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INDONESIA
Jurnal ULTIMATICS
Published by Universitas Multimedia Nusantara
ISSN : 20854552     EISSN : 2581186X     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering
Jurnal ULTIMATICS merupakan Jurnal Program Studi Teknik Informatika Universitas Multimedia Nusantara yang menyajikan artikel-artikel penelitian ilmiah dalam bidang analisis dan desain sistem, programming, algoritma, rekayasa perangkat lunak, serta isu-isu teoritis dan praktis yang terkini, mencakup komputasi, kecerdasan buatan, pemrograman sistem mobile, serta topik lainnya di bidang Teknik Informatika. Jurnal ULTIMATICS terbit secara berkala dua kali dalam setahun (Juni dan Desember) dan dikelola oleh Program Studi Teknik Informatika Universitas Multimedia Nusantara bekerjasama dengan UMN Press.
Arjuna Subject : -
Articles 275 Documents
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Implementation of SAW Method for Design and Development Apartment Recommendation System in Tangerang Using Mobile-Based Nugraha, Achmad Ilyasa; Kusnadi, Adhi; Tobing, Fenina Adline Twince
ULTIMATICS Vol 15 No 2 (2023): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v15i2.3492

Abstract

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 Manoppo, Arnoldus Yitzhak Petra; Istiono, Wirawan
ULTIMATICS Vol 15 No 2 (2023): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v15i2.3504

Abstract

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 Kandoko, Charoline; Waworuntu, Alexander
ULTIMATICS Vol 15 No 2 (2023): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v15i2.3505

Abstract

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.
Designing a QR Code Attendance System Using BYOD (Bring Your Own Device) Djamarullah, Ahmad Raihan; Nuryasin, Ilyas; Wibowo, Hardianto
ULTIMATICS Vol 16 No 1 (2024): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v16i1.3522

Abstract

Attendance is an activity of collecting attendance data from each individual who attends events, work, and learning. The current application of attendance in certain companies, schools, or universities is still done manually using paper so it is considered less efficient and effective. Digitizing attendance activities can provide many benefits, such as making managing large amounts of attendance data easier. This is usually used in companies or schools. To reduce additional costs, this can be done by using a personal device as a medium for taking attendance, this can be called BYOD or Bring Your Own Device. The attendance that will be designed will use the user's smartphone or mobile device as a medium for taking attendance by scanning the QR code. The results of tests carried out using black box testing on mobile and web applications, shows that all the features contained in both applications are running according to their function. The use of QR Codes and also the implementation of BYOD can make it easier for users to take attendance. Apart from this, it is also easier for admins to manage user attendance data.
U-TAPIS Sal-Tik : Typing Error Detection Using Random Forest Algorithm Overbeek, Marlinda Vasty; Glennardy, Bryan; Mediyawati, Niknik; Nusantara, Samiaji Bintang; Sutomo, Rudi
ULTIMATICS Vol 16 No 1 (2024): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v16i1.3563

Abstract

The development of technology in the field of journalism has grown very rapidly. However, in the field of journalism there are still frequent deviations from the language on online news portals. This can be seen from the aspect of spelling and word usage. Spelling mistakes that occur in the news can cause the information contained in the news to be unclear and ambiguous. Based on these problems, a study was conducted to create a model to detect type error in Indonesian. This model is created using the random forest algorithm. random forest is an algorithm that works by building several decision trees and then combining the decisions from each tree that has been built and taking the most votes from the predictions of each tree so that it will produce stable and accurate predictions. The results of the accuracy of the model in the research that has been done is 100%. However, it should be noted that this 100% result is that the model is able to detect words that are already contained in the dataset. Based on the evaluation results that have been carried out, because the detected word is contained in the dataset, the accuracy issued is 100%. The built model successfully detects type error in Tribunnews news articles.
Recommendation System Coffee Shop using AHP and TOPSIS Methods Siagian, Christian Andreas; Surbakti, Eunike Endariahna; Khaeruzzaman, Yaman
ULTIMATICS Vol 16 No 1 (2024): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v16i1.3579

Abstract

Indonesian people generally like to spend time with friends, family and business colleagues while drinking coffee. This habit of consuming coffee can not only be done at home, but can also be done in other places such as traditional and modern coffee shops. This has also significantly influenced the growth of coffee shops, especially in Tangerang. So people are faced with so many choices and alternative coffee shops to visit. This research was conducted to create a system that can recommend coffee shops in Tangerang based on priority criteria input by the user. Therefore, this recommendation system uses the Multi Criteria Decision Making (MCDM) method, where the process of making decisions is based on several criteria. This research uses the method Analytical Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). This research was tested using the Usefulness, Satisfaction, and Ease of Use (USE) Questionnaire and received a very good rating with an overall score of 87.6\%, so the conclusion was that the average respondent felt helped by this recommendation system.
Sentiment Analysis of IMDB Movie Reviews Using Recurrent Neural Network Algorithm Saputra, Aryasuta; Tobing, Fenina Adline Twince
ULTIMATICS Vol 16 No 1 (2024): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v16i1.3610

