Jurnal E-Komtek

Implementation of a Web-Based E-Commerce System with RajaOngkir and Midtrans for Gemstone Sales in Tunjungmuli Village

2026-07-03T13:25:17+07:00

The advancement of internet technology has transformed global business through e-commerce. For agate gemstone craft MSMEs in Tunjungmuli Village, whose products possess high economic value due to their aesthetic appeal and rarity, adopting an information system is a strategic way to expand market reach. However, reliance on conventional marketing methods has limited sales growth and market accessibility. This Research and Development (R&D) study employed the ADDIE model to develop an e-commerce system integrated with product information, automatic shipping cost calculation through the RajaOngkir API, and the Midtrans payment gateway, while also evaluating its feasibility. The results show that the e-commerce platform was successfully developed. Evaluation using the Black Box Testing method yielded a system functionality score of 84.6%, which falls within the 81%–100% range and is categorized as Highly Feasible. The findings indicate that minor input-related issues do not affect transaction stability, making the system suitable for optimizing sales among agate gemstone artisans in Tunjungmuli Village.

Design and Development of a Hydroponic Growing Media Monitoring System for The Growth of Melon Plants from Flowering to Harvest Based on The Internet of Things (IoT)

2026-06-30T02:56:06+07:00

Hydroponic melon (Cucumis melo L.) cultivation requires precise environmental parameter monitoring to achieve optimal results. This study aims to design an Internet of Things (IoT)-based monitoring system to monitor temperature, humidity, pH, and TDS in real-time via a website. The system was developed using the Prototype method with Arduino Uno and NodeMCU ESP8266 as the main controllers. The testing phase included system functionality testing, sensor calibration, and User Acceptance Testing (UAT). Technical testing results showed that the average accuracy of the DHT11 temperature sensor reached 96.61%, the pH sensor 99.67%, and the TDS sensor 64.67%. Meanwhile, the UAT results indicated a system feasibility level of 89.33%, categorized as "Very Feasible." System implementation over 8 weeks demonstrated an improvement in harvest quality, where monitored plants had an average fruit weight of 1.398 kg and a sweetness level of 13.25 °Brix, outperforming unmonitored plants which recorded an average of 1.379 kg and 12.75 °Brix. In conclusion, this system effectively provides measurable data, is feasible for user implementation, and contributes to improving harvest quality.

Implementation of a Web-Based Agricultural Management Information System with Integrated Operational and Financial: A Case Study at Okazakki Farm

2026-06-30T02:55:52+07:00

Operational management in small and medium-scale agricultural enterprises is commonly conducted manually, leading to inaccuracies in record-keeping, limited traceability of cultivation cycles, and inconsistencies in financial reporting. This study aims to develop a web-based agricultural management information system that integrates planting, harvesting, labor management, and financial processes at Okazakki Farm. The system was developed using the Rapid Application Development method with iterative prototyping, while system requirements were collected through observation, interviews, and documentation. The system was implemented using a web-based framework and a relational database. The implementation results demonstrate that the system is capable of validating field block availability, recording harvest activities along with associated labor, updating inventory levels, and automatically generating income and expense records. Black-box testing results indicate that all core system functionalities operate in accordance with user requirements. This research contributes to supporting the digitalization of agricultural enterprises through end-to-end integration of operational and financial processes.

Performance Analysis of a Low-Pass Filter for Virtual Camera Rotation Stabilization Using a Gyroscope Sensor

2026-07-05T02:58:50+07:00

The use of mobile device cameras often suffers from rotational instability caused by jitter and sudden orientation changes, reducing visual quality and user experience in virtual camera applications. This study evaluates the effectiveness of a low-pass filter in stabilizing gyroscope-based virtual camera rotation. Experiments were conducted using an iPhone 12 under six movement scenarios: slow rotation, fast rotation, random movement, walking, stair climbing, and motorcycle riding. Euler angle and inter-frame jitter data were analyzed before and after filter implementation. The results show that the low-pass filter significantly reduces rotational jitter in five of the six scenarios. The greatest improvement was observed during walking, with an 86.55% reduction, followed by fast rotation (72.21%) and random movement (68.87%). These findings confirm that the low-pass filter effectively suppresses high-frequency rotational disturbances, enhancing virtual camera stability and providing a practical foundation for developing more reliable gyroscope-based rotation stabilization systems on mobile devices.

