eJournal Komunitas Dosen Indonesia
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PENGARUH STRUKTUR MODAL, FREKUENSI PERDAGANGAN, DAN VOLUME PERDAGANGAN SAHAM TERHADAP RETURN SAHAM
Full text linkThis study aims to examine the effect of capital structure, trading frequency, and trading volume on stock returns in companies listed in the banking sub-sector on the Indonesia Stock Exchange (IDX) during the period 2019–2023. The study employs a quantitative associative approach, which seeks to determine the relationship and influence between two or more variables. The population in this study includes all banking sub-sector companies listed on the IDX during the specified period. The sampling technique used is purposive sampling, resulting in 36 selected companies that meet the criteria, producing a total of 180 observations over five years. The data analysis method used is panel data regression analysis, which combines cross-sectional and time series data to provide more accurate and comprehensive results. The variables examined include capital structure as measured by debt to equity ratio (DER), trading frequency, trading volume, and stock return as the dependent variable. The results of the analysis show that simultaneously, capital structure, trading frequency, and trading volume have a significant effect on stock returns. However, partially, the capital structure does not have a significant effect on stock returns. Trading frequency also shows no significant effect. Meanwhile, trading volume has a significant positive effect on stock returns. These findings provide insight for investors and management in making investment and financial decisions.This study aims to examine the effect of capital structure, trading frequency, and trading volume on stock returns in companies listed in the banking sub-sector on the Indonesia Stock Exchange during the period 2019–2023. This is a quantitative associative study that focuses on the relationship between two or more variables. The population of this study consists of banking sub-sector companies listed on the Indonesia Stock Exchange (IDX) during the period 2019–2023. The sample for this study was selected using purposive sampling, resulting in 36 company samples yielding 180 observations. The analysis used in this study is panel data regression analysis with a quantitative approach. The results of the study indicate that simultaneously, capital structure, trading frequency, and stock trading volume have a significant effect on stock returns. Partially, capital structure shows no effect on stock returns, and trading frequency shows no effect on stock returns, while stock trading volume shows a significant effect
Evaluation of Watsons ID Application Adoption Among Generation Z Users: Applying the UTAUT2
Full text linkThe rapid advancement of digital technology has significantly transformed the retail landscape, particularly within the beauty and health e-commerce sector. In response to this shift, the Watsons ID application was developed to provide a fast, convenient, and feature-rich platform for online shopping. This study examines how Generation Z consumers in Indonesia adopt and use the Watsons ID application by applying the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework. A quantitative approach was employed using Partial Least Squares Structural Equation Modeling (PLS-SEM), with data collected from 410 respondents through purposive sampling. The research specifically targeted Indonesian Generation Z users who have experience with the Watsons ID application. The findings indicate that Performance Expectancy, Social Influence, Price Value, and Habit have a significant positive impact on users' intention to use the application. Furthermore, Habit and Behavioral Intention positively influence actual usage behavior. Conversely, Effort Expectancy and Facilitating Conditions do not show a significant effect on Behavioral Intention, and Facilitating Conditions also do not affect Use Behavior. These insights provide valuable guidance for e-commerce developers and beauty retailers seeking to optimize digital strategies, enhance user experience, and strengthen customer engagement specifically targeted toward Generation Z consumers in the Indonesian market
Optimizing 3-Axis CNC Router Design: Using QFD and DFM for Enhanced Precision and Efficiency
Full text linkThe development of the manufacturing industry demands continuous innovation in machine technology, particularly the 3 Axis CNC Router, which plays a crucial role in various applications such as cutting, milling, and material shaping.This research aims to design and develop a more efficient and precise 3 Axis CNC Router machine with a user needs-based approach in Indonesia.This machine is optimized using Quality Function Deployment (QFD) to identify consumer needs through questionnaire data, as well as Design for Manufacture (DFM) to ensure a design that is easy to produce and cost-efficient.The results of the QFD and DFM analysis are used to develop the machine with superior features, such as improved cutting precision, reduced noise, and enhanced resistance to corrosion and material dust accumulation. The developed machine is capable of improving cutting accuracy to ±0.05 mm and processing speed by 20% faster compared to the previous machine.Additionally, the noise reduction also reaches more than 15 dB, enhancing operator comfort during use.This research also identifies the main customer needs, such as machine safety, speed, and machine strength, as well as secondary needs, such as aesthetics and dirt prevention.These findings not only provide technical solutions to the existing issues with CNC machines but also suggest a direction for developing machines that are more responsive to the needs of small and medium-sized enterprises in Indonesia, as well as more efficient in material and cost usage
