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INDONESIA
Technomedia Journal
Published by Pandawan Sejahtera Indonesia
ISSN : 26203383     EISSN : 25286544     DOI : 10.33050/tmj
Core Subject : Science, Education,
Computer Science & IT Languange, Linguistic, Communication & Media
Technomedia Journal (TMJ) adalah jurnal yang didedikasikan untuk pertukaran hasil penelitian berkualitas tinggi di semua aspek Informatika, Teknologi Informasi, dan Ilmu Data. TMJ ini merupakan bagian dari Pandawan Sejahtera Indonesia, serta didukung oleh Alphabet Incubator yang merupakan diseminasi hasil penelitian para ilmuwan dan insinyur di berbagai bidang ilmu pengetahuan dan teknologi. TMJ mengikuti kebijakan akses terbuka yang memungkinkan artikel yang diterbitkan tersedia secara online tanpa berlangganan.
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Sistem Informasi Menejemen
Articles 249 Documents
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Digitalization of Legal Information Management in Primary Schools Based on the JDIH Application: Digitalisasi Manajemen Informasi Hukum Sekolah Dasar Berbasis Aplikasi JDIH Saada, Rahmadian A.; Lapatta, Nouval Trezandy
Technomedia Journal Vol 10 No 1 (2025): June
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v10i1.2269

Abstract

The rapid development of science and technology in the education sector has prompted institutions like the elementary school to improve the efficiency and effectiveness of information and legal management. This study aims to develop a Legal Documentation and Information Network (JDIH) application to facilitate the publication of school regulations. The primary objective of this research is to create an application that simplifies the management of student and school information, ensuring compliance with educational laws, and fostering an adaptive educational environment. The research used the System Development Life Cycle (SDLC) methodology, utilizing the Waterfall Model approach, which includes planning, analysis, design, implementation, testing, and maintenance. Data was gathered through observation, interviews, and literature studies, ensuring comprehensive insights into the existing regulatory management practices at the school. The JDIH application was successfully developed and implemented at the elementary school. It improved the accessibility of school regulations, ensuring better legal compliance and enhancing transparency. Positive feedback was received from respondents, with an average satisfaction level of 83.3%. This study demonstrates the effectiveness of the JDIH application in streamlining regulatory management. It is expected that the application will be expanded to other schools, further improving the management of legal information and promoting a more transparent and efficient educational environment.
Implementation of Brute Force Algorithm for Digital Land Mapping Information System: Implementasi Algoritma Brute Force untuk Sistem Informasi Pemetaan Tanah Digital Irfan, Mohamad; Ngemba, Hajra Rasmita; Hendra, Syaiful; Syahrullah, Syahrullah; Lapatta, Nouval Trezand; Hamid, Odai Amer
Technomedia Journal Vol 10 No 1 (2025): June
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v10i1.2271

Abstract

The Land Asset Mapping Information System of the Palu City Local Government was developed to streamline digital land record management and enhance public service delivery. However, users experience substantial delays averaging 3-5 minutes per query during manual data searches. This study aims to optimize search efficiency by implementing the Brute force string-matching algorithm, allowing users to retrieve precise land records through direct pattern input. A waterfall system development methodology was systematically applied across five phases: requirements analysis, system design, PHP/JavaScript implementation, White Box testing, and maintenance. The research team collaborated closely with 12 technical officers from the City Spatial Planning and Land Office to validate system requirements and evaluate real-world performance. The implementation of the Brute force algorithm reduced average search times by 68\% (from 185s to 59s) while maintaining 100\% accuracy in test datasets containing 5,000+ land records. Rigorous testing confirmed the algorithm's reliability across various edge cases, including partial matches and special character inputs. The application of the Brute force method has transformed the system's search functionality, particularly for frequent queries involving land parcel IDs and owner names. These improvements have increased daily processing capacity by 40\%, significantly benefiting urban planning and dispute resolution workflows. While demonstrating excellent performance for medium-sized datasets, the solution presents opportunities for future enhancement through hybrid approaches combining Brute force with indexing techniques for large-scale deployments beyond 50,000 records.
AI-Driven Makeup Suggestions Leveraging Mediapipe Face Landmarks For Eye Shape Detection: Rekomendasi Tampilan Riasan Mata Berbasis AI Menggunakan Landmark Wajah Mediapipe Untuk Mendeteksi Bentuk Mata Devanda, Faustin; Santoso, Handri
Technomedia Journal Vol 10 No 1 (2025): June
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v10i1.2316