Chili Price Prediction Model in Banyumas and Cilacap Regencies Using Comparative Machine Learning Algorithm

2026-07-05T02:58:36+07:00

Fluctuations in chili prices as a strategic commodity often pose challenges to food price stability, particularly in Central Java regions such as Banyumas and Cilacap Regencies. This study aims to explore and compare the performance of three classical machine learning algorithms: Ridge Regression, Lasso Regression, and Random Forest Regressor. This study utilizes daily historical data spanning from January 2018 to June 2025 to identify market patterns and trends. Furthermore, this research projects chili prices for the next 365 days. Consistently, Lasso Regression demonstrated the best performance in both regions. The model achieved the highest accuracy in Banyumas Regency Banyumas (MAPE 2,75%) and Cilacap Regency (MAPE 5,08%). However, visual analysis of long-term predictions revealed that Ridge Regression produced a more realistic graph compared to Lasso Regression. Conversely, Random Forest Regressor failed to capture long-term trends as it yielded stable predictions. The prediction results were subsequently visualized in an interactive dashboard based on the Flask framework.

Comparative Analysis of PCC Load Balancing and Quality of Service (QoS) Queue Tree Methods on Mikrotik for Bandwidth Optimization

2026-07-05T02:58:22+07:00

The increasing demand for fast, stable, and efficient Internet connectivity requires optimal bandwidth management, especially in PLN's operational networks. This study analyzes and compares two MikroTik bandwidth management methods, namely Per Connection Classifier (PCC) Load Balancing and Quality of Service (QoS) Queue Tree, to optimize network performance. An experimental approach was conducted under three traffic conditions: low, medium, and high. The evaluation focused on key network parameters, including throughput, latency, packet loss, and connection stability. The results indicate that PCC Load Balancing achieves higher throughput and more effective traffic distribution across multiple Internet Service Providers (ISPs), making it suitable for networks with many general users. In contrast, QoS Queue Tree provides lower latency and jitter while ensuring better traffic prioritization for critical services such as SCADA systems and internal communications. Therefore, PCC is more effective in maximizing bandwidth utilization, whereas QoS Queue Tree offers superior service quality and network stability. A hybrid implementation of both methods is recommended to achieve optimal efficiency and performance in PLN operational environments.

Classification of Magnetic Resonance Imaging (MRI) Images of Brain Tumors Using Convolutional Neural Network (CNN) Methods with VGG-16 and Xception Architectures

2026-07-05T02:58:08+07:00

rain tumors are critical medical conditions that require early diagnosis to improve treatment
outcomes. Magnetic Resonance Imaging (MRI) is widely utilized for brain tumor detection due to its
ability to produce high-resolution images of soft tissues. Nevertheless, manual interpretation of MRI
images presents several challenges, including time inefficiency and variability among observers. To
address these issues, this study applies the Convolutional Neural Network (CNN) approach using
VGG-16 and Xception architectures to classify brain tumor MRI images and to evaluate their
performance comparatively. The dataset comprises 2,877 MRI images categorized into four classes:
glioma tumor, meningioma tumor, pituitary tumor, and no tumor. Preprocessing stages include
resizing images to 224×224 pixels and dividing the dataset into training, validation, and testing sets
with a ratio of 80:10:10. Model performance is assessed using accuracy, precision, recall, and F1-score
metrics. Experimental results indicate that the VGG-16 architecture achieves an accuracy of 92%, while
the Xception architecture records an accuracy of 91%.

Design of a Website Information System Based on Microcontrollers at BMKG Class 1 Bandung

2026-07-05T02:57:54+07:00

The purpose of this study is to design an information system for visits at BMKG Class 1 Bandung, the method used in this study is observation of objects and literature studies, in addition to using UML to describe the design and agile methods are used for designing information systems. In the development of a website-based information system using the PHP programming language and the Mysql system management database, in addition to using the esp32 microcontroller and RFID as a tool used for reading visit data, the test results of the visit information system at BMKG Class 1 Bandung resulted in the designed information system running well and effectively.

