Ultimatics : Jurnal Teknik Informatika

Bacteria Recognition Application Model Using Marker-Based Augmented Reality for Android Mobile Devices

Asri Mulyani, Dede Kurniadi, Hadi Bagus Fadillah — Tue, 23 Jan 2024 03:51:13 +0000

This article aims to develop a multimedia application model for bacterial recognition using Marker-Based Augmented Reality (Marker-Based AR) technology for Android mobile devices. Marker-based tracking creates mobile augmented reality markers to increase user interaction in Marker-Based Augmented Reality systems. The software development method uses the Multimedia Development Life Cycle, which consists of 6 phases: concept, design, material collecting, assembly, testing, and distribution. The results of this study are a model of a multimedia application for bacterial recognition using Marker-Based AR, which has a marker-based tracking feature and displays bacterial objects in 3 dimensions along with their explanations and exercise questions. Based on user tests, it shows that the application model developed helps and makes it easier to learn about bacteria independently using Android mobile devices more easily and interestingly. This is proven based on beta testing towards users who got a score of 73.68% is obtained which agrees.

Design and Development of a Learning Style Identification Application for JPTK Students using the K-Nearest Neighbor

Firdaus Ditio Ramadhan, Febri Liantoni, Nurcahya Pradana Taufik Prakisya — Tue, 23 Jan 2024 00:00:00 +0000

Learning styles are crucial for all students, as the chosen learning style can greatly assist them in learning. The data source for this research originates from questionnaire results distributed to JPTK students of the 2019-2021 cohorts, which were used to assess the effectiveness of a learning style product on the students' JPTK website. This study employs the K-Nearest Neighbor approach, which utilizes the principle of nearest neighbors to categorize students' learning styles based on provided features. The data used in this research is derived from the website that students use to input information about their preferred learning styles. Various elements, including visual, auditory, and kinesthetic preferences, are present in the questionnaire on the website. Subsequently, the data is processed and fed into a Python K Nearest Neighbor model to predict students' learning styles and nearest neighbors. The evaluation results indicate that the developed classification model achieves a reasonably high accuracy level of 93%, making it a useful tool for effectively and efficiently identifying students' learning styles. It is hoped that implementing this learning style classification model will benefit the field of education. By understanding students' learning styles, educators can create more tailored lesson plans, enhance learning outcomes, and reduce the likelihood of knowledge loss.

REAL-TIME TOMATO QUALITY DETECTION SYSTEM USING YOU ONLY LOOK ONCE (YOLOv7) ALGORITHM

Isna Ayu Muarofah, Muhammad Jauhar Vikri, Ita Aristia Sa’ida — Tue, 23 Jan 2024 05:26:20 +0000

Real-time object detection is a crucial aspect of computer vision. With the increasing prominence of the big data field, it has become easier to gather data from various sources. Over the past few decades, computer vision inspection systems have become essential tools in agricultural operations, and their usage has seen a significant rise. Computer vision automation-based technology in agriculture is increasingly being employed to enhance productivity and efficiency. Tomato is a widely utilized crop commodity, finding applications in food, cosmetics, and pharmaceuticals. Consequently, tomato farming continues to evolve and has become one of the nation's export commodities. YOLO is an algorithm capable of real-time object detection and recognition. In this study, the YOLOv7-tiny architecture, which has lower computational overhead, was utilized. For quality detection of tomatoes, they were categorized into three classes: ripe, unripe, and defective. The trained model yielded a recall score of 0.97, precision of 1.0, a PR-curve of 0.838, and an F1-score of 0.81, indicating that the model learned effectively. The research achieved an accuracy of 90.6% on original images with an average IoU of 0.90 and a detection time of 2.7 seconds. In images with added light disturbance, the average accuracy was 91.2%. Images with reduced light yielded an average accuracy of 92%, while images with blur disturbance had an average accuracy of 78.2%. In real-time testing, ripe tomatoes were detected up to a maximum distance of 90cm, unripe tomatoes at 90cm, and defective tomatoes at 70cm.

Sentiment Analysis on Song Lyrics for Song Popularity Prediction Using BERT

Hana Agatha, Farica Perdana Putri, Alethea Suryadibrata — Tue, 23 Jan 2024 09:43:22 +0000

The increasingly competitiveness in music industry is giving some musicians disadvantages. Musicians need to pay more attention to the factors that influence the popularity of a song, so their song can be popular and they can gain a lot of profit. One of the various factors that can affect a song popularity is the lyrics. The influence of the lyrics can be explored through sentiment analysis. Sentiment analysis is a computing study that identify sentiments or emotions in a text. By conducting sentiment analysis on the lyrics, song popularity can be predicted. Based on the prediction result, songwriters can evaluate their lyrics, so their song can be popular. Bidirectional Encoder Representations from Transformers (BERT) is an excellent algorithm in terms of sentiment analysis. In this study, a BERT model was developed to predict the song popularity, based on the sentiment analysis of the song lyrics. The popularity class of a song will be predicted, based on the results of lyrics sentiment analysis. The developed model is a model that has been trained with English songs. Based on the experiment, the model that used oversampling method achieved accuracy by 87%, precision by 88%, recall by 87%, and f1-score by 87%.

