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  • Congratulations & Success! Here are the Winners and Finalists of UNIKOM PILMAPRES 2026

    Congratulations & Success! Here are the Winners and Finalists of UNIKOM PILMAPRES 2026

    The Academic Community of Universitas Komputer Indonesia (UNIKOM) congratulates and highly appreciates the winners of the 2026 University-Level Outstanding Student Selection (PILMAPRES) for Bachelor and Diploma Programs.

    Our appreciation and pride go to:

    🏆 Febby Cipta – International Relations (1st Place PILMAPRES Bachelor Program)

    🏆 Mursyida Sakina – Marketing Management (1st Place PILMAPRES Diploma Program)

    🥈 Muhammad Faisal Hafiz – Visual Communication Design (2nd Place PILMAPRES Bachelor Program)

    🥈 Dinda Karina – Graphic Design (2nd Place PILMAPRES Diploma Program)

    🥉 Ghaitsa Amalia – Communication Science (3rd Place PILMAPRES Bachelor Program)

    🏅 Alisya Yansa – Law (4th Place PILMAPRES Bachelor Program)

    🏅 Vanessa Rainaya Disam – Law (5th Place PILMAPRES Bachelor Program)

    Congratulations also to the 2026 PILMAPRES Finalists:

    1. Reynaldhy Putra Herdiansyah – Management
    2. Dulce Clarissa Juliety Latuputty – Urban and Regional Planning
    3. Echfiz Dzakwan Arrazie – English Literature

    This achievement is concrete proof of the dedication, hard work, and academic as well as non-academic excellence of UNIKOM students. The 1st Place Winners of the Bachelor & Diploma Programs will be the official representatives of UNIKOM to compete at the LLDIKTI Region IV level and proceed to the 2026 National level.

    We ask for the prayers and support of the entire academic community so that our delegates can give their best results for the alma mater in the national arena.

    Keep creating and innovating for the Nation!

  • The 9th International Conference on Informatics, Engineering, Science & Technology (INCITEST 2026) is back!

    The 9th International Conference on Informatics, Engineering, Science & Technology (INCITEST 2026) is back!

    Universitas Komputer Indonesia is pleased to host this prestigious conference with the theme: “Shaping the Sustainable Future: Emerging Technologies for Smart and Resilient Societies.”

    Featuring distinguished experts from around the world:
    🌟 Prof. Hideomi Gokon (JAIST, Japan)
    🌟 Assoc. Prof. Dr. Irawan Afrianto, S.T., M.T. (Universitas Komputer Indonesia, Indonesia)
    🌟 Dalbir Singh (Leader, Country Digital Acceleration CISCO ASEAN & Korea)

    📆 November 5, 2026
    📍 Auditorium, 17th Floor, Smart Building, UNIKOM

    Submit your best research and engage in a global discussion on emerging issues, innovations, and solutions in Informatics, Engineering, Science, and Technology.

    Discover exciting opportunities for publication, networking, and international collaboration.

    📌 Important Dates:
    ✍️ Call for Paper: 2 May 2026
    📖 Full Paper Submission Deadline: July 4, 2026
    ✅ Notification of Acceptance: September 9, 2026
    📸 Camera Ready: October 10, 2026
    🏫 Conference Date: November 5, 2026

    ⛓️‍💥 Information & Registration:
    📞 Agis Abhi Rafdhi (+62 813-2324-2018)
    📧 timkonferensi@email.unikom.ac.id
    🌐 https://incitest.unikom.ac.id/

  • The Role of Environmental Policy in Promoting Green Transportation Technologies

    Authors: Siphimvadee Suthakavatin, Khodor Shatila, Karine Aydinyan, Raeni Dewi Santy

