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Best : Journal of Applied Electrical, Science and Technology
Published by Universitas PGRI Adi Buana Surabaya
ISSN : 27152871     EISSN : 27145247     DOI : https://doi.org/10.36456/best.vol3.no1
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Physics
A Journal that contain Applied Electrical, Science & Technology. Published twice a year, in March and September. P-ISSN: 2715-2871(print), and E-ISSN: 2714-5247 (online).
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 148 Documents
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Design and Development of a Web-Based Employee Attendance and Payroll Information System at CV Expressa Wanda Fadillah; Hanifah Permatasari; Moh. Muhtarom
BEST Vol 7 No 2 (2025): BEST
Publisher : Universitas PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/agn6m149

Abstract

This study aims to design and build a web-based employee attendance and payroll information system at CV Expressa to overcome problems arising from manual processes, such as late salaries, data recapitulation errors, and lack of transparency. The method used is the System Development Life Cycle (SDLC) waterfall model approach, which includes needs analysis, system design, implementation using the Laravel framework and MySQL database, testing with the blackbox method, and maintenance. The results of the study show that the system built is able to automate GPS-based attendance recording and salary calculations, accelerate data recapitulation, and provide independent payslip access for employees. This system also succeeded in increasing operational efficiency and data accuracy, as well as reducing administrative workload. However, this study has limitations in the scope of implementation which is still limited to one company and does not include advanced security features such as biometric authentication and mobile applications. Further development is recommended to improve the scalability and flexibility of the system.
Design and Construction of Web-Based Budgeting Submission Information System at CV Expressa Muhammad Hashfi Rafid Muttaqin; Hanifah Permatasari; Dwi Hartanti
BEST Vol 7 No 2 (2025): BEST
Publisher : Universitas PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/rw747x67

Abstract

CV Expressa faces problems in budget management due to a slow manual process, less transparent, and vulnerable to errors. This study aims to design a web -based budgeting information system to improve efficiency and accuracy. System development uses the SDLC Waterfall method (Analysis of Needs, Design, Implementation, Testing, Maintenance) with Laravel Technology (PHP) and PostgreSQL Database. Features include budget submission, tiered approval, reporting, and audit trail. Blackbox testing test results show all functions run optimally, supported by automatic notifications and printed reports. This system is proven to speed up the process, reduce errors, and increase budget transparency at CV Expressa
Design and Construction of Pharmacy Sales Information System Sanggita Erinne; agustina srirahayu; Nibras Faiq Muhammad
BEST Vol 7 No 2 (2025): BEST
Publisher : Universitas PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/gb8xvd83

Abstract

Hero Farma Pharmacy in Boyolali serves more than 40 daily transactions but still uses a manual Excel recording system that is prone to human error , data duplication, and slow in reporting. This study aims to create a web-based sales information system to improve the efficiency and accuracy of pharmacy operations. The research method uses a waterfall which includes the stages of needs analysis through interviews and observations, system design with UML, implementation using Laravel 10 and React.js integrated with Inertia.js, and blackbox testing. The implementation results show that the system has been successfully built with a structured database. Blackbox testing on 8 main functions. This web-based information system has succeeded in replacing the manual Excel process , minimizing recording errors, increasing operational efficiency, and supporting better managerial decisions to support pharmacy performance.
Application of Knowledge Based Method in Mobile Application-Based Cat Feed Recommendation System Farrel Putra Ediansyah; Pramono; Dwi Hartanti
BEST Vol 7 No 2 (2025): BEST
Publisher : Universitas PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/m2w0fk03

Abstract

Choosing the right cat food is often an obstacle for Giant Pet shop customers due to the many product variations and monotonous recommendations from sellers. This study designs a mobile application-based cat food recommendation system by implementing a knowledge-based method and a constraint-based approach. The system allows users to receive product suggestions based on brand attributes, taste, cat age, weight, price, and type of food. Data collection was carried out through literature studies and direct observations at Giant Pet shop, with system development following the waterfall model including needs analysis, UML design, and implementation. The results of the system test showed very good performance with a precision of 88.90% which proves the accuracy of recommendations according to user criteria, and a recall of 100% which shows completeness in displaying all relevant products. These results confirm that the system can help and make it easier for users to find products that suit their needs.
Design of Omniwheel Kinematics Learning Platform using ESP32 and Microsoft Visual Studio Alamsyah, Sayyidul Aulia; Diptya Widayaka, Parama; Puspitaningayu, Pradini; Ikhsan, Taj Hakam; Arya Pradana, Rifando; Rizky Herdiansyah Palma, Ryan; Zuhayr Achmad, Ibrohim
BEST Vol 7 No 2 (2025): BEST
Publisher : Universitas PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/fn9f2t21

