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  • 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

  • Developing Security Privacy Program in Information System

    Developing Security Privacy Program in Information System

    Authors: Muhamad Afghany Haryatno, Yeffry Handoko Putra

    Abstract

    The amount of information that people generate on daily life have put their smart devices as active participants of the business that runs by numerous organizations. However, following the process the information brought numerous people to consider the safety level, as some personal information might be leaked during the process. In the last few years, there have been a lot of national and international regulations that oblige organizations to follow certain rules in their information security program. This is mainly because leakage of personal information might put the victim’s privacy in danger, resulting in identity theft and perhaps financial loss. For organizations this situation could led them loss trust, reputation, and loyalty from their customers. Therefore, ensuring privacy during the process, storing, and sharing of personal information is important. Although it’s clear that security and privacy are two different terms, upon implementation security often believed covers privacy too. This paper seeks to enhance information system security, by developing privacy program using privacy by design as method. The goal is to illustrate and present some insight of how privacy by design address privacy in information system security. © School of Engineering, Taylor’s University.

    Author keywords

    Information system security; Privacy by design; Privacy program; Security

    This article can be accessed at https://www.scopus.com/pages/publications/85197658546

  • Development of a Machine Learning Model for Multiple Membership Publication Documents

    Development of a Machine Learning Model for Multiple Membership Publication Documents

    authors: Apriani P. Purfini, Stephanie B. R Hersianie, Rio Yunanto

    Abstract

    This research aims to develop a learning model in the text mining process by modifying TFIDF. The methodology employed in this study consists of a literature review, data collection, data preprocessing, and document processing. Text mining is conducted using the title and keyword attributes in publication documents. The outcome of this research is a learning model with modified TFIDF to determine multiple memberships in publication documents. The modification of TFIDF weighting can group words according to their document field categories. In contrast, previous TFIDF methods could only group words per document, making it difficult to determine the field categories of publication documents. The results of this research are expected to provide a solution to achieve more accurate outcomes with the same data scheme. The modification of TFIDF weighting can group words according to their document field categories. These field categories consist of a collection of words from many documents that have characteristics in specific field categories. Longer documents tend to have higher TFIDF weights because they can contain more words. This condition can affect the comparison between long and short documents. TFIDF also does not consider the context surrounding words, so in some cases, context is crucial for understanding the meaning of words or phrases. © School of Engineering, Taylor’s University.

    Author keywords

    Multiple membership; Publication document; TFIDF

    This article can be accessed at https://www.scopus.com/pages/publications/85199474137

  • Server Security and Air Quality Monitoring System Using Raspberry Pi 4 and Telegram

    Server Security and Air Quality Monitoring System Using Raspberry Pi 4 and Telegram

    Authors: Mochamad Fajar Wicaksono, Myrna Dwi Rahmatya

    Abstract

    The purpose of this research is to develop a system that uses Raspberry Pi and IoT technologies to monitor server room conditions such as temperature, humidity, air quality, and access rights security. The contribution of this research is that it makes it easier for users to monitor the server room and take appropriate action when something goes wrong. The method utilized in this study is experimental. The output obtained is in the form of a web display and telegram notifications. The brain of this system is the Raspberry Pi 4. The input received is temperature, humidity, carbon monoxide levels, carbon dioxide, and dust particle values. The thing that causes the Raspberry Pi 4 to activate the buzzer and send notifications via Telegram is when the temperature value is more than 230C, the humidity is less than 45% or 60%, the measured carbon monoxide value is more than 50 ppm, or carbon dioxide is more than 800 ppm or the AQI value of dust particles is more than 100. Regarding access rights, users can only enter the server room using a registered RFID card. Access rights violations will be detected by PIR1, PIR2, and Ultrasonic sensors. If this happens, the Raspberry Pi will take a photo with the Pi Camera, activate the buzzer, and send it via Telegram. The entire system testing process is tested into two main parts: temperature, humidity, AQI testing, and security testing related to access rights according to the program scenario and initial objectives. Test results show that every part is functioning 100%. The overall test shows 100% success where the system can do actions according to program conditions and scenarios. © School of Engineering, Taylor’s University.

    Author keywords

    AQI; Monitoring; Raspberry Pi4; Security; Server room; Telegram

    This article can be accessed at https://www.scopus.com/pages/publications/85198972754