Jurnal Bumigora Information Technology (BITe)

Utilization of the Internet of Things in Monitoring Hydroponic Lettuce Cultivation

2024-06-30T19:44:35+08:00

Background: Urban residents who create agricultural systems with hydroponic techniques are very busy and do not have time to monitor plant growth.
Objective: This study aims to utilize the Internet of Things (IoT) in monitoring hydroponic lettuce cultivation with the Nutrient Film Technique (NFT) system using ESP32.
Methods: The method used in this study is Rule-Based Automatic Control for monitoring hydroponic lettuce cultivation.
Result:The results of this research are successfully building a monitoring system with a web interface and mobile interface has been successfully built. The system that was built successfully controlled pH and hydroponic nutrients automatically with a pH sensor accuracy of 97.19% and a nutrient sensor of 97.815%.
Conclusion: The implementation of a control and monitoring system for hydroponic lettuce cultivation can be applied because it has high accuracy.

Implementation of the Multi Attribute Utility Theory (MAUT) Method for Selecting the Best Affiliate Marketing

2024-06-30T19:44:35+08:00

Background: Digital marketing has become crucial for companies to remain relevant and grow. One common marketing strategy used is through collaboration with affiliate marketing. However, many companies still need help selecting the best affiliate marketing, often relying on subjective approaches.
Objective: This research aims to develop a Decision Support System (DSS) using the MAUT method to choose the best affiliate marketing in the digital marketing industry.
Method: This research method involves applying the MAUT method to identify normalization value variations among affiliate marketing options, resulting in a ranking of affiliate marketers.
Result: The results of this research show that Sugiharto, Rifan Jauhari, and Nina Dwi Lestari rank the highest, with respective preference values of 0.8750 and 0.8625.
Conclusion: The developed DSS successfully manages affiliate marketing data, providing valuable information for decision-making processes. This study contributes significantly to data management and marketing and has potential applications in various business contexts.

Shoe Dryer Using Fuzzy Logic Controller with Internet of Things-Based Monitoring

2024-06-30T19:44:35+08:00

Background: When the rainy season arrives, the main problem faced is the drying process of shoes due to uncertain weather. Moreover, drying the shoes directly under the sun can reduce the glue's durability and damage the shoes' material.
Objective: This research aims to create an automatic shoe dryer that can be monitored online and uses fuzzy logic to maintain a stable temperature to maintain shoe durability.
Methods: This research uses the fuzzy Mamdani method with ESP32 as a microcontroller to regulate the temperature stability of the shoe drying box.
Results: Sneaker shoes were found to dry at 52% humidity and stable temperature at ± 410C within 82 minutes. Meanwhile, leather shoes dried at 62.9% humidity, and the temperature stabilized at ±350C within 20 minutes.
Conclusion: The application of Mamdani fuzzy logic has an effect in stabilizing the temperature; if the drying box is tested without using a controller, the temperature will continue to increase, and the humidity will drop quickly, resulting in shoes not being completely dry.

Determining a Digital Marketing Strategy Using a Combination of Analytical Network Process (ANP) and Profile Matching

2024-06-30T19:44:35+08:00

Background: Many MSMEs in the city of Matram are experiencing diculties in determining the digital marketing strategy to use. This is due to the many digital marketing strategies that can be used and the many factors that serve as criteria for selection.
Objective: Develop a decision support system using a combination of ANP and profile-matching methods to assist MSMEs in determining the digital marketing strategy to be used.
Methods: The method used in this research is a combination of ANP and Profile Matching Methods.
Result: The combination of methods (ANP) and Profile Matching in determining digital marketing strategies has an accuracy of 83.33%.
Conclusion: The combination of ANP and Profile Matching methods in determining digital marketing strategies has successfully recommended the best digital marketing strategy.

Internet Machine Prototype with a Coin Payment Using a Rock Pi Microcontroller

2024-07-02T08:36:46+08:00

Background: Coins are widely used in game machines to play game applications. Internet use is usually done by purchasing an internet package. This method is often used, but coins are rarely used.
Objective: The aim of this research is how to make a machine that is capable of using coins as internet payment, especially hotspots.
Methods: The research method was carried out using an experimental method with stages of analysis, prototype design, and testing using a descriptive approach.
Result: This research produced 1 one-unit prototype machine equipped with an application for internet hotspots by inserting IDR 500 and IDR 1000 coins with connection limits according to the value of the coins entered.
Conclusion: This research produces prototypes and coin internet application software.

