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Journal : Technomedia Journal

Analisis Sentimen Temporal Tentang Kuliner Di Kota Surabaya Berbasis Gender Menggunakan Bahasa Indonesia Asmara, Rengga; Basuki, Achmad; Al Rasyid, Muhammad Udin Harun
Technomedia Journal Vol 5 No 1 Agustus (2020): TMJ (Technomedia Journal)
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (663.922 KB) | DOI: 10.33050/tmj.v5i1.1260

Abstract

Surabaya is the capital city of East Java Province, Indonesia, and the largest metropolitan city in the province. Surabaya is the largest city in Indonesia after Jakarta. With its large area and a fairly dense population, the city of Surabaya has a variety of culinary to offer. This culinary diversity attracts responses and opinions from the public (both positive and negative). People have certain ways to express their opinions, including through social media. Opinions shared by the Indonesians about Surabaya’s culinary in social media provide the right step to know what people think about the culinary places in Surabaya. But these opinions are very diverse because social media does not decide what people will say. We need opinion analysis to gain uses information from those opinions. In this research, we offered a new approach in analyzing the opinion on the culinary places in Surabaya using temporal analysis based opinion mining. The source is the opinions expressed in Foursquare using Indonesian. The rate of the accuracy is still around 67.32%, because other than Indonesian as the formal language used in the express opinions, social media users there also use many local dialects and slangs.
Aplikasi Pembelajaran Sistem Isyarat Bahasa Indonesia (SIBI) Berbasis Voice Menggunakan OpenSIBI Fatmawati, Risa; Asmara, Rengga; Prayogi, Yanuar Risah; Hakkun, Rizky Yuniar
Technomedia Journal Vol 7 No 1 Juni (2022): TMJ (Technomedia Journal)
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1371.038 KB) | DOI: 10.33050/tmj.v7i1.1690

Abstract

Sign language is one of the means of communication for people who are deaf and speech impaired, especially between normal people and people with disabilities in the wider community. But in reality, not everyone can understand the meaning and purpose of the sign language used so that there is a lack of knowledge of normal people about sign language in Indonesia and there is still a lack of effective and easy-to-understand digital learning media. In this study, we propose a new approach to create a sign language learning application for normal people using voice as input which can later display the results of visualization of sign language movements in the form of 3D animation. The display of 3D animation movements uses data that refers to the SIBI (Indonesian Language Sign System) curriculum. This Sign Language application was built by utilizing the Google Speech to Text API to process voice input, Java as the programming language used, and MySQL to manage the database. Based on system testing and on users (general public and persons with disabilities) using the SUS (System Usability Scale) method, it can be concluded that the sign language learning application with Android-based voice input is successful in facilitating the sign language learning process and in terms of usability or usability of the application getting an assessment that the application can be accepted by users and is suitable for use as a learning support media because its features can be understood well.
Monitoring Proyek Akhir Mahasiswa Berbasis Android Pada Sistem Informasi Manajemen PENS Sekar Puranti, Zazabillah; Yuwono, Wiratmoko; Asmara, Rengga
Technomedia Journal Vol 6 No 2 Februari (2022): TMJ (Technomedia Journal)
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (645.363 KB) | DOI: 10.33050/tmj.v6i2.1702

Abstract

ABSTRACT The final project monitoring activity takes place in the university area, where the final project is one of the requirements for students to receive graduation from the campus. At the Electronic Engineering Polytechnic Institute of Surabaya, there is already a website-based final project monitoring application. However, the application is still based on a website, access for supervisors requires a VPN, and there are no reminders for students, supervisors, and examiners which will have a fatal impact on students if the final project monitoring process is not carried out properly. Due to some of these problems, this final report research aims to create an android-based final project monitoring application. This application will assist users in monitoring the final project because access via mobile phones will be easier and no longer need to use a VPN. The application is also equipped with a reminder feature so that users do not forget during the process of monitoring the final project. Keywords Monitoring, Final Project, Android, Electronic Engineering Polytechnic Institute of Surabaya
Deteksi Ras Kucing Menggunakan Compound Model Scaling Convolutional Neural Network Azahro Choirunisa, Nadia; Karlita, Tita; Asmara, Rengga
Technomedia Journal Vol 6 No 2 Februari (2022): TMJ (Technomedia Journal)
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1114.419 KB) | DOI: 10.33050/tmj.v6i2.1704

Abstract

Cat is one of a popular animals in the world. Number of cat breeds in the world only about 1%, so most are dominated by cats mixed or domestic cat. Nevertheless, there are so many different types of cat breeds in the world, that it is sometimes difficult to identify them. Therefore, we need a system that can recognize the types of cat breeds. One technique of deep learning that may apprehend and hit upon gadgets in a photograph is Convolutional Neural Network (CNN). CNN functionality is alleged because the nice technique in phrases of item detection and item recognition. The author used 9 different types of cat breeds containing 2700 images. The EfficientNet-B0 architecture is used on the system. The most optimal model has earned the accuracy of 95%. Keywords : Deep Learning, Convolutional Neural Network (CNN), Cat breeds, EfficientNet-B0.