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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 79 Documents
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Search results for , issue "Vol 10, No 2 (2022)" : 79 Documents clear
Analisis Sentimen Dari Keywords Yang Dimasukan Pengguna Di Twitter Indonesia Untuk Penunjang Pembelajaran Strategi Komunikasi Di Program Studi Ilmu Komunikasi Universitas Kristen Petra Dengan Metode Cnn-Bidirectional Lstm Andrianto Saputra Linardi Lie; Djoni Haryadi Setiabudi; Indar Sugiarto
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

To increase online media traffic, the first effort made by online media is to examine the trending phenomenon with the right marketing strategy. One of the methods that online media is used is a communication strategy that utilizes the sentiment analysis method. In reality, students of Communication Science Major at Petra Christian University are not optimally using sentiment analyst system because the sentiment analysis system for the Communication Studies Study Program (Netray) cannot be run by more than one student or is not used simultaneously and the price of the application is still not affordable if the students want to subscribe Netray. So a sentiment analysis system is needed to support the learning of the Communication Science Major at Petra Christian University. In previous related research, there was research that discussed the analysis of the #crowdfunding campaign on Twitter but there was not include sentiment analysis, there are only topological analysis, spatial analysis and others analysis. In addition, there are studies that use various deep learning methods of sentiment analysis, by researching CNN, DNN, RNN, Bi-Lstm, but none of them combine these methods. So it can be concluded that research will be made that analyzes sentiment analysis and combines deep learning methods. Sentiment analysis is the process of using text analytics to obtain various data sources from the internet and various social media platforms. Sentiment analysis can be utilized with artificial intelligence or with computing, because it is more efficient . Sentiment analysis can be complemented by methods from artificial intelligence systems, namely deep learning CNN-BILSTM. CNN-BILSTM is a combination of the two methods of CNN and bidirectional LSTM where CNN is the input layer and bidirectional LSTM is the layer that extracts features from the input. The dataset used in this application is retrieved from github by adopting the CC BY-NC (Common Creative Non Commercial) License. Data used in the deep learning model which contains a collection of Indonesian tweets containing neutral, positive, negative sentiments.From two testing this thesis using twitter as the online media. From the first test, 20 tweets were searched, the tweet contain "Shin tae yong” and yielded an accuracy of 30%. The second test was tested by 45 students of the Petra Christian University Communication Science Program at Petra Christian University Surabaya in the Q2.505 building where this application was tried and applied, after that the application was assessed with a satisfaction questionnaire which resulted in an average score of 4.01, so this application can meet the needs of the Petra Christian University Communication Science Program with the initial target of a satisfaction questionnaire of 3.75.
Algoritma Goal Programming untuk Driver Assignmentpada Simulasi Taksi Online Lienny Ferlinda; Andreas Handojo; Tanti Octavia
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Taxi is one of the most common means of public transportation. Assignment of drivers to passengers in online taxi can be done by of ering passenger orders to all drivers closest to the pick-up location. This method has high time ef iciency. However, this causes an increase in the cancellation rate because drivers don't have enough time to view order details, just as long as they accept orders. This can lead to a decrease in the level of passenger satisfaction and online taxi revenue. Therefore, other factors such as driver rating, driver order cancellation rate, number of orderscompleted by drivers are important to consider in the assignment process to produce an ef icient assignment. The process of assigning drivers and passengers will be carriedout using the Goal Programming method because this methodissuitable for problems in decision making that involve morethanone goal (multi-objectives). The results showed that Goal Programming resultedinthehighest total calculation time. In addition, the average waitingtime for passengers and pick-up distance are the lowest. TheHungarian Algorithm method has a faster calculationtimecompared to the Goal Programming method, however, thenumber of assignment is lower. In addition, the average waitingtime for passengers and their pick-up distances is higher. TheRandom Assignment method has the fastest calculation timeandthe highest assignment success rate. However, the averagewaiting time for passengers and the distance to pick themupisfarabove the two comparison methods. The addition of factors otherthan time and pick-up distance in a low percentage can af ect theaverage value of these factors for the better. But, the averagepick-up time and distance is increasing.
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.
Prediksi Kebutuhan Darah Menggunakan Metode ARIMA Dengan Mempertimbangkan Faktor Deterioration Gabriela Consuelo Heriyanto; Andreas Handojo; Tanti Octavia
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Blood has various uses that are very important for the human body. However, blood can only be donated in limited quantities because it can only be produced by humans. This blood donation activity is organized by the Blood Transfusion Unit (UTD), one of which is UTD PMI Surabaya. UTD PMI Surabaya also produces and stores blood products and distributes them to hospitals or directly to patients who need blood. Due to the uncertain amount of blood demand, UTD PMI Surabaya needs to make predictions in order to meet the blood needs. But blood has an expiry that also needs to be considered. Meanwhile, the blood demand prediction system still uses human estimates. Therefore, an information system is needed that can assist in predicting the need for blood by considering the expiration date of the blood. The application made in this research is a web application that can assist in making predictions using the ARIMA method. Then a calculation will be carried out by considering the deterioration of the blood to determine the need for blood in the next month. Based on the test results, the application is able to predict blood needs. The ARIMA model used to predict WB blood components is ARIMA (7,0,6) with a RMSE of 58,91. While the ARIMA model used to predict the TC blood component is ARIMA (5,0,6) with a RMSE of 272,46.
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.