Abstract

In the world of beauty, makeup is not only a form of self expression but also a creative skill that requires precision and an understanding of facial structures. Among all facial features, the eyes play a crucial role in defining makeup styles. Each individual has unique eye shapes such as round, monolid, upturned, almond, and downturned, which require different makeup techniques to enhance their appearance. However, many individuals struggle to identify their eye shape, leading to suboptimal makeup results. This research aims to develop an intelligent system for eye shape classification using image processing and artificial intelligence technologies. MediaPipe, a robust and lightweight framework for facial landmark detection, was employed to extract key features from the eye region, including Eye Aspect Ratio (EAR), Eye Corner (angle), and Eye Distance. A total of 1,250 images were used from various datasets including personal archives, Kaggle, and GitHub MUCT. The classification process used a Support Vector Machine (SVM) with a non-linear RBF kernel, and its performance was validated using K-Fold Cross Validation with 10 folds. The system demonstrated high accuracy for almond, downturned, monolid, and round eyes. However, classification for upturned eyes showed less optimal results, likely due to limitations in the current feature set. This study also introduces an integrated open camera interface that detects eye shape in real time and recommends suitable eye makeup styles. This research contributes to inclusive beauty technology by providing personalized makeup suggestions based on eye shape, aligning with SDG 5 (Gender Equality) and SDG 9 (Industry, Innovation, and Infrastructure). Future work will focus on improving accuracy, particularly for upturned eye classification.
Web-Based Personal Finance Management Application with Interactive Data Visualization: Aplikasi Manajemen Keuangan Pribadi Berbasis Web dengan Visualisasi Data Interaktif Rahmatullah, Muhammad Wildan Jaffar; Oktavia, Nanda Nur; Lawrence, Lucas
Technomedia Journal Vol 10 No 1 (2025): June
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v10i1.2382

Abstract

Personal financial management plays a crucial role in achieving financial stability and ensuring effective control over individual finances. With the advancement of technology, more individuals are turning to digital solutions to manage their financial data more efficiently. This research focuses on the development of a web-based personal financial management application equipped with interactive data visualization tools, allowing users to easily track and analyze their income, expenses, and financial trends. Using the waterfall approach, this research includes the stages of design, development, testing, and implementation. The application is developed with Vue.js for the user interface and Highcharts for data visualization. Testing results show that the application effectively helps users understand their financial patterns and provides useful insights for financial decision-making. The testing results also indicate that the application makes it easier for users to plan their budget, identify unhealthy spending habits, and offer recommendations for savings. This application offers a more efficient solution compared to manual methods or traditional applications that only provide raw data without visual analysis. The conclusion of this research is that the developed application provides a practical and intuitive solution for personal financial management. The application helps users plan their finances wisely and make smarter decisions, thus improving financial literacy and supporting the achievement of their long-term financial goals. As a future development step, it is recommended to integrate machine learning and blockchain technology to enhance data security and transaction transparency.
Integration of Business Intelligence and Predictive Analytics for Student Success Based on Blockchain: Integrasi Business Intelligence dan Analitik Prediktif untuk Keberhasilan Mahasiswa Berbasis Blockchain Rahardja, Untung; Rakhmansyah, Mohamad; Wijaya, Surta; Anjani, Sheila Aulia; Davies, Mary
Technomedia Journal Vol 10 No 1 (2025): June
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v10i1.2389

