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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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Pembuatan Aplikasi Lelang Berbasis Android Lois Fernando Audi; Liliana Liliana; Agustinus Noertjahyana
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Auction is a process of buying and selling to auction participants, where auction participants will make bids and be sold to bidders at the highest price. Today, conducting an online auction can be done through social media. Based on a survey conducted on CV Toro Developer, people still make auction transactions via Whatsapp. This auction transaction is considered inefficient, where the admin in the Whatsapp group must pay attention to the bid price entered by the auction participant. Therefore, this thesis will make an application so that auction transaction activities can be carried out without admin assistance. This thesis will focus on developing auction applications to facilitate auction transaction activities with chat features, auto bids, deposits, bid features that can be displayed in real-time, and notification features. The test results show that the application can carry out the auction process well from the beginning of creation until the transaction is complete. Also, other features can run well.
Pemodelan Lip Reading Bahasa Indonesia Berbasis Visem Menggunakan VGG16 serta Jaro-Winkler Similarity dan Bigram Henry Wicaksono; Liliana Liliana; Alvin Nathaniel Tjondrowiguno
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Lip reading is a technique used to understand spoken words through visual representation of lip movements. Lip reading has many uses, such as aids for laryngectomy patients and aids for people with hearing disabilities. A research shows that 2.6% of Indonesia’s population has a hearing disability. Thus, lip reading can be a relevant solution in Indonesia. This study aims to model a viseme-based Indonesian lip reading system. The method used in this research is VGG16 which is used as a classifier and Jaro-Winkler similarity and bigram (JW-bigram) which is used as a decoder. The dataset used consists of 25 Indonesian sentences composed of 50 different words and spoken by 12 speakers. The results showed that the lip reading system made using VGG16 and JW-bigram was more effective in terms of accuracy and speed compared to other methods combinations.
Sistem Mobile Application, Tracking Lokasi dan Estimasi Perjalanan Untuk Aplikasi Shuttle Bus Uk Petra Menggunakan Flutter dan Google Maps Kevin Jonathan; Rolly Intan; Liliana Liliana
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Petra Christian University (PCU) is a campus that is already growing rapidly becoming one of the popular university in Indonesia with thousands of students from Indonesia and outside Indonesia which is now located in Jalan Siwalankerto, exactly in number 121-131, Surabaya. Petra Christian University planned to launch Shuttle Bus with west Surabaya – Petra Christian University route to facilitate many of the students from west Surabaya to reach Petra Christian University and vice versa. But, this Shuttlebus needs a control system to manage the usage of this shuttle bus by students. This control system is divided in a few big features, which is registration, reservation, identification, tracking, and features related to rating and notification system. The research results showed that after the "Petra Shuttle Bus" application was designed, most of the passengers benefited from being able to make a reservation in advance along with accessing other important features such as viewing bus locations and rating related schedules for service improvement. In addition, the driver also feels benefited because with the current check-in system, this greatly facilitates the driver in the process of checking passengers’attendance who have made the reservations. Please note that this application is far from perfect and requires further improvement according to users’ feedback.
Adaptive Sparse Transformer untuk Meningkatkan ROUGE-1 Score pada Text Summarization Scientific Paper Andrew Firman Saputra; Liliana Liliana; Djoni Haryadi Setiabudi
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Technology advancement and internet causes lots of information that can be accessed at any time. Journal article is one of such many information that’s available that requires time to read thereof in need of automatic summary. Automatic Text Summarization (ATS) basically a process of making a new text that’s smaller than the original text without removing the meanings from the entire input text. The process of making automatic text summarization can be done in extractive and abstractive way. A summary that was made by an extractive method only able to generate a summary with a word that’s included in the original text, whereas summary that was made by an abstractive method can generate a summary that include word that does not exist in the original text. In the previous research in abstractive summarization is found is not optimal thereof need an improvement. The method used in this research is an abstractive summarization with Adaptive Sparse Transformer. Things that will be done in this research are scraping dataset arxiv machine learning, making the dataset, processing the data and trials on hyperparameter configuration in the model to see ROUGE-1 precision performance. The dataset used is Arxiv Scientific Paper dataset and Arxiv Scientific Paper+Machine Learning dataset. The results of this research showed that the method used capable to compete with state of the art methods with average R-1 precision score of 39.4 for Arxiv Scientific Paper+MachineLearning and 42.5 for Arxiv Scientific Paper.
Penyuaraan Pesan Teks Media Sosial Pada Perangkat Mobile Menggunakan Text To Speech Michael Alexander Rustan; Anita Nathania Purbowo; Liliana Liliana
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

The use of smartphones as a communication tool will increase along with the increase of smartphone users. Based on the data obtained, in early 2021 there are around 167 million smartphone users in Indonesia. The use of smartphone as a communication tool to send messages in its use can also start to annoy people when they are doing activities that require concentration, for example, such as driving. In 2017, there were about 15,341 cases of accidents in America caused by drivers using smartphone. To overcome this problem, the text to speech feature will be used to voicing the incoming messages so smartphone users do not need to open their smartphone to find out the sender and the contents of the message. The results of the tests that carried out on the usage on text to speech feature showed that the system can voiced the incoming messages well. For messages that have abbreviated words, the text to speech feature cannot voiced them properly. As for the tests carried out on the feature to detect the message, the system can detect some message data such as the package name of the application, the sender's name, and also the message content properly. For messages received through group chat, the detection results from the line application, and the whatsapp application have problems, so there are obstacles in the process of voicing group chat messages on the line application and whatsapp applications.
Klasifikasi Benda Organik dan Anorganik Dengan Metode YOLOv3 dan ResNet50 Kevin Reynaldi Tanjung; Liliana Liliana; Hans Juwiantho
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

