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All Journal International Journal of New Media Technology Jurnal ULTIMATICS Jurnal Sisfotek Global
Tobing, Fenina Adline Twince
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Journal : Jurnal ULTIMATICS

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Implementation of Scrum Method for Designing Website-Based E-commerce Application (Case Study: Putra Prabu Workshop) Wijaya, William; 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.v15i2.3487

Abstract

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.
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.
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%.
Co-Authors ahmad arifin Andari, Windi Anwar Hadi, Anwar Apriliani, Apriliani Ariyanto, Dwi Wahyu Armanda, Muhammad Geneva, Erick Abraham Hamami, Miftahul kusnadi, adhi Lay, Ferry Mustafa, Siti Nugraha, Achmad Ilyasa Nurmaesah, Nunung Pribadi, Ardian Saputra, Aryasuta Triono Triono Tullah, Rahmat William Wijaya