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DBESTI: Journal of Digital Business and Technology Innovation
Published by STT Terpadu Nurul Fikri
ISSN : 30471028     EISSN : 3032775X     DOI : https://doi.org/10.54914/dbesti.v1i1
Core Subject : Economy, Science,
Computer Science & IT Economics, Econometrics & Finance Library & Information Science
DBESTI: Journal of Digital Business and Technology Innovation merupakan jurnal ilmiah di bidang Bisnis Digital dan Inovasi Teknologi. DBESTI: Journal of Digital Business and Technology Innovation akan diterbitkan oleh LPPM STT Terpadu Nurul Fikri dengan periode dua kali dalam setahun, yakni pada bulan Mei dan November.
Arjuna Subject : Umum - Umum
Articles 20 Documents
 1   2 
Search results for , issue "Vol 2 No 1 (2025): Mei, 2025" : 20 Documents clear
Pengembangan Aplikasi Single Investor Identification (SID) Pasar Modal Indonesia Berbasis Web Menggunakan Metode Extreme Programming Fawwaz, Sya'diyah Nur; Munir, Sirojul; Wiyono, Bambang Harie
DBESTI: Journal of Digital Business and Technology Innovation Vol 2 No 1 (2025): Mei, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/dbesti.v2i1.1380

Abstract

Kustodian Sentral Efek Indonesia (KSEI) is an authorized capital market institution. One of its programs is providing a Single Investor Identification (SID) for the diaspora or Indonesian people living abroad; this SID will act as a single investor identity in the Indonesian Capital Market. This study investigates the design of a Web-Based Diaspora Investment Information System using the .NET Framework, with a primary focus on the business process of obtaining a SID for diaspora investors. The system was developed through iterative planning, design, coding, and testing phases using the Agile Extreme Programming software engineering method. This strategy was chosen since it enabled significant stakeholder participation and flexibility in response to changes throughout the development process. The results of the Blackbox Testing test evaluation method on the application's functionality showed that all 85.7% of the application's features worked well, and the results of feedback on the use of the application by users obtained a score of 88.33%; these results indicate that this application can be used and help PT Custodian Sentral Efek Indonesia to record prospective diaspora investors in the Indonesian Capital Market.
Perancangan UI/UX untuk Pendaftaran Data Calon Karyawan dengan Metode User Centered Design pada PT Pra Kerja Nusantara Rafiq, Muhammad Nur; Wibowo, Edi
DBESTI: Journal of Digital Business and Technology Innovation Vol 2 No 1 (2025): Mei, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/dbesti.v2i1.1382

Abstract

This study discusses the design of User Interface (UI) and User Experience (UX) for the website-based job applicant registration process using the User-Centered Design (UCD) method. PT Pra Kerja Nusantara previously used paper forms to fill in applicant data manually. Now, the company is switching to a website-based system to improve efficiency and effectiveness, but it needs to be optimized to make it easier to use. This research focuses on designing a website for job applicant registration at PT Pra Kerja Nusantara by considering user needs through the UCD method. The design process involves problem analysis, user research, system design, high-fidelity prototyping, and testing and evaluation. The results showed a prototype job applicant registration website with a System Usability Scale (SUS) score of 90.71, indicating an excellent usability level. With the application of effective UI/UX, this website is expected to help PT Pra Kerja Nusantara process and store data efficiently and effectively.
Model Deep Learning untuk Penerjemah Bahasa Isyarat SIBI dengan Arsitektur Transfer Learning Al Fajri, Fikri Pratama; Adriansyah, Ahmad Rio; Munir, Sirojul
DBESTI: Journal of Digital Business and Technology Innovation Vol 2 No 1 (2025): Mei, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/dbesti.v2i1.1476

Abstract

People with speech and hearing disabilities have difficulties when communicating with non-disabled people because they use sign language which is rarely learned in general. To solve this problem, a deep learning model is needed that can detect sign language hand gestures which can then be made a sign language translator application that can facilitate communication between non-disabled people and people with disabilities. The purpose of this research is to create a deep learning model that is able to detect SIBI alphabet type sign language hand gestures with good accuracy. The CNN algorithm model uses Transfer Learning MobilenetV2 architecture and transfer learning method. The results of this study show that the model evaluation reaches 95.45% and the next model can be applied to the sign translator application, for further development it is expected to use more datasets so that the model gets a lot of variation during the training process.
Perbandingan XGB Regressor dengan Algoritma Lain untuk Prediksi Tarif Tol Al Khairi, Said; Adriansyah, Ahmad Rio; Rosyidi, Lukman
DBESTI: Journal of Digital Business and Technology Innovation Vol 2 No 1 (2025): Mei, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/dbesti.v2i1.1477

