communication and Information Technology) Journal Vol. 18 No. 1 (2024): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v18i1.8905

Abstract

Multi-task machine learning approaches involve training a single model on multiple tasks at once to increase performance and efficiency over multiple singletask models trained individually on each task. When such a multi-task model is trained to perform multiple unrelated tasks, performance can degrade significantly since unrelated tasks often have gradients that vary widely in direction. These conflicting gradients may destructively interfere with each other, causing weights learned during the training of some tasks to become unlearned during the training of others. The research selects three existing methods to mitigate this problem: Project Conflicting Gradients (PCGrad), Modulation Module, and Language-Specific Subnetworks (LaSS). It explores how the application of different combinations of these methods affects the performance of a convolutional neural network on a multi-task image classification problem. The image classification problem used as a benchmark utilizes a dataset of 4,503 leaf images to create two separate tasks: the classification of plants and the detection of disease from leaf images. Experiment results on this problem show performance benefits over singular mitigation methods, with a combination of PCGrad and LaSS obtaining a task-averaged F1 score of 0.84686. This combination outperforms individual mitigation approaches by 0.01870, 0.02682, and 0.02434 for PCGrad, Modulation Module, and LaSS, respectively in terms of F1 score.
Insights into Mobile Government Adoption Factors: A Comprehensive Analysis of Peduli Lindungi Application in Indonesia Kurniasih, Denok; Setyoko, Paulus Israwan; Huda, Mohammad Nurul
CommIT (Communication and Information Technology) Journal Vol. 18 No. 1 (2024): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v18i1.9024

Abstract

Information and Communication Technology (ICT) progression has notably impacted the shift from traditional public services to digital alternatives. Among the various digital services, m-government services, provided by smartphone technology, have gained widespread popularity. Unfortunately, the broader adoption of digital technology encounters several challenges, including insufficient user interest and acceptance, as well as concerns regarding security and user privacy. The primary goal of the research is to address the existing gap in the literature by examining the factors that contribute to the effective implementation of m-government services. A mix of key components is employed, incorporating the Information Systems (IS) Success model and Technology Acceptance Model (TAM) as research variables. The research applies a quantitative approach in the form of an online survey. Furthermore, a Partial Least Square- Structure Equational Modeling (PLS-SEM) analytic approach is performed to evaluate 230 data points. The research findings support five hypotheses while rejecting three hypotheses. Significantly, the findings suggest that perceived usefulness and ease of use influence behavioral intention considerably. Additionally, constructions related to service quality significantly impact behavioral intention. Meanwhile, both system quality and information quality do not contribute to affecting behavioral intention. Furthermore, information quality exerts a substantial impact on perceived usefulness, but it does not influence perceived ease of use. Finally, it is observed that system quality significantly affects the perceived ease of use.
An Adaptive Heading Estimation Method based on Holding Styles Recognition Using Smartphone Sensors Nguyen-Huu, Khanh; Duong-Bao, Ninh; Thi, Luong Nguyen; Thi, Le Do; Thu, Thuy Huynh Thi; Lee, Seon-Woo
CommIT (Communication and Information Technology) Journal Vol. 18 No. 1 (2024): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v18i1.9196

Abstract

Pedestrian Dead Reckoning (PDR), which comes with many sensors integrated into widely available smartphones, is known as one of the most popular indoor positioning techniques. Sensors such as accelerometers, gyroscopes, and magnetometers are used to determine three important components in PDR: step detection, step length estimation, and heading estimation. Among them, the last component is the most challenging since a small heading error accumulates to produce a very large positioning error, especially when the pedestrian holds the smartphone in unconstrained styles such as swinging the phone freely along the pedestrian’s walking direction or putting the phone into the pants’ front pockets. The research proposes an adaptive heading estimation method to deal with heading errors caused by smartphone holding styles. The novelties are described as follows. Firstly, the proposed method attempts to classify the four basic smartphone holding styles using a machine learning algorithm based on simple features of acceleration values to give pedestrians more freedom during the walking period. Secondly, the proposed method adaptively combines the two heading estimation methods, which are calculated from the integrated sensors, to determine the walking direction for different smartphone holding styles. The experimental results show that the proposed heading estimation method achieves average heading errors of less than 30 degrees when testing in two different walking paths with the smartphone held in dynamic styles. It helps to reduce the heading errors by more than 15% compared to previous heading estimation methods.
The Determinant Factors of Shopping Cart Abandonment Among E-commerce Customers in Indonesia Sundjaja, Arta Moro; Tatuil, Ariel Velasco; Scholus, Dionisius Vincent; Restiani, Yolanda Dwi
CommIT (Communication and Information Technology) Journal Vol. 18 No. 1 (2024): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v18i1.9308