Design and Development of Web-Mobile Application for Housing Project Management Using KNN for Prediction
Full text linkProject management in housing development is essential to ensure timely completion, budget efficiency, and market alignment. However, many small to medium sized property developers still use manual systems, causing inefficiencies in monitoring, documentation, and sales planning. PT Bakti Luhur Abadi is one such company that still relies on Microsoft Excel for recording project progress and housing unit sales. This study aims to develop an integrated project management system equipped with a sales prediction feature using the K-Nearest Neighbors (KNN) algorithm. The goal is to improve operational efficiency, streamline decision making, and support strategic sales forecasting. The system was developed using the Waterfall method, comprising requirement analysis, system design, implementation, and testing. A key novelty of this research is the dual platform implementation web for administrators and mobile for directors and field teams enabling real time access, structured documentation, and effective communication. The KNN algorithm was tested with 30 test data and 114 training data using K values of 3, 5, and 7. The best result was achieved at K = 7 with an accuracy of 86.7%. Functional validation using black-box testing confirmed all web and mobile features operated as expected. In conclusion, the proposed application effectively automates project management and enables accurate sales prediction. It provides practical benefits for small and medium-scale property developers by increasing efficiency, improving internal coordination, and supporting data driven planning through an accessible and intelligent solution
Enhancing Access Control Security Using ISO 27001:2013 and OCTAVE Method
Full text linkThe development of Information Technology (IT) has brought various conveniences in organizational operations, but also introduced significant security risks. One of the most critical areas of concern is access control, where weaknesses can lead to unauthorized access and data breaches. While absolute security is difficult to achieve, structured governance frameworks are essential to minimize vulnerabilities. ISO/IEC 27001:2013 is an international standard that provides guidelines for managing information security risks, while the OCTAVE (Operationally Critical Threat, Asset, and Vulnerability Evaluation) method supports in-depth, organization-specific risk assessments. This study aims to enhance access control governance at PT. XYZ, an IT-based company, by integrating ISO 27001:2013 controls with the OCTAVE methodology. Risk evaluation is performed through the CIA (Confidentiality, Integrity, Availability) triad, based on internal knowledge collected via interviews with operational teams. The OCTAVE method identifies key assets, assesses threat probabilities, and evaluates business impacts, which are then mapped to appropriate ISO 27001 Annex 9 controls. The implementation resulted in several critical access control mechanisms, including User Access Management, Network and Service Access Restrictions, Privileged Access Management, and Password Security Policies. This combined framework enables PT. XYZ to address specific risk exposures more effectively and to ensure compliance with international standards. The integration of ISO 27001:2013 and OCTAVE provides a practical, risk-based model for access control governance that is adaptable to organizational context and resource constraints. The study offers a replicable reference for similar IT organizations seeking to strengthen their information security posture
Analysis of Factors Influencing the Acceptance of Riliv Application Using UTAUT2
Full text linkThe rapid growth of digital technologies has enabled the emergence of online counseling services as alternative solutions for addressing mental health issues. Riliv is one such platform that provides digital psychological support through professional consultations, guided meditation, and journaling features. However, few studies have applied the UTAUT2 model to examine user acceptance of such platforms within the Indonesian context. This research addresses that gap by extending the UTAUT2 model with three additional constructs: e-health literacy, privacy concern, and trust. A quantitative approach was employed through a structured survey of 400 participants, with data analyzed using SEM-PLS. The findings indicate that performance expectancy, effort expectancy, social influence, facilitating conditions, privacy concern, and trust significantly influence users’ behavioral intention to adopt Riliv. Interestingly, price value and e-health literacy were found to be insignificant, suggesting that users may place greater emphasis on emotional safety and social dynamics than on financial or informational aspects when choosing mental health platforms. Moreover, while performance expectancy is often a key predictor in technology adoption, it may be less dominant in emotionally driven contexts such as mental health. The extended UTAUT2 model proved effective in predicting user acceptance, confirming its relevance for evaluating digital mental health services in Indonesia. These insights emphasize the importance of building trust, ensuring privacy, and fostering a socially supportive, user-friendly experience. Collaboration between developers and mental health professionals is crucial to aligning technological design with user expectations and emotional needs.The rapid growth of digital technologies has enabled the emergence of online counseling services as alternative solutions for addressing mental health issues. Riliv is one such platform that provides digital psychological support through professional consultations, guided