There are still many Indonesian people throw waste in the wrong place. One of the reasons is that there are still many Indonesian people who still find it difficult to sort organic and inorganic objects. Therefore, the introduction of organic and inorganic objects is very important and we need something that can help in sorting organic and inorganic objects. By knowing the difference between organic and inorganic objects, people can sort out organic and inorganic waste. The methods used are You Only Look Once to get waste objects from an images or videos. The detected object will be cut and the results will be processed by the Convolutional Neural Network with the ResNet50 architectural model for classification. In the YOLOv3 and ResNet50 training process, adjustments are made to find parameters to get best accuracy This research will classify objects on waste objects in images or videos. The Mean Average Precision obtained by YOLOv3 is 45% and the average loss is 91%. For ResNet50 there is rule of thumb where when using input size 416x416 and the lower the number of learning rates can increase accuracy. When combined, ResNet50 is able to increase the accuracy of the detected object types by YOLOv3.
Pewarnaan Otomatis Sketsa Gambar Menggunakan Metode Conditional GAN Untuk Mempercepat Proses Pewarnaan Regan Reinaldo Kalendesang; Liliana Liliana; Djoni Haryadi Setiabudi
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Anime is a Japanese animation that consists of many frames of images. Images that used to make an anime can be made using hand-drawn or using digital-drawn. It takes a lot of time to make an anime. In making anime for 1 second, it needs a total of 24 frames, this is why it takes a lot of time to make anime and also takes a lot of money. Each image also needs to be colored, this is also why making anime takes so much time. The method used in this research is GAN (Generative Adversarial Network) or should we call C-GAN (Conditional Generative Adversarial Network) to make coloring anime sketches easier. Dataset that is used in this research is a pair of sketch images and sketch images that have already been colored.
Penerapan 3D Human Pose Estimation Indoor Area untuk Motion Capture dengan Menggunakan YOLOv4-Tiny, EfficientNet Simple Baseline, dan VideoPose3D Gerry Steven; Liliana Liliana; Anita Nathania Purbowo
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Human pose estimation is a research topic that has goal to estimate every human’s keypoint coordinate that can be connected and make a human skeleton. The development of this topic can be applicated to human activity recognition, human tracking, and motion capture for film and animation. There are several challenges for this topic: diverse human pose, diverse body appearance from clothing and similar parts, and complex environment that may cause foreground occlusion. There are several methods to be used in this research: YOLOv4- Tiny, EfficientNet Simple Baseline, and VideoPose3D. YOLOv4- Tiny will process image input to get bounding box coordinate. This coordinate will be inputted to EfficientNet Simple Baseline modification to get 16 keypoint 2D coordinates. After that, VideoPose3D will processed 2D coordinates into 15 keypoints 3D coordinates. The result from this research is EfficientNet Simple Baseline modification is faster with 4.54ms time compared to its original with time of 5.15ms. Although faster, its modification has its own downside. In term of accuracy, modification still less accurate than its original with highest average Percentage of Correct Keypoints head (PCKh@0.2) 86.89%, and original with PCKh@0.2 89.62%. This affect 3D human pose estimation using VideoPose3D, where using EfficientNet modification resulting Mean Per Joints Position Error (MPJPE) 25.3 mm compared to original Simple Baseline resulting MPJPE 28.1mm.
Penerapan metode hand gesture recognition dalam melakukan kontrol terhadap aplikasi powerpoint dan media player untuk kebutuhan online conference William Sean Wiyogo; Liliana Liliana
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Since the prolonged COVID-19 pandemic, most human activities are seen with the concept of virtual meetings. This concept is helped by the use of an online conferencing platform. As a result, needs arise among the new society. The learning model of hybrid learning, or blended learning is a combination of face-to-face learning with e-learning. This learning method reduces teaching performance due to limited range of motion. Thus, hand tracking gesture recognition can be used as a solution to overcome this problem. This study aims to model a gesture recognition system with statistical and dynamic recognition. The method used in this research is CNN-based RT3D_16F which is used as dynamic motion prediction and Mediapipe hand pipeline which is used as static motion prediction. The data set used consists of 27 movement labels (includes 2 movement labels that shouldn't be recognized as specific moves).
Deteksi Plagiarisme pada Kode Bahasa Pemrograman Java menggunakan XGBoost Tomy Widjaja; Andre Gunawan; Liliana Liliana
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

With the ease of access to information and cloud server technology, it makes it easier for anyone to access the code data. Coupled with the industry 4.0 era, the number of informatics students is also increasing rapidly. This makes code plagiarism easier to do, especially in academic environment Manual checking of plagiarism is repetitive, difficult, and time-consuming task. Therefore, automation for high quality source code plagiarism detection is needed. The dataset used in this research was collected from “Dasar Pemrograman” class at Petra Christian University. After that the code will continue to tokenization preprocessing using java grammar stage. Then, the algorithm will calculate pairwise features using 3 main algorithms, namely levenshtein distance, greedy string tiling, and bigram which will produce 12 features and a collection of statistic features. Finally, the features will be used for the training and inference process on the XGBoost model. The test result shows that the proposed features have better performance metrics than previous research, it has f1-score of 99%. Implementation of preprocessing can also improve performance metrics on the features proposed in this study and in previous research.
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 --