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INDONESIA
Jurnal Infra
Published by Universitas Kristen Petra Surabaya
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Core Subject : Science,
Computer Science & IT
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Articles 79 Documents
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Search results for , issue "Vol 10, No 2 (2022)" : 79 Documents clear
Analisis Sentimen Mahasiswa di Surabaya Terhadap Pelayanan Vaksinasi COVID-19 Menggunakan Beberapa Classifier Meliana Kusuma Pangkasidhi; Henry Novianus Palit; Andre Gunawan
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Indonesia is one of the countries that are currently struggling to deal with the COVID-19 virus pandemic by providing vaccination. The government is currently trying to persuade the public to do vaccination by maximizing COVID-19 vaccination services. In reality, vaccination services still have problems with some aspects. To see various insights on vaccination services that have been implemented, therefore a research was conducted in the field of sentiment analysis to analyze public opinion. In this research, classifiers that will be used are Naïve Bayes, Support Vector Machine (SVM), Random Forest, and Light Gradient Boosting Machine (LGBM) to perform text classification and their performances will be compared with evaluation metrics. There are two types of datasets used, namely questionnaire dataset and social media dataset. The questionnaire model will be tested using a social media dataset, while the social media model will use social media dataset that will be split. The testing results show that the model trained with the social media dataset produces better performance than the questionnaire model. Of these four classifiers, the best model for aspect and sentiment classification is Random Forest
Sistem Pakar untuk Mendiagnosa Kerusakan pada Sepeda Motor Kawasaki KLX 150 Menggunakan Metode Forward Chaining dan Certainty Factor Maria Eve Angeline; Djoni Haryadi Setiabudi; Kartika Gunadi
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

The Kawasaki KLX 150 is an all-road or dual sport motorcycle, which means it can be used on the road or off-road. Nowadayas dirt bike riders are not just crossers, ordinary people are starting to like dirt bikes to be used as daily vehicles. Dirt bikes have engines and various kinds of devices or parts that can be damaged or be problematic. The damage that often occurs on a dirt bike is considered trivial and not understood. Therefore, an expert system was created that can detect damage to the Kawasaki KLX 150 motorcycle, with the hope that this research can help replace the role of mechanics to diagnose damage based on the symptoms experienced. The expert system to diagnose damage to the Kawasaki KLX 150 will use the Forward Chaining method and the Certainty Factor method. The use of forward chaining method in this expert system is to collect facts obtained from users so that the system will produce conclusions. The use of Certainty Factor in this study is to provide a level of confidence from the results of system diagnosis in the form of metrics. From this expert system, it can provide information about the name of the damage, how to handle it and the level of confidence in the diagnosis. Application testing for the diagnosis of damage to the Kawasaki KLX 150, using real data with experts, resulted in a system accuracy of 90%. The application for the diagnosis of damage to the Kawasaki KLX 150 is also considered complete, accurate, appropriate and easy to use (user friendly) by the user.
Penerapan Artificial Neural Network dan Rule Based Classifier untuk Mengklasifikasikan Pendonor Darah Potensial pada Sistem Broadcast Pendonor Widya Arditanti; Andreas Handojo; Tanti Octavia
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