Abstract

IMDb is a well-known platform that provides user reviews and ratings of various movies. The number of reviews found on IMDb is quite large, reaching thousands of reviews. Although a movie can have a high overall rating, it is still possible to receive negative reviews from some viewers. Therefore, the purpose of this sentiment classification system is to provide a benchmark for the level of sentiment contained in the movie, and hope that filmmakers can use this information as a reference in the development of their next movie. In this research, reviews from IMDb users are classified into two types, namely positive reviews and negative reviews. The program was created using the Python language with the LSTM (Long Short-Term Memory) classification model of the RNN (Recurrent Neural Network) algorithm. The purpose of using this algorithm is to measure the level of prediction accuracy in the classification process. The results of three test ratios, namely 60:40, 70:30, and 80:20, show that in the scenario of 80% data training and 20% data testing has better performance with the results accuracy of 96%, precision of 97%, recall of 98%, f1-score of 97%.
Comparison of Fine-tuned CNN Architectures for COVID-19 Infection Diagnosis Jonathan, Jonathan; Widjaja, Moeljono; Suryadibrata, Alethea
ULTIMATICS Vol 16 No 1 (2024): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v16i1.3652

Abstract

SARS-CoV-2 (COVID-19) virus spread quickly worldwide affects a variety of industries. The government took preventive steps to control the infection, such as diagnosing the human's lung by taking an X-Ray to see if the lungs were infected with COVID-19 or not. Using several pre-trained Convolutional Neural Network models as the basic model, this research deconstructs the comparison of fine-tuned architecture to identify which pre-trained model delivers the best outcomes in diagnosis by applying machine learning. Comparison is conducted using two scenarios that use batch sizes 64 and 32. Accuracy and f1 score are two evaluation metrics used to justify the model's good performance because the images in the real world, especially for positive classes, are scarce. According to the study, EfficientNetB0 outperforms other pre-trained models, namely ResNet50V2 and Xception, which achieved an accuracy of 0.895 and f1 score of 0.8871.
Public Sentiment Analysis on the Transition from Analog to Digital Television Using the Random Forest Classifier Algorithm Samudera, Elfajar Bintang; Waworuntu, Alexander; Lumba, Ester
ULTIMATICS Vol 16 No 1 (2024): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v16i1.3653

Abstract

Television is one of the most popular media for entertainment and information. Analog television is the most widely used type among the public. However, with technological advancements, analog television is becoming obsolete and is being replaced by digital television, which offers better performance. On November 2, 2022, the Government officially mandated the transition from analog to digital broadcasting. This Analog Switch Off program has elicited various pro and con opinions among the public. Twitter, a widely used social media platform, facilitates rapid communication and information dissemination among users. This study aims to classify public sentiment regarding the Analog Switch Off policy as either positive or negative. The classification model used is the Random Forest algorithm, with the Lexicon Inset for data labeling, Count Vectorizer and TF-IDF Vectorizer for data vectorization and weighting, and various train-test data splits. The study achieved the best classification performance using the Count Vectorizer method, with an 80%:20% train-test data ratio, yielding an accuracy of 88%, precision of 88%, recall of 88%, and an F1-score of 88%. Index Terms—Analog Television; Digital Television; Sentiment; Twitter; Random Forest
Application Fuzzy AHP-TOPSİS Hybrid Method in Facility Location Selection for Software Systems Aliyeva, Kamala Rafig
Ultimatics : Jurnal Teknik Informatika Vol 16 No 2 (2024): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v16i2.3545

Abstract

Facility location is an integral part of the strategic planning process of almost every organization. Selecting the right location for software systems facilities involves considering various factors to ensure optimal performance, reliability, and cost-effectiveness. For business success, and competitive advantage there are some critical factors that very highly affect facility location. They are proximity to customers, infrastructure, labor quality, total cost, suppliers, etc. The criteria for selecting a facility location may be vaguely defined or open to interpretation. External factors such as economic conditions, political stability, and environmental risks may introduce vagueness and unpredictability into facility location decisions. These factors are often beyond the control of decision-makers but can have significant implications for the success of software systems. In this paper we apply fuzzy AHP-TOPSIS hybrid method for facility location in software systems. This offered model combines the fuzzy AHP and the fuzzy TOPSIS methods. Fuzzy AHP (Analytic Hierarchy Process) and fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) are both decision-making methods commonly used in facility location selection. AHP helps in structuring a decision problem into a hierarchy of criteria and alternatives, while TOPSIS ranks alternatives based on their distance to the ideal solution. In the first part of the facility location selection process, we use fuzzy AHP method for determining weights of criteria that are important in selection process. Then by using fuzzy TOPSIS we rank alternatives and select appropriate location for facility.

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