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All Journal Jurnal Informatika Jurnal Dimensi Pratama Teknik Sipil Jurnal Infra Seminar Nasional Informatika (SEMNASIF) Journal of Animation & Games Studies
Liliana Liliana
Program Studi Informatika, Fakultas Teknologi Industri, Universitas Kristen Petra
Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Languange, Linguistic, Communication & Media

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Pengenalan Rambu Lalu Lintas di Indonesia Secara Realtime Menggunakan YOLOv4-tiny Gregorius Nicholas Goenawan; Alvin Nathaniel Tjondrowiguno; Liliana Liliana
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Concentration are crucial when driving. Drivers who lose their concentration tend to have a slower reaction time, and a higher possibility of violating traffic signs. Traffic signs violation is considered a criminal act with harsh penalties. In addition, traffic sign violations interferes with comfort and endanger other road users. Therefore, we need a system that is able to detect signs accurately and quickly which can inform driver in advance. A research on traffic signs detection on Swedish and Slovenian traffic signs use Mask R-CNN model which based on convolutional neural networks [18]. These method was capable of achieving a mAP@50 score that exceeds 95%. However, the research did not evaluate on the detection speed of such methods. In this research, YOLOv4-tiny is used to detect Indonesian traffic signs. Dataset used in this research are independently collected, which consist of nine prohibition signs and two command signs. The YOLOv4-tiny method with input size of 416 x 416 is able to achieve mAP@50 score of 88.55% with detection speed of 19.41 FPS. With modification to input size and dataset, YOLOv4-tiny are able to achieve mAP@50 score up to 89.58% and detection speed up to 30.87 FPS. YOLOv4-tiny are also able to detect road signs from distance of around 5 to 15 meters with 80.42 % accuracy. Indonesian traffic sign recognition program made by utilizing the YOLOv4-tiny model achieve average recall of 72.9%.
Penerapan SVM untuk Klasifikasi Sentimen pada Review Comment Berbahasa Indonesia di Online Shop Yoshua Refo; Silvia Rostianingsih; Liliana Liliana
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

With so many users accessing online shops, comments are an important aspect when shopping. Buyers can provide comments about the goods or thing that have been purchased, both negative comments and positive comments. By collecting various kinds of comments, the data can be used to classify comments. This research will use the Support Vector Machine (SVM) algorithm which is considered the right method for text classification. The method will be tested for its performance, seen from how good and accurate the method used in classifying comments is. In addition, this research also uses kernels, namely Linear kernels, Radial Basis Function (RBF) kernels, and Polynomial kernels as test scenarios. Based on the test results shown, SVM is a good method in classifying text. SVM classifies text that has gone through the preprocessing stage with an accuracy value of 88% on the RBF kernel, 87% on the linear kernel, and 87% on the polynomial kernel. The accuracy value in the aspect classification itself is 78% on the RBF kernel, 78% on the Linear kernel and 74% on the Polynomial kernel.
Form Evaluasi Online Mata Kuliah Pra Skripsi Dan Skripsi Berbasis Android Stephen Cornelius Hertanto; Silvia Rostianingsih; Liliana Liliana
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

In order to support the vision of "Green Campus" implemented by Petra Christian University Surabaya as well as to accommodate the evaluation interests of courses in the new curriculum, namely pre-thesis and thesis. At the evaluation stage of the course, it involves many parties, so to digitize all documents and facilitate coordination, an application is needed to assist the entry process and produce the required reports. So far, the evaluation process that has occurred is quite long and takes a lot of time, namely when evaluating the Pre-Thesis to Thesis. As well as seeing the increasing number of Petra students every year, the coordinating lecturers and supervisors on Pre Thesis and Thesis will be more and more difficult in handling the evaluation. Therefore, this thesis creates an "Online Evaluation Form for Pre-thesis and Thesis courses based on Android" which is an application on an Android-based smartphone that aims to facilitate the coordination of lecturers and supervisors in evaluating these courses. By making this application, it will be easier for the lecturers to fill in the scores and evaluation of the Pre-thesis and Thesis reports without taking much time, and the data created can be more accurate and faster. So that the delivery of grades to students becomes shorter.
Aplikasi Penerjemah Kegiatan Seminar Menjadi Video Bahasa Isyarat BISINDO Dengan Speech To Text Marcel Slamet Sugianto; Liliana Liliana; Anita Nathania Purbowo
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Information at this time is very much needed to increase our knowledge. However, this delivery can be hindered by several conditions such as the inability to hear the deaf community. Based on data from the Data and Information Center of the Ministry of Health of the Republic of Indonesia in 2019, 7.09% of the Indonesian population is deaf. In addition, the delivery of information at the seminar can be hindered by noise and participants sitting far from the speaker will have difficulty hearing the speaker's voice. In this study, we will use Speech-To-Text on the Android application which aims to help translate information in the form of voice delivered as at a seminar into text and will be converted into BISINDO sign language video. The results of testing the use of the Speech-To-Text feature in the application that has been made show that it is able to accommodate approximately 100 words in 1 minute at a time when the speaker speaks without any pause. The Speech-To-Text feature used takes approximately 2 seconds to translate the received voice and the time lag required by the speaker device to the participant's device takes approximately 3-5 seconds after using 5 different internet speeds. For the accuracy of the Speech-To-Text feature that was tested using 3 narrations read by 4 different people, the accuracy of the Speech-To-Text feature has an accuracy of above 80% in general, although there is an accuracy that is below 80% due to the ambiguity of the pronunciation.
Sistem Backend dari Aplikasi Mobile dan Website untuk Sistem Registrasi, Reservasi, dan Identifikasi Penumpang Shuttle Bus UK Petra Michelle Christiana Chandra; Rolly Intan; Liliana Liliana
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