Abstract

In recent years, toll roads in Indonesia have grown rapidly, many of which were built to facilitate traffic in developed areas and improve the distribution of goods and services to support economic growth. In addition, toll roads play an important role as part of efforts to improve connectivity between cities and regions and accelerate community mobility. Many benefits of toll roads have been felt by the people of Indonesia such as, the Jagorawi toll road which smooths traffic so as to shorten the travel time from one region to another, and many more. The purpose of this research is to create a machine learning prediction of toll road tariffs to provide a reference to the public, optimise toll tariffs in Indonesia, and provide input on toll tariffs as a consideration for the relevant government. This research approach is quantitative using linear regression with XGB Regressor algorithm. The results of making machine learning toll tariff predictions are quite accurate where the accuracy test results using the root mean squared error (RMSE) metric are at 3390.691, with the testing results showing that there are several predicted tariffs that match the original tariff.
Evaluasi Pengujian Kinerja Menggunakan JMeter untuk Menunjang Stabilitas Aplikasi Layanan Perbankan pada PT Bank Rakyat Indonesia Tbk Hamidah, Ida; Haromain, Imam; Drehem, Ishom Muhammad
DBESTI: Journal of Digital Business and Technology Innovation Vol 2 No 1 (2025): Mei, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/dbesti.v2i1.1621

Abstract

The advancement of information technology has had a significant impact on the banking sector, including PT Bank Rakyat Indonesia, which relies on the New Delivery System (NDS) application to support its digital services. NDS is designed to ensure that banking services remain stable, scalable, and fast, even in the face of significant spikes in transaction volumes. As one of BRI's flagship applications, NDS has proven reliable in supporting banking operations. However, performance evaluation is still necessary to ensure the system's readiness to handle growing demands in the digital era. This study uses Performance Testing methods to analyze the performance of NDS using the Apache JMeter tool. Testing is carried out through Load Testing and Stress Testing to measure the application's response under various workloads. Evaluation parameters include response time, throughput, and transaction failure rate. The testing simulates different usage scenarios, from normal to extreme load conditions, to ensure system reliability in various operational situations. The results show that under normal load, NDS has an average response time ranging from 244 ms to 739 ms, throughput of up to 22.26 samples/second, and a transaction failure rate of 0%. However, in high-load scenarios (Stress Testing) with 500 users, the response time increases to 12,691 ms, throughput reaches 36.03 samples/second, and the transaction failure rate is 73.10%. The tests also reveal that CPU usage is close to its maximum capacity (85%), while memory usage remains stable. The analysis shows that NDS requires further optimization in middleware and load distribution to improve application performance and stability. This study provides valuable insights for the development of similar applications in the banking sector to support more stable, efficient, and responsive services.
Penerapan Micro Frontend dengan Next.js dan Module Federation pada Aplikasi Cash Management Fikri, Muhammad; Drehem, Ishom Muhammad; Adriansyah, Ahmad Rio
DBESTI: Journal of Digital Business and Technology Innovation Vol 2 No 1 (2025): Mei, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/dbesti.v2i1.1631

Abstract

The digitalization of banking has made cash management applications essential for business efficiency; however, the monolithic architecture of the front-end in PT. Bank XYZ's cash management application presents significant challenges in terms of scalability and flexibility, particularly with the cash pooling feature. This study implements a Micro Frontend architecture using Next.js and Module Federation to enhance development and maintenance efficiency. The results show that build times have been reduced from 1 hour to 37 minutes, with an average build time of 12 minutes achieved through parallel processes. Deployments have also become faster, with only a few hours between releases. A survey of 11 respondents, including developers, quality assurance personnel, and other key stakeholders, recorded an average satisfaction score of 4.44 out of 5, indicating strong support. This implementation accelerates feedback loops, facilitates parallel development, and streamlines the feature release process, making it highly applicable to all features within the cash management application, thereby improving scalability and flexibility comprehensively.
Evaluasi Penggunaan Aplikasi Ninja Driver di Ninja Xpress Jasinga Bogor Menggunakan PIECES Framework Awaliyah, Rita; Rusmanto; Wibowo, Edi
DBESTI: Journal of Digital Business and Technology Innovation Vol 2 No 1 (2025): Mei, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/dbesti.v2i1.1634