One of UTD PMI Surabaya’s task is to provide safe and quality blood when blood is needed in an emergency. The availability of blood at UTD PMI Surabaya can be erratic, because it depends on the number of donors that fluctuates and the storage time of blood is not long. Therefore, UTD PMI Surabaya needs a system to invite potential donors to meet blood needs when needed in an emergency, by minimizing blood wasted. The classification model and the creation of a recommendation system will produce a list containing donors who have been sorted by priority. Testing was carried out by dividing the data according to the conditions of the data collection environment (before the pandemic, during the pandemic and a combination of before and during the COVID-19 pandemic). The highest MRR value was obtained from the ANN model made from a combined data of 90% classification results using RBC and fake data. The accuracy value obtained from the model is 91.13% for training and 91.83% for testing. The resulting MRR value is 8.07 x 10-4 .
Implementasi Framework Scrum Pada Aplikasi Project Management PT. Rutan Berbasis Mobile William Evan Budiawan; Yulia Yulia; Anita Nathania Purbowo
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Project management is the process of planning and controlling an ongoing project. Nowadays, a lot of companies started to divert their current systems into digital formed systems, which can be accessed anywhere, everywhere. PT. Rutan as a company that prioritizes innovation, plans to digitalize the current existing project management system. Until now, PT. Rutan has no active management system that controls the performance of the company’s employees, and almost everything was done manually. In this research, a mobile application and a website was designed and developed to assist PT. Rutan in project management. The framework which will be implemented in the mobile application is the Scrum framework. The usage of the Scrum framework has been proven to improve task monitoring, task assignment, project scheduling, and evaluating the project. Based on tests conducted using a questionnaire at the Department of Information and Technology of PT. Rutan, the mobile application and website that have been developed have successfully helped in organizing, managing, and controlling project tasks. Overall, the mobile application and website created were also given a very good score by the Department of Information and Technology of PT. Rutan.
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.
Sistem Suggestion dengan Metode TOPSIS untuk Meningkatkan Keberhasilan Serious Game Greenlife Town Edward Manhattan Prasetio; Gregorius Satia Budhi; Hans Juwiantho
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Indonesia has a huge potential for renewable energy sources. However, this potential has not been fully utilized. One of the reasons is that the Indonesian people still do not understand renewable energy sources properly. Due to a lack of understanding and education, very few people are motivated to advance renewable energy sources in Indonesia. The solution to this problem is to create a platform for education to encourage. The platform is in the form of Serious Game. However, in practice, players often find it difficult to complete the game, so that the player's focus is more on solving problems than receiving information. Therefore, this thesis also utilizes the suggestion system to provide assistance options to players using the TOPSIS method. The test results show that the suggestion system is not able to increase the success of players in completing the game. The resulting effect is the opposite, where players increasingly have a worse final score even touching the number 88%. This failure is not solely caused by the method used, but also the way the method is implemented, the user convenience in playing, and the form of testing that is less flexible.
Sistem Registrasi Dan Identifikasi Wajah Untuk Akses Fasilitas Universitas Kristen Petra Dengan Kombinasi Facenet Dan Hierarchical Navigable Small Worlds August Berlin Tungka
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

The Identity Cards of students are used to access the facilities and participate in events of Petra Christian University. The problem which arises from these cards is the misuse by the irresponsible group. For this, the university needs the face identification system as the alternative. This thesis is meant to build a fast, accurate, and easy to use face identification system. The methods used to solve the problem is a combination of Facenet and Hierarchical Navigable Small Worlds (HNSW). Facenet is used to process the face into a 128-dimension vector which will be used for searching. HNSW is a k Nearest Neighbor search method which is used in a large-scale search. Using the method, the system takes an average time of 1 second to identify faces.
Penerapan Machine Learning dalam mendeteksi Fake Account pada Instagram Hendy Gunawan; Yulia Yulia; Gregorius Satia Budhi
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Instagram is the fourth most used social media in terms of the number of active users. Currently, many people are trying to increase the number of followers for other reasons such as gaining fame or wanting to be famous and trustworthy by people because they have a large number of followers. Therefore, people create fake accounts that are used to increase the number of their followers and also as a place to commit crimes such as fraud and cyberbullying. Such flexibility and spread of use has made Instagram a platform used for the proliferation of fake accounts. In this research, a website based application was designed that can detect accounts on Instagram whether they are fake or real accounts. The detection is carried out using machine learning with the Support Vector Machine, Naïve Bayes, Random Forest and Adaptive Boosting methods to detect fake or real accounts on Instagram. The method used is compared to its performance to find which method is the most appropriate in detecting fake or real accounts on Instagram. The use of k-fold cross validation is used to prevent overfitting in machine learning. Based on the tests that have been carried out, that AdaBoost can be used for account classification on Instagram with an accuracy of 92.5%, Random Forest 91.7%, Support Vector Machine 90.7% and Naïve Bayes 83.6%.
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.
Sistem Pakar Diagnosa Penyakit pada Anjing Menggunakan Metode Forward Chaining dan Certainty Factor Kevin Shaquille Limanuel; Leo Willyanto Santoso; Silvia Rostianingsih
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Dogs' diseases have different treatments which affect the owner on how to treat them. If the treatment given is not proper, even a minor disease could be fatal, which will be very detrimental to the dog owner and also the dog itself. The problem that the author wants to address is by utilizing a website that functions to diagnose common dog disease by using an expert system based on the forward chaining method and the certainty factor method to diagnose if there are any symptoms in dogs. Tests were also carried out on a collection of interview data and also from the expert in the form of disease symptoms and the program that was made are able to diagnose dog disease with the results of the method test being able to achieve an accuracy value of 80%.

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