    DOI: 10.1051/bioconf/202414506013

    Abstract

    This study explores the role of environmental policy in promoting the adoption of green transportation technologies, focusing on the effects of financial incentives, regulatory frameworks, and public investment in infrastructure across key Asian urban centres. The research highlights how technological innovation acts as a crucial mediator between policy measures and the adoption of sustainable transportation options such as electric vehicles (EVs) and hydrogen-powered vehicles. Using Structural Equation Modelling (SEM), the study examines the relationships between these factors, demonstrating that higher levels of financial incentives, supportive regulations, and strategic public investment lead to significant advancements in technological innovation, which in turn drives the adoption of green transportation technologies. The findings contribute to the broader understanding of sustainable urban mobility solutions and offer important insights for policymakers and industry stakeholders in regions experiencing rapid urbanization. The study also discusses the dual role of these policy drivers, both in directly influencing adoption and in fostering technological advancement. © The Authors, published by EDP Sciences.

    This article can be accessed at https://www.scopus.com/pages/publications/85216661038

  • Analysis of Solar Powered Public Street Lighting Design (PJUTS)

    Analysis of Solar Powered Public Street Lighting Design (PJUTS)

    Authors: Sutono S, Chepi Nur Albar

    Abstract

    This research aimed to propose and demonstrate a Solar-Powered Public Street Lighting lamps concept as part of a Community Service (PKM) initiative conducted at the Halim Cluster Housing Complex in West Bandung Regency. The study employed an experimental method combined with product design. The findings revealed that the solar-powered Public Street Lighting (PJU) design offers an innovative and environmentally friendly solution to meet public lighting needs. The calculation and testing involved 5V/12W LED lights, 12V/50Wp solar panels, a 10A charge controller, and 12V/30Ah lithium batteries. The solar-powered street lighting system can operate for 12 hours, even under sunny and cloudy conditions. © 2025 Taylor’s University. All rights reserved.

    Keywords: Battery; Charge control; Complex; Housing; LED

    This article can be accessed at https://www.scopus.com/pages/publications/85214486386

  • Preferences of Landscape Elements in Teras Cikapundung Park in the COVID-19 Pandemic

    Preferences of Landscape Elements in Teras Cikapundung Park in the COVID-19 Pandemic

    Authors: Tri Widianti Natalia, Iren Haifa Khoerunissa, Dhini Dewiyanti Tantarto, Nova Chandra Aditya

    DOI: 10.1063/5.0254818

    Abstract

    Currently, many people use public open spaces for various activities, such as sports, meetings, and recreation. The existence of public open spaces is one of the main needs, especially in urban areas. Public open spaces are also created to provide comfort to the surrounding community in their activities and interactions in them. Especially during the COVID-19 pandemic, where people are bored with the limitations of their activities and they prefer parks that are considered safer for recreation areas. One of the public open spaces in Bandung which is visited by quite a lot of people is Teras Cikapundung Park which is located on Jl. Siliwangi, Cidadap District, Bandung City. This study aims to find out favorite places/preferences in the landscape area in Teras Cikapundung Park based on visitor activities. The research method used descriptive quantitative methods, such as observations, surveys, and distributing research questionnaires to visitors at Teras Cikapundung Park. The results showed that the amphitheater area is one of the favorite landscape areas that is most often visited in groups because it is the largest area in Teras Cikapundung Park which can accommodate enough visitors to carry out various activities that are safer to do by implementing fairly good health protocols. The activities carried out at the amphitheater include morning exercises, community gatherings, discussions and talks, and taking selfies. The results of this study can be used as a planning strategy for designing landscape elements in urban open spaces to improve people’s quality of life. © 2025 Author(s).