The Effect of Tool Type and Vertical Milling Machine Feeding Depth on ST 42 Steel Surface Roughness

2026-07-06T02:57:45+07:00

The quality of the final surface finish in machining operations is a critical parameter that dictates the performance and wear resistance of mechanical components. This study aims to analyze the effect of tool types (High-Speed Steel [HSS] and Carbide) and variations in depth of cut (0.2 mm, 0.3 mm, 0.4 mm, and 0.5 mm) on the surface roughness of ST 42 steel utilizing a vertical milling machine. The experimental method integrated real-time machine vibration monitoring using a LUTRON VB-8201HA Vibration Meter during the up-milling process. The evaluation of surface topography was measured based on average roughness (Ra), ten-point roughness (Rz), and root-mean-square roughness (Rq) parameters using a Mitutoyo SJ-301 Surface Roughness Tester, which were subsequently correlated with the ISO 1302 roughness grade standard. The results indicated that the cutting tool material characteristics exerted a dominant influence, with the Carbide tool consistently producing significantly superior surfaces compared to the HSS tool. The Carbide tool achieved an overall average Ra value of 0.77 µm, classifying it into the N6 roughness grade (finishing standard), along with 5.12 µm for Rz and 0.97 µm for Rq. Conversely, the HSS tool yielded sub-optimal surface quality with an average Ra of 2.65 µm, classifying it into the N8 roughness grade (roughing standard), alongside 15.65 µm for Rz and 3.41 µm for Rq. Increasing the depth of cut triggered a linear increase in Ra for the HSS tool due to amplified cutting forces however, a contrasting phenomenon occurred with the Carbide tool, where the surface became smoother due to local thermal softening of the workpiece material. In conclusion, the optimum machining combination to achieve minimum surface roughness at the N6 grade standard on ST 42 steel is accomplished by utilizing a Carbide cutting tool operated at deeper depth of cut parameters.

Implementation of The K-Nearest Neighbors (KNN) Algorithm in The Process of Student Graduation Prediction (Case Study of The Bachelor of Informatics Engineering Program, PLN Institute of Technology, Jakarta)

2026-07-10T02:59:28+07:00

Student graduation is one of the key indicators in a university’s Internal Quality Assurance System (SPMI). Based on data from the Bachelor of Informatics Engineering program, out of 305 students from the 2016 cohort, 227 graduated on time and 78 graduated late. This study aims to predict student graduation using the K-Nearest Neighbors (KNN) algorithm. The research stages include data collection and division for training and testing, parameter determination with K=3, and distance calculation between data points. The results show that the KNN model with parameter K=3 achieved an accuracy rate of 90% in predicting student graduation. This demonstrates that the KNN method is effective in predicting student graduation outcomes.

Snack Supply Information System at UD Bunda Ida Using the EOQ Method

2026-07-10T02:59:14+07:00

This research aims to design an integrated inventory information system with the Economic Order Quantity (EOQ) method, equipped with safety stock and reorder points, to assist stores in optimizing inventory control. The EOQ method is used to determine the number of orders that are economical so that it can minimize the total cost of inventory. The developed system not only calculates EOQ, but also manages inventory data in real-time, provides notifications of near-expired products, and re-order recommendations. This study fills the gap from previous studies that are still limited to semi-manual or unintegrated systems. The design results show that the EOQ-based information system is able to improve the efficiency of inventory management, reduce the risk of overstock and stock shortages, and support more accurate decision-making. Thus, this system is expected to help UD Bunda Ida in providing optimal service to consumers while increasing business profits.

Development of a Web-Based Graduation Document Completeness Information System

2026-07-06T09:04:02+07:00

The manual graduation administration process causes data errors, incomplete documents, and legal risks such as diploma revocation. This study aims to develop a web-based graduation document information system to automate final project document verification and improve graduation administration accuracy and efficiency. The study used the waterfall method, including requirements analysis, database and interface design, implementation with PHP and MySQL, and black-box testing. The system features student data management, an 8-document checklist (including file upload), automation of eligibility status, a statistical dashboard, and three report levels. Testing on 47 scenarios achieved a 100% success rate. The web-based system effectively improves graduation data accuracy, eliminates human error, and supports digital transformation of academic services. Further development requires adding student roles and automatic notifications.

Digital Transformation of Locksmith Services through Website Development and Google Ads for Customer Acquisition and Business Sustainability

2026-07-06T09:32:29+07:00

The development of information technology has encouraged small businesses to adopt digital transformation strategies to maintain business sustainability. One of the sectors affected by this change is locksmith services, which traditionally rely on physical storefronts to attract customers. This study aims to implement digital transformation through website development and Google Ads utilization to increase customer acquisition and maintain business continuity after the loss of a physical storefront due to eviction. The research employed the Prototype software development method, consisting of requirements analysis, system design, website development, Google Ads implementation, and system evaluation. The resulting website, accessible at www.kuncipanggilan.com, provides information on key duplication services, car key services, safe lock services, and emergency locksmith assistance. To improve online visibility, Search Engine Optimization (SEO) and Google Ads were implemented. The evaluation results showed that the Google Ads campaign achieved an average Click Through Rate (CTR) of 4.58%, an average Cost Per Click (CPC) of IDR 2,036, and approximately 100 website clicks per day. Furthermore, the digital transformation strategy contributed to a 70% increase in customer acquisition compared to the previous conventional storefront-based business model. The findings indicate that website development combined with digital advertising effectively expands customer reach, improves service accessibility, and supports business sustainability. This study demonstrates that digital transformation can serve as an effective adaptation strategy for service-based businesses facing the loss of physical business locations.