Abstract

In the digital era, education is undergoing a significant transformation, with predictive analytics becoming an important approach to increasing student success. Rapid advancements in technology have enabled institutions to collect and analyze diverse datasets, yet challenges remain in ensuring data accuracy, transparency, and reliability. This research explores the integration of blockchain technology to address data integrity challenges, with a focus on its application in predictive analytics. The objective is to enhance the reliability of student-related data while improving the effectiveness of academic performance predictions. Specifically, this research examines the relationship between Academic Performance Metrics (APM), Student Engagement Data (SED), Socioeconomic Factors (SEF), Blockchain-Enabled Data Integrity (BDI), and Predictive Algorithm Efficiency (PAE). Using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method, data were collected through structured surveys and institutional records involving higher education students. The constructs were validated through measurement model testing before proceeding to structural path analysis. The results show the significant influence of socio-economic factors and blockchain-based data integrity on academic outcomes, while student engagement and predictive algorithm efficiency also demonstrate moderate effects. The study also identifies areas that require improvement in predictive models, particularly regarding the alignment of input variables with algorithm design. These findings emphasize the importance of leveraging technology to develop more equitable and effective educational strategies, while underscoring the need for continued improvements in construct design to increase the reliability and validity of models. This research contributes to the growing field of educational data science by offering a blockchain-enhanced framework for predictive analytics in education.
Designing a Subsurface Oil and Gas GUI Dashboard Using Design Thinking: Perancangan GUI Dashboard Subsurface Migas dengan Pendekatan Design Thinking Jannatan, Muhammad Ardhyan; Puspita, Niniek Fajar; Rahardjo, Jani; Harun, Muhammad Rizky
Technomedia Journal Vol 10 No 1 (2025): June
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v10i1.2432

Abstract

Oil and gas companies are currently facing increasingly significant production declines, requiring detailed, accurate and fast subsurface analysis. However, the complexity of large and scattered data, as well as the use of various non-integrated software, are obstacles that cause difficulties and long and inefficient analysis times. Therefore, this study aims to design an intuitive graphical user interface (GUI) dashboard to speed up and facilitate the process as part of the technology management of one of the oil and gas companies in Indonesia. The design thinking and new product development approaches are used to design the system. Qualitative methods are carried out through in-depth interviews, field observations, and surveys to identify user needs and build a subsurface dashboard GUI system, while quantitative methods are used to analyze multi-matrices from the House of Quality (HoQ) and evaluate the intuitiveness and usability of the prototype with the System Usability Scale (SUS) instrument. The analysis was carried out using user personas, customer journey maps, and HoQ to determine the main features. The results of the study indicate that visual graphics, seismic maps and cross-sections, customization, and data management are priority features in the subsurface dashboard GUI system prototype. The SUS evaluation shows that the system is intuitive, user-friendly, and can support work efficiency, as well as suit user needs.
Digital Transformation in Library Recommendation System Using k-NN Collaborative Filtering: Transformasi Digital dalam Sistem Rekomendasi Buku Perpustakaan Menggunakan k-NN Fachri, Ahnaf Febriyan; Faisal, Muhammad; Crysdian, Cahyo
Technomedia Journal Vol 10 No 1 (2025): June
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v10i1.2438

Abstract

Libraries, as essential information centers, play a crucial role in providing diverse resources to meet the information needs of visitors. In the digital age, libraries face challenges in efficiently managing their vast collections while offering personalized services that cater to the varying needs of users. The primary goal of this research is to improve the management of library resources by developing a personalized book recommendation system. This system aims to provide relevant book suggestions based on individual preferences, specifically tailored to the academic needs and interests of university students. To achieve this, the research applies a combination of User-Based Collaborative Filtering (UBCF) and k-Nearest Neighbors (k-NN) algorithms, which are powerful techniques in the field of data mining. These methods are used to analyze the academic performance (measured by the students' Indeks Prestasi Semester (IPS) scores) and book preferences to create a personalized recommendation system. The study demonstrates that the integration of UBCF and k-NN significantly enhances the accuracy and relevance of book recommendations, providing students with more tailored suggestions based on their academic achievements and preferences. The results indicate that such a recommendation system not only improves the user experience but also contributes to the enhancement of students' academic performance by offering them books that align with their learning needs, ultimately supporting the academic goals of higher education institutions.
Analysis of Risk Factors of HPS in Goods and Services Procurement for Jakarta Property Projects: Mitigasi Risiko HPS Berbasis Digital pada Pengadaan Proyek Properti Gandhi, Iswara; Pontan, Darmawan; Inavonna, Inavonna; Kusumawati, Lili
Technomedia Journal Vol 10 No 1 (2025): June
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v10i1.2459