Aplikasi Sistem Pengontrolan Turtle Tub Untuk Pemeliharaan Kura-Kura Red Belly Nelsoni Dengan Arduino Kevin Pramana Pongmasak; Silvia Rostianingsih; Indar Sugiarto
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Having turtles, especially Red Belly Nelsoni turtle is very common, but usually the owner don’t really know how to properly taking care of their turtles, according to the parameters needed in turtle maintenance. The problem that the author wants to solve is by utilizing Blynk application and Internet of Things tools that has a function to control, monitor and maintain all parameters that needed in turtle maintenance, so that the owner of the turtle can more easily taking care of the turtle in the turtle tub. The test was carried out by giving 2 turtle tubs containing Red Belly Nelsoni turtles to 2 volunteers who carried out the turtle care and maintenance in different ways. From the result of the test carried out, the application has been able to help the volunteers in taking care of the turtles according to the parameter aspects that needed in turtle maintenance.
Aplikasi Sentiment Analysis terhadap Trend Cryptocurrency pada Platform Twitter Menggunakan Library Textblob sebagai Alat Bantu Berinvestasi Ricky Chandra; Kartika Gunadi; Stephanus Antonius Ananda
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Along with the rapid development of information technology, many digital communication tools make it easier for people to access or share information. Twitter is one of the social media that has more than 1.3 billion users and more than 500 million tweets or tweets every day. The uniqueness of Twitter limits the number of writings to 280 characters, making Twitter a social media that contains sentiments about something. The cryptocurrency alone gets 4.1 million hashtag exposures per hour and has 2225 unique tweets per hour on the Twitter platform. The number of tweets related to Cryptocurrency causes investors to lose in terms of time because they have to manually assess a tweet. To overcome this, an effort that can be realized is to classify sentiments. One of the Natural Language Processing methods that have been developed for sentiment classification is TextBlob. In this thesis, an application will be made with sentiment analysis features using the Textblob Library, request tweets data using the Tweepy API, visualization of tweets data in the form of pie charts, tables, and word clouds, features that display the market price and history of cryptocurrency coins using the CoinGecko API and YFinance. as well as tweets from selected accounts. TextBlob Library testing is done by classifying results with 100 data that have been labeled by 2 examiners who have more than 1 year of experience investing in cryptocurrencies, the results obtained are 35% of the data have similarities between the results with the second tester, the application is tested with Tweets data request according to keywords, as well as application testing to display visualizations of Tweets data. A correlation test was conducted between the price change of cryptocurrency coins in 24 hours with the results of the classification of Tweet data and the Tweet volume of several coins. The conclusion that can be drawn from the correlation test is that when Tweet volume increases from the previous day, there will be a trend where the coin will increase or decrease. The results of the application web page where the application can display tweet data according to keywords and display visualizations, as well as display the price and history of the cryptocurrency market according to the available input.
Implementasi Text Summarization pada Review Aplikasi Super di Google Play Store Menggunakan Metode Maximum Marginal Relevance Dion Alexander Louis; Silvia Rostianingsih; Leo Willyanto Santoso
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Super App is an app for reseller agents who sell and distribute basic necessities in tier 2, 3 cities and rural Indonesia. The Super app has been downloaded by around 50,000 users on the Play Store. Various reviews or reviews have also been given by users who have downloaded the Super application. Whether we realize it or not, customer opinions / reviews given on Google play, a little or a lot, will have an influence on potential customers. Based on the problems that occur, this research will implement a text summarization program on Super App reviews with the implementation of the MMR and TF-IDF methods, so that from the large number of existing reviews, only a few important sentences can be extracted, so that the conclusion making process will become easier. The results of the research using the MMR method produced an average precision value of 40.4% in 3 trials, and with the highest precision value of 60.4% in the experiment using the parameter value = 0.7
Pengawasan Jalur Kapal dengan Automatic Identification System (AIS) berbasis Android Leonardo Yurion Tungribali; Justinus Andjarwirawan
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Indonesia, which is known as an archipelagic country, has a vast ocean that spans the country, that’s why Indonesia is known as a maritime country. With the vast sea, it becomes a wheel for economic turnover for Indonesia and internationally. Because Indonesia has 4 strategic points out of 10 points on international ship journeys, this makes Indonesian marine traffic very crowded and not a few ships from other countries cross Indonesian. When someone uses a ship to travel or deliver goods, there needs to be information about when the ship will arrive at its destination and the position of the ship when that person checks the information from the ship. Information about the ship consists of several important parts, the first is the estimated time of arrival (ETA), ETA is the time that ship will arrive at the port of destination, the second is the position of the vessel, the position of the vessel is in the form of latitude and longitude coordinates so that we can know the vessel's position on the map, and thirdly a ship specification that tells the ship type, ship size, MMSI, IMO, Call Sign, ship destination, and other important information. This information is quite difficult to find and also when looking for ETA the ship needs to go to the port and sometimes it is also not given in general at the port for certain vessels such as cargo and vessels other than passenger vessels. Therefore we need an application that can display ETA information, vessel position, and vessel specifications with the Android platform. The proposed application also has features that help users to do shipping or use transportation services using vessels. To obtain vessels information, an Automatic Identification System (AIS) is used which provides ship information and assists in calculating the vessel's ETA. ETA calculation and ship position prediction are assisted by the Haversine method. The results of the application have been tested with ETA information with test data, with the difference between ETA obtained from AIS and calculated by the system of ±20 minutes. The results of the application have been surveyed for the level of user satisfaction. The process of using the vessel is more helpful because of the features provided.
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.

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