CT-Scan Image Segmentation of Liver Cancer Using the Active Contour Method

2026-07-10T02:58:59+07:00

Liver cancer is one of the most common types of cancer both in Indonesia and throughout the world. The increase in liver cancer cases is thought to be related to the increase in hepatitis B and C virus infections. According to statistical data from Globocan, in 2022 there will be 866,000 cases of liver cancer recorded worldwide, with 758,000 deaths due to this disease. To overcome this challenge, image processing plays an important role in improving image quality and performing segmentation to separate objects based on certain characteristics. In this research, the Contrast Limited Adaptive Histogram Equalization (CLAHE) and Contrast Stretching methods are used to improve image quality, while the Active Contour method is applied for image segmentation. Validation of segmentation results was carried out using Receiver Operating Characteristic (ROC) calculations. Testing was conducted on 21 CT-scan images of liver cancer, yielding an accuracy of 97.16%, a sensitivity of 75.69%, and a specificity of 98.85%. This research was conducted using the MATLAB application (R2015a). These findings demonstrate the effectiveness of the methods used in supporting the diagnosis and treatment of liver cancer

Sustainable Waste Management Assessment of Small–Medium Motorcycle Workshops

2026-07-06T10:33:48+07:00

The growth of small-to-medium-sized motorcycle repair shops in Soloraya has increased the amount of waste that has the potential to pollute the environment if not managed properly. This study analyzes the characteristics of repair shops, the types and amounts of waste, management practices, and the potential economic value from a sustainability perspective. The study was conducted at ten repair shops (n = 10) through observation, structured interviews, and surveys. In one month, the ten workshops produced 1,214 used oil bottles, 337 liters of used oil, and 20 used batteries, as well as non-hazardous waste in the form of metal components and brake pads. The dominance of used bottles and oil reflects the high level of routine maintenance. Management is still limited to temporary storage and delivery to third parties with substandard facilities. Waste has economic value: oil at Rp1,500/liter, batteries and metal at Rp12,000/kg, indicating both environmental risks and circular economic opportunities.

Study of the DTC P0108 Fault on a Suzuki XL7 Engine

2026-07-06T10:50:25+07:00

This study aims to describe the analysis of the causes of problems in the engine of Suzuki XL7 with Diagnostic Trouble Code P0108. The analysis was conducted to identify the causes of this problem in the engine. The research method employed was a quantitative descriptive approach, utilising testing with a Scantool, Multy Tester and Vacuum Gauge. The testing procedure included engine preparation, instrument calibration, and the execution of diagnostics in accordance with established standard procedures. The research results indicate that the cause of the problem lies in the internal circuit of the MAP (manifold absolute pressure) sensor, with an O.L. (open-loop) measurement result, indicating no connection. This result was obtained by analysing the connections within the entire internal circuit of the MAP sensor. Overall, this study provides empirical information regarding the functioning of the MAP sensor in relation to the engine performance of the Suzuki XL7 following measurement analysis conducted in accordance with applicable procedures.

Weaving Architecture Effects on Mechanical and Chemical Performance of Alkali-Treated Coconut Fiber Composites

2026-07-10T02:58:46+07:00

This study examines the effect of fabric architecture and alkali treatment on the properties of coconut fiber–polyester composites as an alternative environmentally friendly material. Coconut fibers were treated with 15% NaOH for 2 hours and woven in basket weave and twill weave patterns. The composites were made using a vacuum-assisted resin infusion method with a fiber fraction of 40%, and compared with E-glass composites as a control. FTIR analysis showed a decrease in the intensity of the absorption band in the range of 1200–1300 cm⁻¹, indicating a reduction in lignin content after alkali treatment. The mechanical test results showed that the basket weave composite had higher tensile and flexural strengths, respectively, of 20.40 N/mm² and 78.45 N/mm², compared to the twill weave at 12.98 N/mm² and 52.31 N/mm². However, the highest impact resistance was obtained in the twill weave at 23.61 J/mm². The results of the study indicate that the weave architecture has a significant effect on the mechanical performance of the composite and has the potential to support the development of sustainable composite materials for engineering applications.

