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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
Prediksi Peringkat Mingguan Lagu Pada Spotify Amerika Serikat Menggunakan Multiple Charts Dataset Dengan Berbagai Metode Christianto Imanuel Aryanto; Henry Novianus Palit; Andre Gunawan
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

In 2020, the majority of the music industry's revenue, 62.1%, came from streaming music. As a result, many music business parties are striving for a hit song, particularly on Spotify US chart. However, this is difficult to achieve because nowadays, a song's performance is determined by its performance on various music charts, not by its quality. Due to that, a study in the field of hit song science will be conducted to forecast weekly song ranking on Spotify US using data from Spotify, Shazam, Airplay, and TikTok charts. Multipler linear regression, polynomial regression, gradient boosting tree, and random forest are the methods used in this study to create models, and each model will be compared using adjusted r-squared and mean absolute error (MAE) as evaluation metrics. Random forest produced the best model, with adjusted r-squared and MAE values of 93.133% and 11.687, respectively. The usage of music attribute had a negative impact on model performance. Shazam chart, on the other hand, has been shown to have a positive impact on model performance. Meanwhile, neither the Airplay nor the TikTok charts have a definite positive or negative impact. However, both have been shown to have a very weak relation with model performance. Overall, the dataset combination of Spotify, Shazam, Airplay, and TikTok chart produced the best model in this study.
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.
Aplikasi Sistem Informasi Praktikum pada Program Studi Informatika Universitas Kristen Petra Berbasis Website Cynthia Budiono; Lily Puspa Dewi; Alexander Setiawan
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Presently, Petra Christian University informatics study program use SAOCP for laboratory activities problems. But there are drawbacks that can be minimized. Recruitment, assessments, attendance using Microsoft Excel for every data collection carried out. The person in charge of the practicum schedule often experiences confusion in setting the schedule. The current system also reads the NRP by using the old NRP format which is start with M alphabet. Based on these problems, it is necessary to have an application that can answer problems in the informatics study program. This system is created using PHP with the CodeIgniter 3 framework as the main basis, and SQL for the database. In this information system, the user has six different types of access right, namely admin, lecturer, head of the laboratory, permanent assistant, lecturer assistant, and student. The final result of this application is the integration of information such as vacancies, ratings, attendance, and reports. Based on the results of the existing questionnaire, 100% of the correspondents considered that the features made in this application were sufficient in accordance with the needs of the company.
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%.
Aplikasi Monitoring Pada Tanaman Aglaonema menggunakan IOT Liyyin Putra Arif Wicaksana; Alexander Setiawan; Resmana Lim
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Aglaonema plants are quite difficult to cultivate because the keeper must know what Aglaonema plants need in order to thrive and be beautiful. Aglaonema plants have high sensitivity to roots and stems, as well as leaves. Aglaonema plants require a soil moisture level that is not too moist and not too dry, a soil pH of 6-7, and a placement that is not exposed to direct sunlight. The solution is made by utilizing advanced technology which makes an application that can monitor and maintain the fertility of soil conditions on the Aglaonema plant on a mobile basis and use IOT as a sensor tool to retrieve data which will later be sent to the android application. The trial was carried out by using 2 aglaonema plants to be treated simultaneously. Plant 1 will be treated by volunteers who have just touched Aglaonema so that it provides care like other plants in general, plant 2 will be treated using a monitoring application, trials are also carried out by adjusting the data obtained from aglaonema experts. From the test results, it was found that the effectiveness of the application in monitoring Aglaonema plants has an accuracy rate of 100%.
Order Fulfillment pada Taksi Online dengan Mempertimbangkan Prioritas Penumpang Menggunakan Metode Recency, Frequency dan Monetary Viona Angelica; Andreas Handojo; Tanti Octavia
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Along with the development of technology in Indonesia, online taxi companies are one of the fields that are starting to be developed. Just like other companies, online taxi companies are looking for profits, to achieve it, they need to maintain good relations with their passengers. That can be achieved by improving service to loyal passengers. In this study, factors will be applied to improve service to loyal passengers and drivers such as rating, number of trips, driver’s RFM score and passenger’s RFM score. The method used to segment drivers and passengers is RFM prioritization and Filtered RFM prioritization. The method used to pair the driver and passengers is the Hungarian method. This study shows that by adding additional factors such as driver and passenger RFM scores, driver ratings, and the number of trip drivers accompanied by a passenger pick-up time limit, don’t change the assign time, waiting time, and pickup time of passenger but can prioritize passengers and drivers according to those factors. In addition, internet speed also has a huge influence on website-based order fulfillment simulations.
Aplikasi Self Management untuk Mencatat Jadwal Kegiatan Dengan Speech to Text Menggunakan Google API Berbasis Android Kevin Angka Wijaya; Justinus Andjarwirawan; Lily Puspa Dewi
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Self Management is a person's ability to control himself against an action. But there are still many people who underestimate this, especially in terms of scheduling activities. People tend to only rely on memory and organize activities incorrectly. This makes people think a lot and tend to forget things. Thus, a scheduler app can be a perfect solution for busy people. This paper was made to create an application for scheduling using speech to text. The features of the application are calendars, to-do lists, notes, and speech to text. Speech to text using the Google Speech API. Calendar connects directly to Google Calendar using the Google Calendar API. Other features are stored in a local database in the form of SQLite. The application was tested by measuring the speed of making a schedule using a stopwatch. The result is that the schedule can be made in 10.426 seconds using speech to text. By using the Google Speech API in making the schedule, the accuracy obtained reaches 96.45%.
Aplikasi Analisa Sentimen Bilingual dan Emoji pada Komentar Media Sosial Instagram Menggunakan Metode Support Vector Machine Satria Adi Nugraha; Henry Novianus Palit; Hans Juwiantho
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Indonesia is ranked 4th as the most Instagram user in the world. This makes business people triggered to promote their products and services to content creators to make reviews and upload them on Instagram. Business people need to evaluate uploads to assess whether the promotions carried out get a positive or negative response from netizens. Evaluation can be done by checking the comments column. Instagram comments not only contain comments in Indonesian but in English along with emojis. However, checking manually will certainly take a lot of time. Therefore, it is necessary to build an application system that can detect bilingual sentiments and emojis in Instagram comments. This system was built using the Support Vector Machine method to classify language, Indonesian sentiment, and English sentiment and then evaluated using the accuracy value. The data used is a sample of uploaded comments in the form of posts, reels, and IGTV. The combination of preprocessing cleansing, normalization, stopwords removal, and stemming as well as parameter tuning using GridSearchCV was also tested to find the best model. The model is divided into language classification models with Indonesia, Inggris, and Campuran labels, Indonesian sentiment classifications, and English sentiment classifications with positive, neutral, and negative labels. The best accuracy obtained by the model for language classification, Indonesian sentiment, and English sentiment is 88.77%, 73.10%, and 71.56%, respectively. In addition, emojis need to be analyzed because the model that analyzes emojis has 3.875% better accuracy than the model that ignores emoji.
Aplikasi Sistem Pendukung Keputusan Perekrutan Karywan berdasarkan Hasil Tes Rekrutmen dengan Metode Fuzzy AHP dan Profile Matching pada Konsultan Manajemen Sumberdaya Manusia CV.X Josia Christian; Silvia Rostianingsih; Yulia Yulia
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

