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  • Autonomous Cyber-Physical System Control Using Fuzzy Type 2

    Autonomous Cyber-Physical System Control Using Fuzzy Type 2

    Authors: Sopian Alviana, Taufik Djatna, Shelvie Nidya Neyman, Sri Wahjuni

    Abstract

    Environmental changes in a dynamically changing system require monitoring and control to maximize the results obtained. This research aims to utilize an autonomous control process for cyber-physical systems using type 2 fuzzy logic, which has been fine-tuned to achieve optimal results. The initial framework employed involves developing an interaction framework between physical and cyber components within a cyber-physical system framework. The control process implemented utilizes type 2 fuzzy logic, incorporating uncertain values. Type 2 fuzzy logic is chosen to handle changes in parameter values effectively within the dynamic cyber-physical system environment. The results indicate that the control process employing type 2 fuzzy logic during the cyber-physical system tuning process yields a smaller error value than using type 1 fuzzy control. The accuracy achieved with type 2 fuzzy logic is 98.84% in the control process. Autonomous control plays a crucial role in the decision-making process, facilitating the attainment of optimal result values in controlling dynamic environments. © 2024 Taylor’s University. All rights reserved.

    Author keywords

    Autonomous; Control; Cyber-physical system; Fuzzy type 2

    This article can be accessed at https://www.scopus.com/pages/publications/85184592428

  • Application of Data Mining for Predicting Horticultural Commodities Price

    Application of Data Mining for Predicting Horticultural Commodities Price

    Authors: Dian Dharmayanti, Arsy Opraza Akma, Eddy Soeryanto Soegoto, Lia Warlina

    Abstract

    In Garut Regency, farmers receive their commodities at a selling price that collectors determined. This issue causes farmers to lose money because their income does not correspond with the market price for their goods. This loss has an impact on reducing farmer productivity. Therefore, this research aims to provide recommendations to farmers regarding commodity selling prices for particular periods based on forecast results. This research implements data mining so commodities selling prices can be predicted. Data mining is a way to find patterns or knowledge from past data. Multiple linear regression methods or algorithms are used to find patterns or knowledge with data mining. Multiple linear regression can be used to predict commodities selling prices based on rainfall factors and total production. The application developed can produce recommendations for farmers for commodity selling prices for specific periods based on prediction results, thereby reducing losses for farmers. © 2024 Taylor’s University. All rights reserved.

    Author keywords

    Data mining; Horticultural commodities; Multiple linear regression; Price prediction

    This article can be accessed at https://www.scopus.com/pages/publications/85184573404

  • Risk Assessment of Work Posture in Manufacture Industry for Drilling Pipes

    Risk Assessment of Work Posture in Manufacture Industry for Drilling Pipes

    Authors: Herry Saputra, Purnama Dicki Gilar, Putra Muhamad Luki, Ramdoni Mochamad Sahri, Suryatno Wiganepdo Soegoto

    Abstract

    The objective of this research is to examine the working postures of individuals in the manufacturing sector involved in drilling pipe production, utilizing the REBA and RULA methodologies. These methods serve to identify potential risks associated with the working positions adopted by workers, distinguishing between correct postures and those that may lead to problems. The research involved data collection through field observations and photographs capturing operators’ postures during work. Data processing entailed creating sketches of the operator’s posture and measuring the angles of each part using CorelDRAW. This facilitated aligning the measurement results with the RULA and REBA worksheets. The results indicated that the RULA method, when assessing the operator’s working posture while handling the spindle, yielded a final score of 5. The assessment outcome indicates a need for a thorough examination of the operator’s body positioning, and prompt implementation of alterations in working posture is essential. Conversely, the application of the REBA method to the operator’s stance while dealing with the iron pipe resulted in a score of 8, signifying a significant risk level. Immediate improvements in the working position are considered imperative. © 2024 Taylor’s University. All rights reserved.

