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All Journal Jurnal Bina Manajemen Intelektual : Jurnal Penelitian Dosen Akuntansi Blockchain Frontier Technology (BFRONT)
Tessa Handra Tessa Handra
Unknown Affiliation
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering Library & Information Science Social Sciences Other

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PERBANDINGAN ESTIMASI MAINTENANCE COSTING KENDARAAN OPERASIONAL PADA PT TUNASJAYA PACKINDO Tessa Handra; Vincent Vincent
Jurnal Bina Manajemen Vol 6 No 2 (2018): Jurnal Bina Manajemen Vol.6 No.2 Maret 2018
Publisher : STIE Wiyatamandala

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1575.667 KB)

Abstract

Correct cost estimation for company’s tangible and intangible asset is one of the important factors in accounting for budgeting in future periods or as a source of information in decision making for the next of the object treat. PT Tunasjaya Packindo and the entire company can not be separated from the problem of this cost estimation. Based on data collected through interviews, observation, and this documentary determining the estimated cost can be processed by two methods. With the traditional costing method of processing and the activity-based costing resulted in the difference in numbers reaching until IDR143.103,-. This shows there is one method of cost estimation is potentially overcosting or undercosting. Keywords: Activity Based Costing, Traditional Costing, Maintenance, Budgeting
Application of IoT and AI Based on ESP32CAM to Support Sustainable Mobility in Smart Cities Mohammad Annas; Ramahdan, Fikri Arsla; Tessa Handra; Achmad Hidayat Dwi Saputra; Henrik Jensen
Blockchain Frontier Technology Vol. 4 No. 2 (2025): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/bfront.v4i2.707

Abstract

Sustainable mobility is a crucial component of smart city development, aiming to create an efficient, ecofriendly, and high quality urban environment. The rapid urbanization and increasing vehicle numbers have led to traffic congestion, high carbon emissions, and inefficient public transportation systems. To address these challenges, integrating Internet of Things (IoT) and Artificial Intelligence (AI) technologies, particularly through the ESP32CAM platform, offers innovative solutions for realtime monitoring, analysis, and management of transportation systems. This study aims to develop an intelligent mobility system that leverages ESP32CAM as the primary device for capturing visual data, including traffic density, vehicle tracking, and parking area occupancy. The collected data is processed using AI algorithms to generate insights, such as traffic pattern predictions and alternative route recommendations. The gap in existing smart mobility solutions lies in their high implementation costs and limited adaptability to developing regions. this study introduces an affordable and flexible system that optimizes transportation efficiency by up to 30%, reducing travel time and carbon emissions while enhancing public transportation management. The results indicate that implementing this system significantly contributes to sustainable urban development by improving mobility, reducing environmental impact, and accelerating the transformation towards smart cities, especially in developing countries where cost-effective solutions are essential.
Adaptive Workflow Management with Decentralized AI in Blockchain Based Distributed Ledger Systems Tessa Handra; Ninda Lutfiani; Ariesya Aprillia; Fitra Putri Oganda; Fhia Amelia; Noah Rangi
Blockchain Frontier Technology Vol. 5 No. 1 (2025): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/bfront.v5i1.804

Abstract

Blockchain technology has rapidly evolved as a decentralized solution offering high security and transparency; however, several challenges still hinder the effective management of workflows within blockchain based environments. This study aims to develop an adaptive workflow management model that utilizes decentralized artificial intelligence (AI) and distributed ledger technology (DLT) to enhance the performance, security, and flexibility of processes in blockchainn networks. A mixed method approach combining simulation and experimentation on a dedicated blockchain platform was employed. The adaptive workflow model consists of a realtime process monitoring module, a decentralized AI module for adaptive decision making, and a DLT component that ensures data consistency and security. Statistical methods and system performance evaluations were used to analyze the experimental data. Results show that the proposed model can reduce workflow response times by up to 25% and increase the successful execution rate of smart contracts to 98%. Moreover, the integration of decentralized AI optimizes workload distribution across nodes, enabling network scalability improvements of up to 150% without significant performance degradation. The findings demonstrate that the adaptive workflow model combining AI and DLT enhances the flexibility and governance of blockchain networks through AI’s predictive capabilities and DLT’s security. Nevertheless, challenges such as high computational resource demands and technical complexities must be addressed. This research opens opportunities for further development to expand the scope of complex and dynamic blockchain applications and supports their integration with technologies like the Internet of Things (IoT).
The Use of Beauty Products in Purchasing Decisions Reviewed from the Perspective of Product Quality and Brand Image Tessa Handra; Subandriyo; Lod Sulivyo; Faye Maya Dewi
JOURNAL INTELEKTUAL Vol 4 No 1 (2025): JOURNAL INTELEKTUAL
Publisher : LPPM STIE PPI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61635/jin.v4i1.209

Abstract

Introduction/Objective: This study discusses the analysis of the Influence of Product Quality (X1) and Brand Image (X2) on Purchase Decisions (Y) of Beauty Products on Female Students in Private Institutions in Tangerang Regency.. Background of the Problem: The growth of the beauty industry in Indonesia has experienced rapid growth, beauty products have become primary needs and not just secondary needs and consider beauty products as self-expression and a means to increase self-confidence. Novelty: Analyzing the same variables according to previous research by testing different research locations and samples. Research Method: Using a quantitative descriptive approach, data was taken from users of local cosmetic brands obtained 71 samples with Slovin's theory and the tool for analysis used was SPSS. Findings/Results: It is proven that there is an influence that can positively consider purchasing decisions, namely product quality (X1) and brand image (X2) on local cosmetic users among female students. Conclusion: This finding provides important implications in paying attention to product quality and brand image in purchasing decisions in terms of cosmetic products because beauty products are their self-expression
Co-Authors Achmad Hidayat Dwi Saputra Ariesya Aprillia Faye Maya Dewi Fhia Amelia Fitra Putri Oganda Henrik Jensen Lod Sulivyo Mohammad Annas Ninda Lutfiani Noah Rangi Ramahdan, fikri Arsla Subandriyo Vincent Vincent