meditation, and journaling features. However, few studies have applied the UTAUT2 model to examine user acceptance of such platforms within the Indonesian context. This research addresses that gap by extending the UTAUT2 model with three additional constructs: e-health literacy, privacy concern, and trust. A quantitative approach was employed through a structured survey of 400 participants, with data analyzed using SEM-PLS. The findings indicate that performance expectancy, effort expectancy, social influence, facilitating conditions, privacy concern, and trust significantly influence users’ behavioral intention to adopt Riliv. Interestingly, price value and e-health literacy were found to be insignificant, suggesting that users may place greater emphasis on emotional safety and social dynamics than on financial or informational aspects when choosing mental health platforms. Moreover, while performance expectancy is often a key predictor in technology adoption, it may be less dominant in emotionally driven contexts such as mental health. The extended UTAUT2 model proved effective in predicting user acceptance, confirming its relevance for evaluating digital mental health services in Indonesia. These insights emphasize the importance of building trust, ensuring privacy, and fostering a socially supportive, user-friendly experience. Collaboration between developers and mental health professionals is crucial to aligning technological design with user expectations and emotional needs
Evaluation of the Quality Satisfaction the MELISA Information System with the WebQual 4.0 Method
Full text linkThe integration of information technology in higher education is essential to support academic and administrative activities. The MELISA Information System at Surabaya State University plays a vital role in meeting student needs. Periodic evaluation of user satisfaction is necessary to ensure the quality and effectiveness of the service, as poor system quality can hinder learning and productivity. This study aims to analyze and evaluate the quality of the MELISA Information System at Surabaya State University and its impact on student satisfaction. Specifically, this research seeks to determine how WebQual 4.0's Usability Quality, Information Quality, and Service Interaction Quality dimensions influence user satisfaction. Using a quantitative descriptive survey method, data was collected via online questionnaires from Surabaya State University students who use MELISA. System quality was measured using three dimensions of WebQual 4.0: Usability Quality, Information Quality, and Service Interaction Quality. Data analysis involved descriptive statistics and multiple linear regression to test the effect of quality dimensions on student satisfaction. The results show that Usability Quality, Information Quality, and Service Interaction Quality significantly affect student satisfaction with MELISA. The majority of respondents gave a positive assessment, although some improvements are still needed. Information Quality was found to be the most dominant influence on student satisfaction. The quality of the MELISA Information System, based on WebQual 4.0, is crucial for student satisfaction at Surabaya State University. To increase user satisfaction, the university must continue to improve the usability, accuracy of information, and quality of service interactions in the MELISA system
Analysis of Frequency Spectrum in Digital Image Transmission Using Orthogonal Frequency Multiplexing
Full text linkAccurate and efficient data transmission is increasingly essential due to the growing reliance on digital communication, particularly for multimedia content such as images. Orthogonal Frequency Division Multiplexing (OFDM) provides high bandwidth efficiency and strong noise resilience by transmitting data over multiple orthogonal subcarriers. Despite its advantages, limited studies have explored how modulation schemes influence frequency-domain characteristics during image transmission under different noise conditions. This study addresses that gap by evaluating digital image transmission through OFDM using Binary Phase Shift Keying (BPSK) and Quadrature Phase Shift Keying (QPSK) modulation. The objective is to compare spectral performance across various signal-to-noise ratio (SNR) levels. A grayscale image is converted into a binary stream, modulated using BPSK and QPSK, and processed through an OFDM system with 512 subcarriers and a 25% cyclic prefix. The signals are transmitted through an Additive White Gaussian Noise (AWGN) channel at SNR values of 0 dB, 5 dB, and 10 dB. Power Spectral Density (PSD) is measured using the Welch method with a Hamming window, 50% overlap, and 1024-point Fast Fourier Transform (FFT). The results show that increasing SNR improves spectral sharpness, reduces the noise floor, and enhances symmetry. BPSK offers better performance in noisy conditions, while QPSK is more efficient in high-SNR environments. These findings provide practical insight for optimizing modulation choices in OFDM-based image transmission systems where spectral efficiency and noise robustness must be balanced.Accurate and efficient data transmission is increasingly essential due to the growing reliance on digital communication, particularly for multimedia content such as images. Orthogonal Frequency Division Multiplexing (OFDM) provides high bandwidth efficiency and strong noise resilience by transmitting data over multiple orthogonal subcarriers. Despite its advantages, limited studies have explored how modulation schemes influence frequency-domain characteristics during image transmission under different noise conditions. This study addresses that gap by evaluating digital image transmission through OFDM using Binary Phase Shift Keying (BPSK) and Quadrature Phase Shift Keying (QPSK) modulation. The