Implementation of Multi-Attribute Utility Theory (MAUT) Method in Gaming Laptop Selection

2024-08-07T12:06:41+08:00

Background: This time, laptops are an essential piece of technology because these instruments can be used for various tasks, including work, play, and education.
Objective: This research aims to develop a decision support system using the MAUT method for selecting gaming laptops.
Methods: The method used in this research is MAUT which is applied to the selection of gaming laptops.
Result: Based on calculations that have been carried out using the MAUT method, it is found that the MSI Cyborg Katana laptop (B13VGK) is the first ranked gaming laptop with a utility value of 0.7035.
Conclusion: The implementation of MAUT for gaming laptop selection is proven to be applicable.

Feasibility and Performance Evaluation of Microprocessor and Fuzzy Logic-Based Overcurrent Relay in Electrical Protection Systems

2024-06-30T19:44:35+08:00

This research focuses on the development and testing of a microprocessor-based Overcurrent Relay (OCR) with the implementation of fuzzy logic control for adaptive setting of TMS values. OCR is a crucial component in the electricity protection system which aims to detect and respond to disturbances due to excessive current, preventing damage to electrical equipment. The aim of this research is to test the feasibility and performance of microprocessor-based OCR with fuzzy logic control in setting TMS values, and compare it with the international standard IEC 60255. The method used in this research is the implementation of the Sugeno type fuzzy logic algorithm on the Atmega 328P microcontroller. This algorithm is used to control the TMS value based on the rotating frequency of the detected overcurrent. The results of this research are a characterization of the OCR response to variations in streaming current and different PS settings. The lowest TOp deviation was observed at higher PS settings, with the best performance in the IDMT OCR type. The use of fuzzy logic control is able to increase the OCR response to overcurrent disturbances, although under normal conditions it sometimes results in a longer TOp. The conclusion of this research is that microprocessor-based OCR with fuzzy logic control can provide protection performance that is adaptive and responsive to dynamic operational environmental conditions. This implementation has the potential to increase the efficiency and leakage of the electricity protection system

Analysis of Rclone Implementation for File Sharing Security on OneDrive Cloud Storage

2024-07-12T17:26:48+08:00

Background: OneDrive provides a reliable infrastructure for storing and managing user data. However, along with the benefits, the security challenges associated with storing and sharing files in the cloud are also increasing. One of the main aspects of cloud storage security management is the file-sharing process. While OneDrive offers a few security features, such as access control and two-factor authentication, there remains a need to strengthen additional layers of security, especially when sharing files with external parties.
Objective: This research aims to analyze the effectiveness of Rclone in improving file-sharing security on OneDrive, especially File Backup and File Encryption.
Methods: This research uses the Network Development Life Cycle (NDLC) method, which includes six stages. This research focuses on three stages: analysis, design, and simulation prototyping.
Result: The application of Rclone for file sharing security on OneDrive can increase data security in cloud storage, as evidenced by three backup attempts on .doc files with an average time of 2.033 seconds and successful encryption of 4 files with an average time of 37 seconds.
Conclusion: Using Rclone as a tool to manage data security on OneDrive improves data protection and provides flexibility and efficiency in file management, making it an effective solution for file sharing security needs in cloud storage

Analysis of Tourist Sentiment towards Tourist Attractions in the Mandalika Special Economic Zone Using the Naïve Bayes Method

2024-08-07T11:51:02+08:00

The Mandalika Special Economic Zone has become one of the most popular destinations for both domestic and international tourists. This popularity highlights the importance of understanding the views and feelings of the tourists. Therefore, this study aims to analyze tourist sentiment towards the attractions in the Mandalika Special Economic Zone. The data analyzed was obtained from 1,144 reviews on the TripAdvisor platform. The research stages included data collection, data labeling, data preprocessing, data transformation, data classification, as well as data analysis and visualization. The results of this study indicate that the majority of tourists have a positive sentiment towards the attractions in the Mandalika Special Economic Zone. Furthermore, testing with the Naïve Bayes algorithm successfully classified tourist sentiments accurately, with consistent accuracy rates obtained from each fold: fold 1: 89.08%, fold 2: 89.96%, fold 3: 88.21%, fold 4: 87.34%, and fold 5: 90.79%.