Implementation of Scrum Method for Designing Website-Based E-commerce Application (Case Study: Putra Prabu Workshop)

William Wijaya, Fenina Adline Twince Tobing — Thu, 25 Jan 2024 09:01:13 +0000

The internet is a technology that has now become a major necessity in the world. There are many applications designed using the internet to meet daily needs, such as educational, commercial and other applications. according to DataIndonesia.id the number of motorized vehicles in Indonesia, which according to vehicles in Indonesia reached 141.99 million units in 2021. Bengkel Putra Prabu is a workshop that operates in the city of Prabumulih, Putra Prabu has several problems, such as lack of intensive advertising. Scrum is a software engineering method using agile principles that relies on team collaboration, incremental products and an iteration process to realize the final result. The results show user acceptance of the system system was 76.06% for the Perceived Ease Of Use category, 73.51% for the Perceived Usefulness category, 71.53% for the Atitude Toward Using category, and 71.89% for the Behavioral Intentional category. The conclusion of this research the system that has been created is well received by users.

Efficient Order Management: Design and Implementation of a System using Scheduling Algorithms and Expert Validation

Eunike Endariahna Surbakti, Nazim Rizky, Ivransa Zudhi Pane, Filbert Khouwira — Fri, 26 Jan 2024 00:00:00 +0000

This research focuses on the crucial role of system interfaces in enhancing user experience, particularly in the context of an online canteen ordering system. A well-designed interface not only improves user satisfaction but also streamlines the ordering process, addressing issues like queuing in canteens. The study employs Expert Validation to gather valuable insights from experts, ensuring a robust foundation for system development and evaluation. The online canteen ordering system facilitates food orders through an application, eliminating the need for users to physically visit the canteen. This approach not only benefits users but also aids canteen management in efficient order handling.The scheduling algorithms, FCFS (First Come First Served) and SJF (Shortest Job First), are utilized to manage incoming orders. FCFS, chosen for its intuitive handling of queuing problems, complements the SJF algorithm, which excels in efficiently managing numerous orders. The system dynamically switches between these algorithms based on the order load, resulting in an effective queuing structure. Usability testing is conducted to evaluate the system’s user-friendliness, with an impressive average score of 86.6%. This indicates that the system is wellreceived and navigable by users. The website implementation receives an ”good” categorization through UEQ (User Experience Questionnaire) testing, with attractive design and high scores in aspects like Perspicuity, Efficiency, Dependability, Stimulation, and Novelty. These findings collectively affirm the success of the designed interface in delivering a positive user experience for the online canteen ordering system.

Implementation of SAW Method for Design and Development Apartment Recommendation System in Tangerang Using Mobile-Based

Achmad Ilyasa Nugraha, Adhi Kusnadi, Fenina Adline Twince Tobing — Fri, 26 Jan 2024 03:14:05 +0000

The house is no longer the sole type of residence available while looking for a place to live. Apartments are a solution for those who need a place to live in locations with limited land, such as Tangerang, in today’s period. However, criteria are needed to choose an apartment based on a person’s needs, thus in this project, we will develop and create an apartment recommendation system in Tangerang using the SAW approach to make it easy for people to choose the best apartment. The user’s choice will be determined by the recommendation system based on their interests, activity, and other data. To put the recommendation system into action, the FMADM method must be employed. A Simple Additive Weighing (SAW) approach is required to complete this FMADM, which is a mechanism for computing the number of performance appraisals for each alternative based on all criteria. This recommendation system is called APARTKU, and it was created with HTML5, CSS, and AngularJS, as well as the Ionic Framework and the Firebase Database. The system was then put to the test by administering questionnaires to 32 respondents using the DeLone and McLean methodologies, and the results were tallied using the Likert Scale method, yielding a score of 90.64 percent, based on the interval on the Likert Scale technique, these results imply that the application has been constructed and designed very well.

Cloud-Based ERP System Backend Design, study case: PT Cranium Royal Aditama

Arnoldus Yitzhak Petra Manoppo, Wirawan Istiono — Fri, 02 Feb 2024 08:40:45 +0000

An ERP system is a comprehensive software solution that facilitates the integration of all resources inside a firm. PT Cranium Royal Aditama is a company specializing in the development of Enterprise Resource Planning (ERP) solutions for other businesses. The ERP system of Cranium was constructed on the .Net architecture. Nevertheless, the situation remains unchanged. The Net framework is constrained by its compatibility exclusively with the Windows operating system. Cranium developed a cloud-based ERP system using Java programming language to ensure flexibility and compatibility with all operating systems. The backend of the ERP system is constructed utilizing a monolithic modular architecture, employing Java Springboot as a framework and PostgreSQL as the database. The purchasing, inventory control, and production planning modules are responsible for the design and development process. The design and development of the ERP system backend is now underway, however it is still in the development stage and is currently confined to a basic CRUD technique

Development of a Mouse Pad Selection Recommendation System Using the Simple Additive Weighting (SAW) Approach

Charoline Kandoko, Alexander Waworuntu — Tue, 06 Feb 2024 03:25:56 +0000

In the current era of technological advancement and growth, especially in the realm of virtual entertainment, specialized equipment like mouse pads has become increasingly essential. Often, the vast array of mouse pad types and brands available can be overwhelming, making it challenging for consumers to choose one that meets their specific needs. This research aims to design and develop a mouse pad recommendation system to assist individuals in selecting the most suitable mouse pad. The study employs the Simple Additive Weighting method, a weighted sum approach for problem-solving, enabling users to receive tailored recommendations based on criteria such as size, thickness, stitching, material, and price across various brands. User satisfaction was measured using the End User Computing Satisfaction (EUCS) method, achieving a satisfaction percentage of 88.67%. This indicates that the system is effective as a mouse pad recommendation tool. The mouse pad recommendation system has been successfully constructed using the Simple Additive Weighting method, following a comprehensive process of design, development, and system testing.