Abstract

Predicting the non-purchase behavior of potential customers, such as the abandonment of online shopping carts, is a pivotal factor in determining the success of companies. Despite several conducted studies, further investigation is still required to gain a profound understanding of the underlying causes of these phenomena. The research aims to analyze the motivating factors behind shopping cart abandonment among ecommerce customers in Indonesia using a quantitative method. Furthermore, the population size is undefined, and the sample consists of 200 respondents selected through purposive sampling. The sample size is determined by five times the indicator number. The data analysis is conducted using Structural Equation Modeling (SEM) through SmartPLS 4.0.8.5, and the Coefficient of determination (R2) value for shopping cart abandonment is found to be 37.5%. The results show that complicated checkout, information overload, complicated policies, and limited shipping options positively impact shopping cart abandonment. Complicated checkout emerges as the most significant variable. Meanwhile, perceived cost and emotional ambivalence have no impact. The research also provides theoretical contributions and suggests future research for e-commerce companies and merchants. The theoretical contribution is how user emotions, user experience, merchant policies, and e-commerce regulation affect shopping cart abandonment. From the practical implications, e-commerce companies should focus on the user experience during checkout to reduce shopping cart abandonment.
Uncovering the Risk of Academic Information System Vulnerability through PTES and OWASP Method Putra Utama, Ferzha; Hilmi Nurhadi, Raden Muhammad
CommIT (Communication and Information Technology) Journal Vol. 18 No. 1 (2024): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v18i1.9384

Abstract

The security of academic information systems needs consideration to anticipate various threats, resulting in data leakage, misuse of information, modification, and data destruction. There are 36 public and private universities that utilize the academic information system provided by the software developed by Company XYZ. Limited resources in universities contribute to the weak handling of vulnerabilities in academic information systems. The research aims to determine the vulnerability level of academic information systems developed by Company XYZ through penetration testing. The research employs a deductive approach to explore academic system vulnerabilities based on incidents related to system security issues at a university. The research utilizes a combination of two testing methods: Penetration Testing Execution Standard (PTES) and Open Web Application Security Project (OWASP), chosen for their reliability, ease of use, and support by penetration testing tools. Penetration testing follows the PTES, involving seven steps: pre-engagement interaction, information collection, threat modeling, vulnerability analysis, exploitation, postexploitation, and reporting. The threat focus in the research aligns with the top 10 of 2021 OWASP, ranking the ten most critical security risks. Results reveal eight critical security issues based on measurements using the Common Vulnerability Scoring System (CVSS) method. There are two high-level vulnerabilities, five medium-level vulnerabilities, and one low-level vulnerability. Moreover, the three principal vulnerabilities are Structured Query Language (SQL) Injection, broken access control, and weak encryption. Universities can enhance data integrity by independently remediating vulnerabilities discovered in the research. Furthermore, universities are encouraged to raise awareness within the academic community regarding the security of academic data.
Smart Aquaculture Design for Vannamei Shrimp Farming Based on Quality Function Development Setiawan, Budi; Surantha, Nico
CommIT (Communication and Information Technology) Journal Vol. 18 No. 2 (2024): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v18i2.9466

Abstract

In the fishery industry, Indonesia’s large water area has the potential for developing and cultivating fisheries such as vannamei shrimp. For this reason, aquaculture, particularly vannamei shrimp farming, can play a crucial role in Indonesia’s economy and food supply. However, challenges such as fluctuating water quality, disease outbreaks, turbidity levels, and irregular shrimp feeding schedules in ponds can affect the productivity and sustainability of shrimp farming. The smart aquaculture system integrates technologies, such as IoT-based sensors, automated feeding mechanisms, and real-time water quality monitoring to optimize the farming process. The research proposes a smart aquaculture design for vannamei shrimp farming based on the Quality Function Development (QFD) method. It starts by creating questionnaires to identify stakeholders’ level of interest. The questionnaire results are used as a reference for system redesign using the QFD method to improve the quality and quantity of shrimp harvest, cultivating effectively and efficiently and helping and facilitating the supervision of pond managers on pond water quality, feeding, and feed availability. The result highlights the application of QFD in creating a tailored, technology-driven solution that supports better decision-making, resource optimization, and improved shrimp health. The system reduces human error, enhances farm management, and promotes higher yields by providing real-time data and automation. The evaluation results show that the proposed design can achieve high stakeholder satisfaction. It also achieves better scores compared to the other two competitor’s designs.
Classification Taxonomies Genus of 90 Animals Using Transfer Learning Resnet-152 Saputro, Satria Nur; Adhinata, Faisal Dharma; Athiyah, Ummi
CommIT (Communication and Information Technology) Journal Vol. 18 No. 1 (2024): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v18i1.9482

Abstract

The process of learning theory and the limited ability to remember anything, especially a foreign language, often cause students to have difficulty understanding lessons, especially in determining the type and taxonomy of the animal. With the assistance of computer vision technology, students can more effectively face various challenges, enhance their understanding, and improve their ability to apply the concept of animal classification. The research classifies the taxonomy of 90 animals using Transfer Learning ResNet 152. It aims to analyze the performance of Transfer Learning ResNet 152 on the 90-animal dataset. The results show that in Model A with an architecture with frozen layers in 6 ResNet blocks, the highest evaluation value obtained is 0.9222 on Batch size 4 with Dropout 6, 0.9241 on Batch size 8 with Dropout 7, 0.9259 on Batch size 16 with Dropout 8, and 0.9296 on Batch size 32 with Dropout 4 and Dropout 7. Meanwhile, in model B with an architecture with frozen layers in 5 ResNet blocks and one non-frozen block, the highest evaluation value obtained is 0.7611 on Batch size 4 with Dropout 8, 0.8713 on Batch size 8 with Dropout 2, 0.8852 on Batch size 16 with Dropout 1, and 0.9204 on Batch size 32 with Dropout 3.
Fuzzy-Based Decision Support Model for Assessing Green Building Performance Widayat, Muhamad Akbar Bin; Utama, Ditdit Nugeraha
CommIT (Communication and Information Technology) Journal Vol. 18 No. 2 (2024): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v18i2.9797