CV X is a human resource management consulting company serving personnel management services such as recruitment, assessment, making company policies, and making employment agreements. So far, all business processes are still done manually including the employee recruitment process. Based on the existing problems, this research will create a Decision Support System for Employee Recruitment based on Recruitment Test Results with Fuzzy AHP and Profile Matching Methods. The system is expected to optimize the efficiency of the recruitment process at CV X Human Resource Management Consultant. The results show that the system can help calculate candidate rankings with an accuracy of 83.975% when compared to manual ranking results. In addition, the system can also help reduce the influence of assessor subjectivity on ranking results.
Game RPG Berbasis Android untuk Mendorong Pengguna Berolahraga Wilson Mark; Henry Novianus Palit; Djoni Haryadi Setiabudi
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

With the lockdown period due to Covid-19, maintaining stamina and body health is a priority. People are advised to reduce activities outside the home and work from home. Working from home is often done behind a desk, and after work people do activities to relieve boredom such as watching television, playing games, and other sedentary activities that cause them to be unhealthy. Playing games on a smartphone is becoming more popular because they are easily accessible and only require a smartphone that has many features already on it. This thesis research aims to create a game application on a smartphone to overcome this problem. This RPG game application, is hoped to increase people's interest in exercising by playing on a smartphone that detects motion using the accelerometer sensor and calculates calorie burned using the MET formula. The results of testing the game show that 40% of respondents are more interested in exercising. In addition, the calculation of calories is quite accurate compared to other tools. And it is also proven that this game can meet the recommended daily exercise.

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