    This article can be accessed at https://www.scopus.com/pages/publications/85219186135

  • Exploring Strategies to Manage Expectational Knowledge in Higher Education After Covid-19 Pandemic

    Exploring Strategies to Manage Expectational Knowledge in Higher Education After Covid-19 Pandemic

    Author: Denok Sunarsi, Horas Djulius, Azhar Affandi, Sidik Priadana, Umi Narimawati, Iman Sudirman

    DOI: 10.11591/edulearn.v19i2.21784

    Abstract

    The COVID-19 pandemic has brought unprecedented challenges and opportunities for knowledge management systems (KMS) in various domains and sectors. This research explores the strategies to manage expectational knowledge in higher education after the COVID-19 pandemic. This study employed a qualitative research method with a case study design to capture the students’ perspectives on strategies to manage expectational knowledge in higher education after the COVID-19 pandemic. The participants are students at the doctoral program, Universitas Pasundan, Bandung, West Java, Indonesia. The interview was conducted in December 2022 using a semi-structured interview technique and then was analyzed using thematic analysis. This research found four strategies doctoral management students use to manage expectation knowledge after the COVID-19 pandemic. The strategies are codification, personalization, knowledge partnering, and knowledge harvesting. The research implications of this study provide a foundation for future research endeavors to advance the understanding and application of knowledge management strategies in the post-pandemic higher education landscape. © 2025, Intelektual Pustaka Media Utama. All rights reserved.

    Keywords: Expectational knowledge; Knowledge management system; Management strategies; Pandemic COVID-19; Tacit knowledge

    This article can be accessed at https://www.scopus.com/pages/publications/85216364801

  • Predicting Covid-19 Cases Using Hybrid Arimax-Bidirectional LSTM Model

    Predicting Covid-19 Cases Using Hybrid Arimax-Bidirectional LSTM Model

    Authors: Nugroho Widyanto, Jin-Whan Kim, Umi Narimawati

    Abstract:

    Currently, there has been improvement in the handling of the pandemic with the availability of vaccines, which has had an impact on improving the economy and starting to return to normal community activities. However, further studies are still needed. So that this pandemic condition can be anticipated in the future, there must be a model that can predict future COVID-19 cases, so that each country can anticipate it by implementing more appropriate policies and handling. In this research, we will propose 2 methods that are popularly used in the case of time-series forecasting involving other factors in the regression model, namely ARIMAX, which is very superior in predicting linear (stationary) models, and bidirectional LSTM, which is a better development than LSTM, which can predict non-linear (non-stationary) models. The hybrid approach used for these two models is expected to provide much better prediction results with a smaller error range, as well as reducing existing variations, compared to using both methods separately. The process of creating a hybrid ARIMAX-Bidirectional LSTM model involves six sub-processes: data transformation using ARIMAX, data normalization (min-max scaling), feature selection using a genetic algorithm, hyper-parameter tuning for ARIMA models and bidirectional LSTM models, prediction models with bidirectional LSTM, and lastly the creation of a hybrid model. The hybrid model was proven to provide much better prediction results than the models run individually. The ARIMAX-Bidirectional LSTM hybrid model has also been proven to be better than the ARIMAX-LSTM hybrid model, as well as other deep learning-based hybrid models. Even though the ARIMAX-Bidirectional LSTM hybrid model can provide very good predictions, its implementation has not been widely carried out, so it is an excellent opportunity to carry out research on its use and utilization. © School of Engineering, Taylor’s University.

    Keywords: ARIMAX; Bidirectional LSTM; COVID-19; Deep learning; Forecasting; LSTM; Model hybrid; Time-series

    This article can be accessed at https://www.scopus.com/pages/publications/85199480143

  • Analysis of the Need for Information Systems for Early Childhood Education Services in Play Group during the Covid19 Pandemic

    Analysis of the Need for Information Systems for Early Childhood Education Services in Play Group during the Covid19 Pandemic

    Authors: Mia Fitriawati, Sri Supatmi, Rani Puspita Dhaniawaty

    DOI: 10.37934/araset.34.2.264270

    Abstract:

    Early childhood education services in play groups during the COVID-19 pandemic have changed. This change includes various services such as administration, acceptance of new students to the face-to-face teaching and learning process and remote meetings. This is certainly not easy if the group knows how the need for an information system is. The need for this information system aims to provide convenience from various fields of education, especially early childhood education in play groups. In this study, we will discuss the analysis of information system requirements using the value chain analysis method. The analysis uses the value chain in five main activities and four supporting activities. These activities will discuss the needs of early childhood education information systems in play groups which consist of management and implementation of activities, financing, educators and education, blinding of information systems in particular, the use of technology to be used, and how the use of this information system will be used in understand the internal and external parties that will be related to the management of facilities and infrastructure. The results of this value chain analysis will be used as a guide in determining the information system needs by adjusting the early childhood education services in the play group by adjusting the level of management owned by each play group. © 2024, Semarak Ilmu Publishing. All rights reserved.

