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INDONESIA
Jurnal Infra
Published by Universitas Kristen Petra Surabaya
ISSN : -     EISSN : -     DOI : -
Core Subject : Science,
Computer Science & IT
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Articles 1,326 Documents
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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%.
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.
Aplikasi Moblie Learning untuk Meningkatkan Interaksi Pembelajaran dalam Mendukung Penyerapan Materi Pembinaan UMKM oleh LPPM Universitas Kristen Petra dengan Menerapkan Model Learning Group Cynthia Wijaya; Djoni Haryadi Setiabudi; Justinus Andjarwirawan
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

 Synchronous learning provided by LPPM in learning events is often limited, and makes MSME participants have to understand and develop the material that has been delivered individually after receiving the lesson. This makes the lack of interaction in learning, and reduces the interest and attention of MSMEs to improve learning from the material obtained, especially when they find difficulties in learning. This can affect the level of absorption of material by MSMEs to be not optimal. Several previous studies using mobile learning still have weaknesses, namely learning is still more focused on individual learning so there is no interaction in the learning process through mobile learning.To overcome this problem, in this study a mobile learning application was designed with a learning group model that has collaborative features, such as the task forum feature where MSMEs can choose the question to be worked on and then give each other comments on whether the answers in each question are correct, problem box to help each other provide solutions from a lack of understanding of the material, discussion forums to discuss things that have not been discussed in the material, glossary, chat with tutors and mobile push notification support to encourage MSMEs to be more active in mobile learning.The results of this study based on questionnaires and activity calculations, it can be concluded that the mobile learning application with the learning group model helps MSMEs to understand or increase the absorption of material in training. In addition, it also makes MSMEs active in participating in the training, thus indirectly helping better absorption of material.
Sistem Otomasi Rute Order Picking Pada Gudang dengan Metode Simulated Annealing Stienley Nagata Cahyady; Andreas Handojo; Tanti Octavia
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Order Picking is a process to make a selection from products and picking them up from the place that products are stored and then sort the products out to fulfill the customer orders. Order picking process is the most expensive activity in the warehouse. The reason is order picking needs a lot of workforce and if order picking done manually it will cost as much as 55 % of the total cost of the warehouse. That’s why order picking is the correct part to be optimize to make warehouse become more effective and efficient. In this thesis, a web based application designed to solve all the problems above, which includes showing the shortest route to be pick for orders picking with simulated annealing method. Other than that, the application will be included with a hardware named RFID reader which can detect product placement and pickup from the shelf. The result of this thesis showed that simulated annealing algorithm able to reduce the range that are needed to order picking as much as 51.57058354 % for 100 data, 35.56569879 % for 500 data and 28.18222784% for 1000 data with fixed parameters. For the RFID reader it have the accuracy of 40% for reading products on the shelf. This is because the signals from tags clashing with each other which make the reader unable to read all of them.
Aspect-Based Sentiment Analysis pada Ulasan ECommerce dengan Metode Support Vector Machine untuk Mendapatkan Informasi Sentimen dari Beberapa Aspek Hansen Gunawan Sulistio; Andreas Handojo
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

In this era of globalization, all people's activities are starting to use technology to facilitate their daily activities. One of the most impactful forms of digitization activities is online buying and selling activities such as the use of the Tokopedia and Shopee platforms. The existence of a review feature on online buying and selling places (e-commerce) is one of the factors supporting the increase in people's online transactions. The number of people who have started to implement online buying and selling activities in their daily lives has resulted in an increase in the number of reviews on e-commerce.The large number of reviews makes it difficult for potential buyers to review a product to be purchased. The factors that determine the shopping experience of each individual are different so that the reviews and ratings given by each individual on a product or store vary. This affects the average rating of a product or store so that the average rating on a product does not necessarily represent the quality of the product. To overcome this problem, the author makes a system where prospective buyers and sellers will be facilitated to assess an aspect of a product. The system created by the author shows several aspects that are crucial for buyers and sellers in reading a review, such as general aspects, accuracy, quality, service, delivery, packaging, and price using the Support Vector Machine method. In these aspects, the system created will show sentiments on reviews that have been written by buyers such as positive, negative, or neutral sentiments. In addition to showing the sentiments of aspects of a product, this system also shows which aspects affect the product rating the most, the aspects that are most frequently discussed, what aspects are most rated positively and negatively.The results of the thesis show that the aspect that is often discussed is the quality aspect. General aspects, accuracy, quality, service, delivery, and packaging affect the rating value on a product rating while the price aspect does not affect a product rating. Compared to the Shopee platform, there are more positive reviews written on Tokopedia than reviews on Shopee.

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