    Author keywords

    REBA; Risk assessment; RULA; Work posture

    This article can be accessed at https://www.scopus.com/pages/publications/85184616974

  • Prediction System for Vitamin A Requirements in West Java Indonesia Using Linear Regression

    Prediction System for Vitamin A Requirements in West Java Indonesia Using Linear Regression

    Authors: Sri Nurhayati, Wicaksono M. F, Diana Effendi

    Abstract

    This research aims to analyse the accuracy of the linear regression method in predicting the amount of vitamin A needed and providing information about predicting vitamin A needs within a specific period. Vitamin A is identified as the most crucial nutrient, necessitating external supplementation due to insufficient and low food consumption. The linear regression method is employed in this study, serving as a data analysis technique to predict unknown data values based on related and known data values. The dataset involves the number of vitamin A administrations in each district/city in West Java, Indonesia. Mean absolute perception error (MAPE) was utilized to assess prediction errors. The system requirements analysis used an object-oriented approach with Unified Modeming Language (UML) tools. The comprehensive prediction results yield an average accuracy of 86%, indicating that the linear regression method effectively predicts vitamin A needs in the subsequent period. Functional testing of the system demonstrates a 100% success rate, aligned with the needs analysis, thereby providing information on predicting vitamin A requirements within a specific period for each district/city in West Java. © 2024 Taylor’s University. All rights reserved.

    Author keywords

    Linear regression; Object-oriented based system; Prediction; Vitamin A

    This article can be accessed at https://www.scopus.com/pages/publications/85184606841

  • Prototype Design for a Microcontroller- Based Parking Information System

    Prototype Design for a Microcontroller- Based Parking Information System

    Authors: Euis Neni Hayati, Taufan Ismail Mihrab, Fadlan Alfarezh Hartono, Dida Prambudi, Bobi Kurniawan

    Abstract

    In a parking area, numerous issues exist, such as the lack of information to locate available parking spaces, leading to prolonged search times. To streamline and expedite the search for parking, a parking system can be designed to provide information about full and empty parking spaces. Employing an agile process to address parking challenges, the aim is to shorten queues and provide timely parking information. The envisioned outcome is a system enabling drivers, especially those with specialty vehicles, to identify parking spaces without manual searching. The parking information system prototype incorporates a 16×2 LCD for displaying parking space addresses, LED indicators, and the ability to showcase the number of available parking spaces, enhancing effectiveness and user accessibility. By preventing excessive queues through real-time information on vacant parking spaces, the system reduces congestion and provides smoother parking experiences for drivers. Each parking lot has an infrared sensor to determine occupancy status, while the LCD at the entrance relays information on available spaces. The LED is an indicator light, illuminating when a parking lot is vacant. The microcontroller is the central system, seamlessly connecting and coordinating each component. © 2024 Taylor’s University. All rights reserved.

    Author keywords

    Information system; Microcontroller; Parking

    This article can be accessed at https://www.scopus.com/pages/publications/85184575827

  • Best Classifier Over Feature Selection and Delta Error in Time Series Dataset

    Best Classifier Over Feature Selection and Delta Error in Time Series Dataset

    Authors: Nugroho Widyanto, Jin-Whan Kim, Agus Nursikuwagus

    Abstract

    The selection of the best classifier on conventional machine learning is often made intuitively by observing existing research. It becomes an obstacle when stating high accuracy, regardless of whether the machine suits the dataset. This research proposes a method to deal with the accuracy of using a learning machine so that the accuracy generated can be aligned with the usage of the dataset. This method uses the feature selection method combined with the machine learning classifier. SelectKbest and principal component analysis (PCA) methods combined with the classifier machine by counting confirmed MSE, MAE, R2, and delta errors can predict the appropriate machine learning for the OTHERS datasets. Delta error and R2 by SelectKBest and the PCA can see the Delta Error tendency of its classifier learning. The observed classifiers confirmed the best R2 values on linear and Bayesian regression. The R2 values of Bayesian and linear regression are 0.634 and 0.687, respectively. Average Delta Error of MAE of SelectiKbest < Average Delta Eror of MAE of PCA, 3.21×1015 < 1.37×1016. In future research, we found the challenge of the best classifier in Deep Learning and the method of selecting features appropriate for the time series dataset. © 2024 Taylor’s University. All rights reserved.

    Author keywords

    Chi-square; Classifier; Delta error; Principal component analysis; SelectKBest

    This article can be accessed at https://www.scopus.com/pages/publications/85196260915

  • Analysis of Verticulture as an Alternative Agricultural Method in IndonesiaAuthors: Dafa Rizky Fahreza, Arif Abdan Syakur, Saeful Anwar Oktariansah, Bobi Kurniawan, Rudhi Lesmana

    Abstract
    The purpose of this study is to find out how effective Verti culture can be implemented in Indonesia. This study used qualitative method with literature review as data collection method. The result of this research shows that Verti culture is an alternative agricultural method which probably can help with global lack of food problem and global warming. It is supported by the facts that Verti culture is an efficient, high weather-resistant, and environment friendly agricultural method. The analysis result on this study can be used later as consideration to mass implement Verti culture in Indonesia. © 2024 Taylor’s University. All rights reserved.