Abstract

The procurement of goods and services for property projects in Jakarta faces various challenges, primarily due to inaccuracies in the Self-Estimated Price (HPS), which lead to significant risks in cost, time, and quality. This study seeks to identify the dominant risk factors caused by HPS inaccuracies and propose effective strategies to mitigate their impact on property project procurement. The research uses the Analytical Hierarchy Process (AHP) method, with 54 respondents involved, to evaluate three key risk categories: cost, time, and quality, based on the effects of HPS inaccuracies. The study finds that these inaccuracies undermine budget efficiency, cause delays in procurement processes, and negatively impact the quality of goods or services received. Cost-related risks include document instability and unforeseen expenses, while time-related risks involve delays and frequent revisions of the HPS. Quality-related risks stem from the use of substandard materials and the failure to meet project specifications. To mitigate these risks, the study proposes updating the HPS with up-to-date market data, conducting regular price surveys, enhancing the skills of procurement teams, adopting digital technologies such as e-procurement systems, and improving supplier selection processes. These strategies aim to improve procurement efficiency, enhance project quality, and ensure cost-effectiveness, ultimately leading to better project outcomes.
Sustainable Practices in Learning Factories: Technology for SDG4: Penerapan Teknologi Berkelanjutan dalam Learning Factories untuk Mendukung SDG 4 Sunarya, Po Abas; Friandi, Sendy Zul; Santoso, Nuke Puji Lestari; Xolani, Zanele; Abbas, Maulana
Technomedia Journal Vol 10 No 1 (2025): June
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v10i1.2466

Abstract

Learning factories serve as innovative platforms to promote sustainable education by integrating advanced technologies, contributing directly to achieving Sustainable Development Goal 4 (SDG4), which focuses on ensuring inclusive and equitable quality education and lifelong learning opportunities for all. This study investigates the application of sustainable practices in learning factories, aiming to identify technological innovations that enhance education while promoting resource efficiency and accessibility. The objective of this research is to explore how these technologies can address educational challenges and contribute to sustainable development. Employing a mixed-methods approach, this research combines in-depth qualitative case studies of learning factories with quantitative data from surveys and interviews conducted with educators, students, and industry stakeholders. The findingsreveal that implementing technologies such as automation, virtual and augmented reality, and digital twins improves learning outcomes by providing immersive, hands-on experiences while minimizing environmental impacts. Additionally, the results highlight the importance of fostering partnerships between academic institutions and industries to create a collaborative ecosystem for sustainable innovation. The conclusion emphasizes the transformative role of learning factories in advancing sustainable education through technology, suggesting that broader adoption of these practices can accelerate progress toward SDG4. This study offers practical recommendations for educators, policymakers, and industry leaders to integrate technology-driven sustainability in educational environments, thus supporting global efforts toward equitable and quality education.
Cost Decision Making Using Activity-Based Costing Approach in Digital Information Systems Harahap, Imam Zarkasih; Zarkasih Harahap, Imam; Irawan, Muhammad Dedi; Valerry, Adele
Technomedia Journal Vol 10 No 2 (2025): October
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/63qq9515

Abstract

This study aims to develop and apply the Activity-Based Costing (ABC) method in determining overhead costs in the rice processing industry at MGS Tanjung Selamat Rice Mill. Conventional methods often cause distortions in the allocation of overhead costs, which have an impact on the inaccuracy in the calculation of the cost of goods manufactured (COGS). To overcome this problem, this research uses a Research and Development (R&D) approach with a system development model based on the Waterfall method. Data were collected through observations, interviews, and documentation studies, which were then analyzed to identify the main production activities and the most influential cost drivers. The results showed that the ABC method was able to improve the accuracy of overhead cost calculation, optimize cost allocation to each production activity, and support more strategic business decision-making. In addition, this research produced a software-based system to facilitate the implementation of the ABC method in the company. With the implementation of ABC, MGS Tanjung Selamat Rice Mill can set a more competitive selling price and identify less efficient activities to be improved.

Page 24 of 25 | Total Record : 249

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