In 2022, Petra Christian University (PCU) launched its shuttle bus program exclusive to the academic community of PCU. This bus operates by picking up and dropping off passengers on the route of West Surabaya – PCU and vice versa. There are overwhelmingly many more members of the academic community of PCU residing in West Surabaya compared to the capacity of the shuttle bus. Registration, reservation, and identification systems are necessary to resolve this problem. The registration system ensures that the passengers are members of the academic community of PCU. The reservation system supports passengers in booking seats for the desired trips. The identification system authenticates the passengers when boarding the shuttle bus. The PCU shuttle bus program is operational and has been using the deployed application properly. Every function and API in the application passes the designed feature testing and matches the appropriate expectations. A survey was conducted of 76 passengers and 1 admin and 2 drivers were interviewed. From 76 passenger respondents, the average satisfaction score is 4.259 out of 5. From the 2 driver interviews, the application received a score of 8 and 10 out of 10. And lastly, the average satisfaction for the admin system and website is 4.75 out of 5.
Procedural Content Generation pada Game Tower Defense menggunakan Perlin Noise dan Algoritma Floyd Warshall Hans Juwiantho; Liliana Liliana; Michael Budiono
Journal of Animation and Games Studies Vol 9, No 1 (2023): April 2023
Publisher : Institut Seni Indonesia Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24821/jags.v9i1.8100

Abstract

To distinguish each level, tower defense games require map design, enemy travel routes, and enemy wave designs. Manually designed designs require a lot of effort and time. To overcome this problem, procedural content generation is used to create maps automatically. Not all content can be created automatically, the content designed in this research includes portal design, tower design, enemy design, and tile design. The Map is created automatically using Perlin Noise to determine the type of tiles on the map. To produce a playable map in accordance with the minimum distance requirement of 45 tiles, the position of the player portal and enemy portal need to be checked using the Floyd-Warshall algorithm. The test results show that after 100 attempts, 25 trials need to be repeated because the distance between the portals does not meet the requirements. The average map creation time is 0.99 seconds. The enemy waves on each map also vary from the number of each type and the order in which the enemies come out.
Co-Authors A.A. Ketut Agung Cahyawan W Adi Wibowo Agustinus Noertjahyana Alvin Nathaniel Tjondrowiguno Andre Gunawan Andreas Setiawan Andrew Firman Saputra Anita Nathania Purbowo Anthony Wibisono Anthony Wibisono Armandarius Darmadji Armandarius Darmadji Claffyan Wicaksono Danny Setiawan Putra Robianto Danny Wijaya Danny Wijaya Djoni Haryadi Setiabudi Djoni Haryadi Setiabudi Djoni Haryadi Setiabudi Edna Ricky Fajar Adi Putra Eric Yogi Tjandra Erick Hansel Winer Erick Hansel Winer Ferdi Atmaja Wong Susilo Ferdi Atmaja Wong Susilo Ferdiana Soekresno Ferdiana Soekresno Filbert Sugianto Manunggal Filbert Sugianto Manunggal Franky Halim Gerry Steven Gideon Simon Gideon Simon Gregorius Nicholas Goenawan Gregorius Satia Budhi Gregorius Satia Budhi Hans Juwiantho Hans Juwiantho Henry Novianus Palit Henry Wicaksono Ivana Jovita Handoko Kartika - Gunadi Kartika Gunadi Kartika Gunadi Kartika Gunadi Kartika Gunadi Kevin Jonathan Kevin Reynaldi Tanjung Kiat Stanley Kiat Stanley Leow Wee Kheng Lois Fernando Audi Marcel Slamet Sugianto Meliana Luwuk Meliana Luwuk Michael Alexander Rustan Michael Budiono Michael Budiono Michelle Christiana Chandra Regan Reinaldo Kalendesang Ricky Tanojo Ricky Tanojo Rolly Intan Rudy Adipranata Sendy Andrian Sugianto Silvia Rostianingsih Silvia Rostianingsih Stefani Virgin Stefani Virgin Stephen Cornelius Hertanto Thomas Leman Tomy Widjaja Welly Pontjoharyo Welly Pontjoharyo William Sean Wiyogo Willy Nugraha Utomo Willy Pratama Darmalim Wilson - Wong Foek Tjong Yanuar Christian Ardianto Yanuar Christian Ardianto Yoshua Refo Yulia -- Yulia --