    Author keywords
    Farming; Global lack of food; Global warming; Verti culture

    This article can be accessed at https://www.scopus.com/pages/publications/85211044891

  • Implementation of GraphQL in the Dodo Kids Browser Application

    Implementation of GraphQL in the Dodo Kids Browser Application

    Authors: Adam Mukharil Bachtiar, Dian Dharmayanti, Dimas Miftahul Huda

    Abstract

    This study aims to implement GraphQL to address the issues of under-fetching and over-fetching in the Dodo application. Dodo Kids Browser (Dodo) is a cross-platform application that serves as a parental control tool. This application assists parents in managing and monitoring their children’s online activities. The initial testing revealed problems with the backend of the Dodo application, which utilizes the REST API. Specifically, under-fetching and over-fetching were identified as issues that negatively impact performance and the application development process. After a comprehensive review of the existing literature, implementing GraphQL can serve as a viable solution. This solution is primarily due to the functions of GraphQL as a query language, enabling clients to precisely determine the specific data requested from the server. A series of tests were conducted to assess this implementation’s effectiveness. These tests involved comparing the required data attributes specified by the client with the actual data attributes transmitted from the server. Additionally, tests were performed to evaluate the performance of the previous and current systems. Upon analysing the results of these tests, it was discovered that GraphQL effectively resolves the issues of under-fetching and over-fetching that commonly arise in the Dodo Kids Browser application. © 2024 Taylor’s University. All rights reserved.

    Author keywords

    Indonesian sign language system; Learning media; Learning mode; Question mode; Sign language

    This article can be accessed at https://www.scopus.com/pages/publications/85196324733

  • Sign Language Letter Learning Media

    Sign Language Letter Learning Media

    Authors: Myrna Dwi Rahmatya, Mochamad Fajar Wicaksono 

    Abstract

    This research aims to build a sign language learning media, especially alphabet letters. Users can not only learn to act out the sign code but also train and test their understanding through question mode. The system will guide the user to act out the letters in sign language in the learning mode. After that, the user can practice in the practice mode, which is by acting out the sign code and the system will provide voice feedback. Meanwhile, with question mode, users can test their understanding of letters in sign language. In question mode, users will be asked to act out certain signs as instructed. The sign language used in this learning media is the Indonesian Sign Language System (SIBI). In question mode, users will act out the sign language with their hands and will be captured by the camera. In its development, the method used is the waterfall method with the stages of requirements, design, implementation, and testing. At the end of the stage, testing is done using the black-box method. Testing is done on the practice mode and question mode. The test results show that the learning media can work as expected. © 2024 Taylor’s University. All rights reserved.

    Author keywords

    Indonesian sign language system; Learning media; Learning mode; Question mode; Sign language

    This article can be accessed at https://www.scopus.com/pages/publications/85196284506

  • Queue System Analysis Using Arrival Patterns and Customer Service Patterns for Fast Food Restaurants at Simpang Dago Bandung

    Queue System Analysis Using Arrival Patterns and Customer Service Patterns for Fast Food Restaurants at Simpang Dago Bandung

    Authors: Faysal Rafly, Muhammad Rafi Hafizh, Agung Rahmat Fardan, Suryatno Wiganepdo Soegoto, Rudhi Lesmana

    Abstract

    Queues are one of the problems that have a large enough influence for a fast-food restaurant, especially in the world of food and beverage. Queues occur because the high arrival rate is not matched by the maximum level of service. This study aims to determine the queuing model that occurs at the McDonald’s cashier and find out whether the queue model applied is efficient by comparing the results of observations and simulation results. The research method used is descriptive analysis with a quantitative approach to customers at McDonald’s restaurants with arrival times and service times every 20 minutes on both servers. The results showed that there are several things that affect the queuing system, namely arrival time, service time, number of servers and McDonald’s consumer eating hours. From this, we can simulate the addition of servers to reduce queues during peak hours, namely at lunch time. Of course, the optimal performance of the queuing system will provide satisfaction for consumers or buyers because it can reduce waiting time during the purchasing process. © School of Engineering, Taylor’s University.

    Author keywords

    Fast-food restaurant; McDonald’s cashier; Queues; Queuing model; Simulation results

    This article can be accessed at https://www.scopus.com/pages/publications/85197583948