Abstract

Global warming is currently a major environmental issue that is capable of causing unpredictable climate changes. The phenomenon is due to the accumulation of gases and carbon dioxide in the earth’s atmosphere, partly attributed to building operation and construction. The Green Building Rating System (GBRS) is developed to assess and measure the level of green building practices to address this problem. The assessments have typically been conducted using conventional methods that require parameters to meet specific criteria. However, certain parameter values cannot be calculated using objective methods, such as bias, time series, and distance values. The existence of these challenges leads to the development and integration of the Decision Support Model (DSM) into the GBRS in the research. The DSM uses a mathematical model, Tsukamoto Fuzzy Inference System (FIS), and conventional methods to handle the parameter values. Moreover, data related to the parameters are collected and analyzed quantitatively. As a result, the DSM-GBRS model is successfully implemented with two findings. First, there are 83 parameters, related to policy, retrofit, construction, and utilization aspects based on Peraturan Menteri Pekerjaan Umum dan Perumahan Rakyat Nomor 21 Tahun 2021. Second, the model provides precise decision values by splitting the treatment into four types: conventional, Fuzzy logic, slope, and Euclidean distance to ensure a comprehensive assessment of green building performance.
Data Monetization Service Development Using Iterative Lifecycle Framework, Quality Assurance, and Open Web Application Security Project: A Case Study of a Utility Company in Indonesia Kusuma Atmaja, Wahyu Haris; Warnars, Harco Leslie Hendric Spits; Gaol, Ford Lumban; Soewito, Benfano
CommIT (Communication and Information Technology) Journal Vol. 18 No. 2 (2024): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v18i2.10293

Abstract

The research aims to provide Data Monetization (DM) services for an Indonesian utility company as a pilot to generate additional revenue beyond the primary operation. The service is built using an iterative development lifecycle framework and evaluated based on five Quality Goals (QGs), including application and security testing activities. The framework includes methods for processing and modeling electricity usage data, testing application quality, checking infrastructure quality, and ensuring access security for front-end and back-end applications using the Open Web Application Security Project (OWASP). For data modeling, Support Vector Regression (SVR) is used, and it outperforms Polynomial Regression (PR) and Multi-Layer Perception (MLP) Neural Networks. Furthermore, QG shows strong performance with an Relative Root Mean Squared Error (RRMSE) value < 10%, high forecasting ability with Mean Average Probability Error (MAPE) < 10%, and a near-zero average error rate (Mean Squared Error (MSE)) square using minimal data from four months. The services go through functional and integration test to ensure product quality and application performance, which results in a minimum of 95% service response in throughput, 0.128 seconds for processing 2,000 requests, stability at 300–500 in one second per hour, and 7–21 seconds during peak hours. Additionally, the service passes nine penetration tests and ten vulnerability assessments using the OWASP top 10:2021 category. Based on the comprehensive testing and evaluation results, both the application and the service are considered ready and secured for deployment.
Simulating Free-Space Optical Communications to Support a Li-Fi Access Network in a Smart City Concept Darusalam, Ucuk; Nathasia, Novi Dian; Zarlis, Muhammad; Priambodo, Purnomo Sidi
CommIT (Communication and Information Technology) Journal Vol. 18 No. 1 (2024): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v18i1.10458

Abstract

Smart city development has grown rapidly in the decades since 4G and 5G technologies have been released. Moreover, a highly reliable network is required to support the Internet of Things (IoT) and mobile access within a city. Light Fidelity (Li-Fi) technology can provide huge bitrate transmission and high-speed communications. In the research, a backbone based on Free-Space Optical (FSO) communication (FSO) is designed through simulation to provide a Li-Fi access network with a high capacity data rate. The originality of the proposed method is the implementation of double filtering techniques, which gives an advantage when forwarding the signal to a node and improves the quality of the signal received by the Li-Fi. The FSO as the Optical Relaying Network (ORN) is designed with a configuration of 12 channels of Dense Wavelength Division Multiplexing (DWDM) amplified by optical amplifiers in the transmitter and receiver. The signal output is filtered by a Fiber Bragg Grating (FBG) and a Gaussian filter. In the simulation, the ORN has node spacing in the range of 500 m to 2,000 m. Then, the data transmission rate at 120 Gbps is provided by the implementation of DWDM channels to serve as an access network. From the simulation, the FSO backbone can optimally deliver highly reliable Li-Fi access networks. When the nodes are spaced in a 500–2,000 m range, the Bit-Error-Rate (BER) performance is produced at the order of 10−6.

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