Abstract

Wheeled robots have evolved significantly, starting from simple designs that utilized a single wheel for maneuvering to the present day, where there are numerous types capable of moving in all directions. The increasing complexity of wheeled robots today has created a learning gap for students who are just entering the world of robotics and the advanced robots that currently exist. Based on this problem, a mobile robot learning platform is needed to bridge their knowledge. The design of this platform is expected to help guide students’ learning of omniwheel robot kinematics in terms of robot model preparation, robot firmware design, communication design between the PC and the robot, and the implementation of kinematic formulas as robot commands. This platform is also designed to be universal, so it can be implemented for ready-made robots or robots built with any type of microcontroller. Comprehensive testing was performed for both movement modes in the application: forward kinematics and inverse kinematics. The forward kinematics test was carried out by assigning speed values to each motor individually. The inverse kinematics test was cariied out by assigning target position in cartesian plane. This platform is expected to serve as a valuable tool in the study of omniwheel robot kinematics.
Short Circuit Current Analysis and Recloser Coordination in 20 kV Distribution Network Using Manual Calculation and ETAP Software Simulation Riswanda; Putri, Raihan; Abdul Muthalib, Muchlis
BEST Vol 7 No 2 (2025): BEST
Publisher : Universitas PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/nw6kbg33

Abstract

This study aims to analyze the performance of reclosers in improving the reliability of the 20 kilovolt distribution network at PT PLN (Persero) UP3 Lhokseumawe. The research focuses on optimizing the placement and delay time settings of reclosers based on fault current and network impedance. A comparative method was used involving manual calculations and simulation using ETAP 16.0.0 software. The object of study is the CD 12 feeder. The simulation evaluates fault currents and the corresponding recloser delay times at several bus locations. Results show that the closer the fault location to the power source, the higher the short-circuit current, which leads to shorter recloser operating time. Conversely, longer distances result in lower fault currents and longer delay settings. The analysis confirms that proper coordination and parameter settings significantly improve system protection and recovery. Moreover, differences between manual and simulation results emphasize the importance of digital tools in distribution network analysis. The study concludes that recloser configuration based on accurate load profiles and fault data enhances overall system performance and operational efficiency.
P2GS Web-Based E-CRM with WhatsApp API for MSME Customer Engagement Alia Akhmad, Khabib; Nurohman
BEST Vol 7 No 2 (2025): BEST
Publisher : Universitas PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/jjxnrx20

Abstract

This study discusses the development, implementation, and user guide of the web-based Electronic Customer Relationship Management (E-CRM) P2GS system integrated with the WhatsApp API as an innovative solution for customer relationship management in Micro, Small, and Medium Enterprises (MSMEs). The system was developed using the System Development Life Cycle (SDLC) Waterfall model, comprising requirement analysis, design, implementation, testing, and evaluation stages. The trial was conducted on five MSMEs that are members of Perkumpulan Pengusaha Gading Sukowati (P2GS) in Sragen. Key features include a dashboard, sales management, purchase management, product master data, stock-taking, reporting, and store settings. The WhatsApp API integration enables automated messaging to customers, enhancing retention and engagement. Evaluation results indicate a 23% increase in customer retention, an 18% reduction in marketing costs, and a 12% increase in monthly revenue. The system’s usage is documented in the P2GS E-CRM Application User Guide to facilitate adoption and training. This study demonstrates that integrating popular technologies into E-CRM systems can significantly improve efficiency and performance in MSMEs
Integration of Concatenated Deep Learning Models with ResNet Backbone for Automated Corn Leaf Disease Identification imam sudianto, Achmad; Sigit Susanto Putro; Eka Mala Sari; Ika Oktavia Suzanti; Aeri Rachmad; Wildan Surya Wijaya
BEST Vol 7 No 2 (2025): BEST
Publisher : Universitas PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/3kct9e57

Abstract

Corn is one of Indonesia's food commodities, which is an alternative food that supports food diversification in Indonesia. However, leaf infections in corn plants often cause significant yield losses and threaten food security. Early detection of this disease is very important, especially for small farmers, because conventional diagnostic methods that rely on agronomists are expensive and time-consuming. Recent advances in Agricultural Artificial Intelligence (AI) and image processing have facilitated automatic plant disease recognition through Convolutional Neural Networks (CNN), with ResNet as the main backbone combined through concatenation with MobileNetV3, DenseNet161, and GoogleNet. The dataset consists of 4,000 images divided into 2,560 training data, 640 validation data, and 800 test data, with image sizes adjusted to 224×224 pixels. The dataset consists of 4,000 images distributed across four categories: gray leaf spot, common rust, northern leaf blight, and healthy leaf. The testing was conducted using three different optimizers, namely Adam, RMSprop, and SGD, with a learning rate of 0.01. The experimental results showed that the SGD optimizer provided the best performance with a loss value of 0.2275, accuracy of 0.9513, precision of 0.9536, recall of 0.9513, and F1-score of 0.9512. These findings confirm that the combination of ResNet, MobileNetV3, DenseNet161, and GoogleNet architectures with the SGD optimizer can significantly improve the accuracy of corn leaf disease detection, making it a potential application for automatic detection systems in support of smart farming practices.

Page 15 of 15 | Total Record : 148

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