Development of a Motorcycle Charging System Trainer as a Student-Centered Learning Medium for Vocational Automotive Education

2026-07-10T02:58:32+07:00

The Indonesian government prioritizes vocational education as a human resource development strategy to meet industrial needs. This study developed a Trainer for the Motorcycle Charging System at the PVTO Laboratory of PGRI University Yogyakarta using the ADDIE model. The Design phase utilized Autodesk Fusion 360 to design an ergonomic hollow steel frame, while the Development phase included frame fabrication, installation of a standard wiring system, and integration of digital measuring instruments for real-time visualization of electrical parameters. Technical testing results showed 100% system functionality and very high physical feasibility with a validation score of 4.71/5.00. This product has proven effective as a troubleshooting tool that facilitates systematic diagnosis and supports students’ mastery of mechanical competencies.

Development of Problem-Based Learning (PBL) Based Instructional Materials for Automotive Manual Clutch Systems

2026-07-06T17:04:52+07:00

This study aims to develop a Problem Based Learning (PBL) based learning media for the manual clutch system in the Automotive Technology Vocational Education Study Program, Universitas PGRI Yogyakarta. The research used the Research and Development (R&D) method with the 4D model. The teaching aid was developed through design, assembly, and finishing stages using hollow iron. Validation results showed 84% feasibility by media experts, 94% by material experts, and 86.2% by users (very feasible). This media is expected to enhance students’ active understanding through PBL approach before direct practice.

Analysis of Smartphone Camera Stabilization Based on Gyroscope Using Exponential Smoothing in Mobile Applications

2026-07-10T02:58:17+07:00

Camera usage on mobile devices under dynamic conditions frequently induces vibration (jitter) and unstable orientation changes. This study aims to analyze the effectiveness of the Exponential Smoothing method in reducing rotational fluctuations of a gyroscope-based smartphone camera in a mobile application. An experimental approach was employed across six movement scenarios, namely stationary conditions, slow movement, fast movement, walking, stair climbing, and vehicle riding, by measuring rotation angle values and jitter values before and after stabilization. The results indicate a significant reduction in jitter following the application of Exponential Smoothing across all testing scenarios. The gyroscope-based stabilization system utilizing this method is proven effective in improving smartphone camera rotation stability in mobile applications.

Utilizing the Technology Acceptance Model (TAM) to Drive E-Warehouse Adoption in Brebes' Shallot Sector

2026-07-10T02:58:04+07:00

This study explores the factors influencing the adoption of SiJuna, a cold storage-based e-warehouse platform, among shallot farmers in Brebes Regency. Price volatility significantly impacts farmers, leading to economic losses, particularly when prices drop below production costs. SiJuna aims to help farmers by offering cold storage to preserve their harvests during price declines and sell when prices stabilize. Using the Technology Acceptance Model (TAM), data was collected from 90 farmers and analyzed through Structural Equation Modeling (SEM). The results reveal that perceived ease of use and perceived usefulness positively influence farmers' behavioral intention to adopt SiJuna, which in turn significantly affects the actual use of the system. The findings underscore the importance of usability and perceived value in technology adoption, suggesting that a user-friendly design and clear benefits can enhance the adoption of agricultural technologies, ultimately improving post-harvest management and farmers' profitability.

Quality Assurance Integration of Sugeno Fuzzy & Tsukamoto Fuzzy for Readiness in Implementing Document-Based Banking Application QA Checklist

2026-07-08T12:18:49+07:00

This research proposes a decision support expert system for the readiness deployment process based on a QA checklist by integrating the Fuzzy Tsukamoto and Fuzzy Sugeno methods. This research is very necessary because application release failures to production still often occur due to inconsistent testing and reliance on the experience of Quality Assurance (QA), especially in the workplace of the researcher. The variables used for analysis are five, namely error handling, multi-platform testing, performance testing, defect handling, and UAT results. Fuzzification is mapped into 3 categories: LOW/MEDIUM/HIGH, which is implemented using a trapezoid function; Tsukamoto output is in the form of a monotonous curve shaped L/R (rising or falling). Sugeno uses constants or linear functions. In this study, an internal dataset was used with a total of 500 data points, with 185 ready data, 220 partially ready data, and 95 not ready data. I performed numerical mapping on the fuzzification categories [LOW, MEDIUM, HIGH] as [0,30, 0,60, 0,90], for a weight λ of 0.70 and showed an accuracy of 83.8%. This system provides consistent recommendations and conservative safeguards against critical conditions before production release.