objective is to compare spectral performance across various signal-to-noise ratio (SNR) levels. A grayscale image is converted into a binary stream, modulated using BPSK and QPSK, and processed through an OFDM system with 512 subcarriers and a 25% cyclic prefix. The signals are transmitted through an Additive White Gaussian Noise (AWGN) channel at SNR values of 0 dB, 5 dB, and 10 dB. Power Spectral Density (PSD) is measured using the Welch method with a Hamming window, 50% overlap, and 1024-point Fast Fourier Transform (FFT). The results show that increasing SNR improves spectral sharpness, reduces the noise floor, and enhances symmetry. BPSK offers better performance in noisy conditions, while QPSK is more efficient in high-SNR environments. These findings provide practical insight for optimizing modulation choices in OFDM-based image transmission systems where spectral efficiency and noise robustness must be balanced
Business Optimization Through Implementation of Cost of Production Pricing System Using Bill of Material Method
No full textThe furniture industry often struggles with setting accurate selling prices due to the lack of structured and precise cost calculation systems. Many furniture entrepreneurs still rely on traditional methods that base prices on market trends, without accounting for underlying production costs. This often leads to prices that are too low, eroding profit margins, or too high, making it difficult to stay competitive. This study introduces a novel Cost of Goods Manufactured (COGM) calculation system, integrated with the Bill of Materials (BOM) method, to advance current pricing systems in the furniture industry. By incorporating key cost elements such as raw materials, labor, and the impact of waste and rework, the system enhances the accuracy of COGM calculations. Additionally, it offers greater transparency by providing a detailed breakdown of each cost component, allowing entrepreneurs to better understand their production expenses. The implementation of this system led to a 15% improvement in pricing accuracy, significantly reducing pricing errors and optimizing production costs. Furthermore, businesses reported a 20% increase in competitiveness due to more informed pricing strategies. This research demonstrates that integrating COGM with BOM not only improves production efficiency but also strengthens pricing strategies, contributing to long-term profitability. It highlights the role of cost transparency in driving sustainable growth, particularly for small and medium-sized furniture enterprises.The furniture industry often struggles with setting accurate selling prices due to the lack of structured and precise cost calculation systems. Many furniture entrepreneurs still rely on traditional methods that base prices on market trends, without accounting for underlying production costs. This often leads to prices that are too low, eroding profit margins, or too high, making it difficult to stay competitive. This study introduces a novel Cost of Goods Manufactured (COGM) calculation system, integrated with the Bill of Materials (BOM) method, to advance current pricing systems in the furniture industry. By incorporating key cost elements such as raw materials, labor, and the impact of waste and rework, the system enhances the accuracy of COGM calculations. Additionally, it offers greater transparency by providing a detailed breakdown of each cost component, allowing entrepreneurs to better understand their production expenses. The implementation of this system led to a 15% improvement in pricing accuracy, significantly reducing pricing errors and optimizing production costs. Furthermore, businesses reported a 20% increase in competitiveness due to more informed pricing strategies. This research demonstrates that integrating COGM with BOM not only improves production efficiency but also strengthens pricing strategies, contributing to long-term profitability. It highlights the role of cost transparency in driving sustainable growth, particularly for small and medium-sized furniture enterprises
Digitization of Warehouse Stock Management Through Web-Based Information Systems
Full text linkDigitalization in warehouse stock management has become increasingly important, particularly for small and medium enterprises that still rely on manual recording methods. These traditional systems often lead to delays, data inaccuracies, and operational inefficiencies. This study aims to design and implement a web-based warehouse stock management information system to improve the recording process, increase accuracy, and support decision-making at Digital Connection, a company still using Microsoft Excel for inventory tracking. The system was developed using the waterfall method, which includes five structured stages: needs analysis, system design, implementation, testing, and maintenance. Functional testing was conducted through black box testing to validate the performance of all system features from a user perspective. The results demonstrate that the developed system enables real-time recording of incoming and outgoing goods, provides interactive data visualization through a dashboard, and issues automatic alerts for minimum stock thresholds. Compared to the previous manual system, the digital solution significantly enhances data accuracy, reduces the risk of duplication or loss, and speeds up reporting processes. This transition not only streamlines warehouse operations but also improves user responsiveness in stock management activities. In conclusion, the proposed information system offers an effective and adaptive approach for small businesses to transition from manual to digital warehouse management, contributing to operational efficiency and supporting broader digital transformation initiatives in logistics and supply chain environments