Abstract

The growth of e-commerce in Indonesia has driven the need for fast and ef icient delivery services, including Ninja Xpress,which utilizes the Ninja Driver application to support courier operations. This study aims to evaluate the Ninja Driverapplication at Ninja Xpress Jasinga using the PIECES framework (Performance, Information, Control, Ef iciency, Service).The research employed a quantitative approach through questionnaires distributed to 27 couriers as respondents,complemented by interviews with the company to validate the findings. The results showed average scores for Performance(2.74), Information (3.15), Control (3.27), Ef iciency (3.10), and Service (3.07), with all aspects rated as "agree." Theapplication supports ef iciency and service, such as reducing delivery time and improving the quality of information.However, there are issues with application stability in weak signal areas and delays in the validation process. Overall, theapplication is considered adequate in supporting courier operations but requires improvements in stability and ef iciencyfeatures. Recommendations include enhancing application stability in areas with weak signals, improving the delivery statusvalidation mechanism for faster processing, and developing error-handling features.
Pengembangan Backend Aplikasi Geoproperty dengan Golang di PT. Nerdvana Solusi Teknologi Ramdani, Muhammad Asnur; Nabarian, Tifanny; Maulana, Reza
DBESTI: Journal of Digital Business and Technology Innovation Vol 2 No 1 (2025): Mei, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/dbesti.v2i1.1636

Abstract

This research discusses the backend design of the Golang-based GeoProperty application at PT Nerdvana Solusi Teknologi, which is designed to improve the property search experience with the integration of Geographic Information System (GIS) technology. This research focuses on developing the backend using the Agile Scrum method to ensure optimal functionality in managing spatial and property data. The backend supports key features such as interactive map-based property search, polygon input for search area boundaries, and Point of Interest (POI) visualization around the property. Testing was conducted using the blackbox testing method to evaluate API functionality. The results show that the backend system can meet user needs with reliable performance, provide accurate visualization of property locations, and comprehensive information that supports prospective buyers' decisions.
Peningkatan Efisiensi Jaringan Internet Menggunakan Firewall Fortigate Studi Kasus: PT. Jarvis Integrasi Solusi Radityo, Daffa Bagus; Rustianto, April
DBESTI: Journal of Digital Business and Technology Innovation Vol 2 No 1 (2025): Mei, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/dbesti.v2i1.1695

Abstract

PT Jarvis Integrasi Solutions often experiences unstable internet connections, which disrupt productivity. To address this, the company implemented SD-WAN (Software-Defined Wide Area Network) technology using the FortiGate 40F Firewall, replacing the previous Mikrotik gateway router. This SD-WAN feature enables smarter, more efficient network management by automatically adjusting settings based on connection quality and traffic load. The study used a quantitative method involving system design, SD-WAN configuration, and performance testing for failover and load balancing. Results showed that the FortiGate 40F significantly reduced downtime and improved network distribution. During failover tests, the system quickly switched to a backup path within 1–2 RTOs. Load balancing tests showed stable speeds, with inbound speeds of 7.21 Mbps and 7.17 Mbps and outbound speeds of 829.53 Kbps and 757.76 Kbps. Overall, SD-WAN optimized traffic usage and enhanced connection stability, offering clear benefits to the company's internet operations.
Analisis Sentimen Tagar #KaburAjaDulu Pilihan Migrasi ke Jepang pada Platform X dengan NLP Meliala, Rajhaga Jevanya; Chasanah, Nur Indah; Manik, Jonser Steven Rajali; Pasya, Thoriq Muhammad; Lestari, Humannisa Rubina
DBESTI: Journal of Digital Business and Technology Innovation Vol 2 No 1 (2025): Mei, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/dbesti.v2i1.1756

Abstract

The hashtag #KaburAjaDulu, which went viral on platform X, reflects the concerns of Indonesian society—particularly among younger generations—regarding domestic social and economic pressures, as well as an increasing interest in migrating to Japan. This phenomenon illustrates the complexity of digital public opinion, yet few studies have specifically compared the effectiveness of different sentiment analysis algorithms within this context. Therefore, this study aims to analyze and compare public sentiment toward the #KaburAjaDulu hashtag, particularly about migration to Japan, using a Natural Language Processing (NLP) approach with three sentiment analysis algorithms: VADER, TextBlob, and BERT. A total of 1000 tweets were collected using scraping techniques, and after preprocessing, 967 tweets were included in the analysis. Sentiments were categorized into three classes: positive, negative, and neutral. The results show that VADER and TextBlob tend to classify tweets as neutral or positive, while BERT reveals a dominant negative sentiment of 52.3%. These findings suggest that BERT is more sensitive to context and implicit sentiment in the informal Indonesian language. This study highlights the importance of selecting appropriate algorithms for social media sentiment analysis and contributes to a deeper understanding of digital migration aspirations within Indonesian society.

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