    Keywords: Covid-19 Pandemic, Early Childhood Education Services, Information Systems, Play Group

    This article can be accessed at https://www.scopus.com/pages/publications/85179302380

  • An Augmented Reality-Based Lipstick Color Recommendation System Model to Help Prevent COVID-19 Spreadness

    An Augmented Reality-Based Lipstick Color Recommendation System Model to Help Prevent COVID-19 Spreadness

    Authors: Agustia R.D, Bryllyanti A

    DOI: 10.1063/5.0128549

    Abstract

    The aim of this research is to provide lipstick color recommendations based on the analogous color theory. The recommended lipstick color is based on the user’s skin tone color, where the skin color that is taken is the skin of lip color. Facial landmark detection will be used as a method to detect the position of the user’s lips where the recommended lipstick color results can be seen in the form of augmented reality. To find out what lipstick products are used as the basis for lipstick color recommendations, questionnaires were distributed using random sampling to 100 female respondents, and data was sorted to obtain the three products that were most widely used by female respondents in Indonesia. Based on the results of the questionnaire the products most widely used by respondents are Wardah, Makeover, and Emina products. The results of the research is lipstick color recommendation system model based on the user’s skin tone color using augmented reality facial landmark detection method. Based on performance testing, detection can be carried out well with the criteria that the face is facing the camera with a tilt position of 0 °-45 °, the optimal distance between the camera and the face is 20-80 cm, and with optimal lighting using 40W incandescent lamp or 8 W-23W fluorescent lamp. During the COVID-19 pandemic, using lipstick product samples at the same time will increase the risk of contracting COVID-19 so the lipstick color recommendation system will be an alternative to help prevent COVID-19 spreads. © 2023 Author(s).

    Keywords: Augmented reality; lipstick color recommendation system


    This article can be accessed at https://www.scopus.com/pages/publications/85177603924

  • Air Quality Monitoring System for Cyclist

    Air Quality Monitoring System for Cyclist

    Authors: Aria M. ; Wangsanegara T. ; Kurniawan F. ; Maulana T.

    DOI: 10.1063/5.0129192

    Abstract: 

    In recent years, emissions of toxic gasses caused by burning fossil fuels, industrial production, and vegetation loss have made air pollution even worse. The concentration of harmful gasses and particulates increased in the atmosphere. Air quality influences human health, especially the particulate matter that affects the respiratory system of people. To find out the level of air pollution for bicycle users, we need an instrument to detect pollution levels in the air that functions as a monitor of pollution levels and early detection in air pollution, so it becomes a reference for bicycle users in knowing their area of cycling whether or not it has good air quality. The system development method in this study used the prototype method because this method can be easily evaluated and implemented in stages. The device’s hardware consists of three sensors: gas sensors MQ-7, MQ-135, and a DHT-11 Humidity sensor. The device has three sensors attached with an Arduino. The air quality measurement device generates real-time air pollutants monitor from the sensor and shows the information using the Liquid Crystal Display (LCD). In conclusion, it is affordable, user-friendly, low-cost, and minimum-power requirement hardware and comprehensible data collection. It is helpful for the bicycle user to be concerned about the health of air condition near the cyclist area. © 2023 Author(s).

    Author Keywords:

    air quality; cyclist; Monitoring system

    This article can be accessed at https://www.scopus.com/pages/publications/85177557112?