Analysis Overall Equipment Effectiveness (OEE) Using Multiple Linear Regression on the Assembly Coil Line at PT. XYZ

2026-07-10T02:57:50+07:00

Production efficiency is a critical factor in the increasingly competitive automotive manufacturing industry. This study analyzes the value of Overall Equipment Effectiveness (OEE) of the Assembly Coil Line at PT. XYZ during February 2026. OEE was evaluated using three main components Availability, Performance Efficiency, and Rate of Quality. Data were collected over 20 working days, with a Planned Production Time of 19,200 minutes and Planned Down Time of 2,880 minutes, resulting in 16,320 minutes of Effective Working Time. The Average OEE reached of 94.48%, comprising Availability of 95.31%, Performance Efficiency of 99.70%, and Rate of Quality of 99,42%, all exceeded the 85% world-class benchmark. Reduced Availability was primarily caused by 670 minutes of unplanned downtime, 36 machine failures, and an average MTBF of 432 minutes. The study recommends implementing Total Productive Maintenance (TPM) and Predictive Maintenance to sustain and further improve production performance.

Development of an Electrical Work Unit Price Analysis System with Random Forest Regressor Approaches

2026-07-16T02:59:29+07:00

The preparation of Cost Budget Plans (RAB) for electrical installation projects is still
commonly performed manually using Microsoft Excel, making cable requirement
calculations and Unit Price Analysis (AHS) time-consuming and prone to errors. This study
develops a machine learning-based system to predict the cable length required for lighting
installations using room characteristics, including the number of rooms, floor area, room
height, and the number of spotlight, downlight, and pendant lighting points. Two
prediction models, Random Forest Regressor and Artificial Neural Network (ANN), were
trained using historical residential electrical installation project data with an 80:20 training
testing split. Model performance was evaluated using R², MAE, MSE, RMSE, and MAPE.
The Random Forest Regressor achieved superior performance with an R² of 0.982 and a
MAPE of 18.94%, outperforming the ANN (R² = 0.942; MAPE = 19.34%). The best model
was integrated into a Streamlit-based web application to support faster, more accurate, and
consistent cable estimation for efficient AHS and RAB preparation.

Evaluation of Internal Control on the Siakad Application at Politeknik Kesehatan Bhakti Setya Indonesia Using Cobit 2019

2026-07-16T02:59:11+07:00

The digitalization of higher education has made Academic Information Systems (SIAKAD) essential assets requiring effective IT internal controls. This study evaluates the capability level of internal controls in the SIAKAD application at Poltekkes Bhakti Setya Indonesia (BSI) using the COBIT 2019 framework and identifies improvement opportunities. Data were collected through in-depth interviews with six key respondents, including IT management, SIAKAD operators, and the Head of Academic Affairs, supported by institutional documents. The assessment focused on five COBIT 2019 processes: APO12, DSS01, DSS05, BAI10, and MEA02. The results indicate that most processes remain at Capability Level 1 (Performed Process), while DSS01 achieved Level 2 (Managed Process). The largest capability gap was identified in MEA02, which remains at Level 0 (Incomplete Process), whereas APO12, DSS05, and BAI10 each showed a gap of two levels. These findings provide practical recommendations to strengthen IT governance and achieve Capability Level 3 (Established Process) through standardized procedures and continuous internal monitoring.

Logistics Departure Scheduling Information System Using the Fifo (First In, First Out) Method at CV. RAS

2026-07-17T02:59:48+07:00

RAS is a trucking transportation company that provides goods delivery services to various destinations. Currently, logistics scheduling is performed manually, leading to scheduling conflicts, recording errors, and delivery delays that reduce operational efficiency. This study aims to design and develop a web-based logistics scheduling information system implementing the First in First Out (FIFO) method to improve logistics management. The research adopted the Research and Development approach using the Waterfall software development model, consisting of requirements analysis, system design, implementation, testing, and maintenance. The FIFO method schedules deliveries according to the sequence of incoming shipment requests, ensuring fair and systematic processing. The developed web-based system simplifies scheduling, data management, and monitoring of logistics activities. System evaluation confirmed that all functional features operated as expected. The results demonstrate that the proposed system effectively minimizes scheduling conflicts, improves data accuracy, enhances operational efficiency, and supports better decision-making for logistics scheduling at CV. RAS.