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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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Aplikasi Sistem Pakar Penyakit Hewan Peliharaan Dengan Metode Forward Chaining Ocky Mahendra Alim; Leo Willyanto Santoso; Agustinus Noertjahyana
Jurnal Infra Vol 3, No 2 (2015)
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Abstract

With the lack of knowledge about the disease and treatment of animal diseases, animals do not get first aid, if we know the ilness no need to be panic and bring the animal to the doctor to perform further tests.Therefore, to help understand the illness and knowing first aid should be done when a pet suffering from the disease, it takes an application that can help detect what type of disease suffered and help necessary.From the above problems the authors designed a web-based expert system application that can overcome the above problems.
Sistem Informasi Simpan Pinjam Koperasi Citra Abadi Yuan Pratama; Lily Puspa Dewi; Alexander Setiawan
Jurnal Infra Vol 9, No 1 (2021)
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Abstract

Currently, the Citra Abadi savings and loan cooperative is still running all of its business processes manually. Cooperative recording is still done manually by means of books and paper. As a result of the system that is still manual, cooperative employees often find it difficult to find the required data quickly, for example when looking for member data, savings and loan data. Cooperative employees must find this data from the pile of cooperative records. It is also less effective and there is often missing data. Problems are also found when calculating reports in the cooperative, such as SHU reports, savings reports, and loan reports, the calculation process will take a very long time because you have to manually collect data which will be calculated one by one manually using a calculator. HTML 5 web-based information systems and PHP is built using Bootstrap framework and MySQL database. Features provided include: members data, saving and loan, remaining business results, promotion, balance, and survey data. The results obtained from the creation of this information system are that users can find out member data along with savings and loans, survey data, and receive reports needed by cooperative managers. From the results of the questionnaire, there are 100% on the assessment of good savings and loan features, 100% on the assessment of good application speed, and 66.7% on the overall assessment of the application is good.
Penerapan Konsep Marketplace pada Bisnis Laundry dengan menggunakan Framework Multiplatform Flutter Satriany Lauri; Djoni Haryadi Setiabudi; Agustinus Noertjahyana
Jurnal Infra Vol 8, No 2 (2020)
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Abstract

Over time, more and more laundry companies are threatened by their existence because of the lack of containers to accommodate laundry needs from customers and ultimately resulting in fewer and fewer customers, with a variety of reasons owned by customers such as the distance that does not allow, and customer ignorance of quality laundry that is automatically price and fulfillment. When viewed from the aspect of the customer, the user needs a system that can facilitate the user in meeting the need to wash, both in terms of time efficiency, and the affordability of the place. When viewed from the aspect of the laundry owner, the laundry owner needs a system that can be a bridge between the user and the owner, so that the laundry owner can enter a wider market. So when viewed from these two aspects, both parties need a concept or system that connects the two parties, namely the concept or marketplace system. The mobile laundry application with the marketplace concept aims to increase the user's time efficiency in meeting washing needs, and provide greater access to enter a broader market for laundry entrepreneurs. This application will be created using the Dart language using Visual Studio Code. This application helps customers to choose various kinds of laundry, with various categories of choices, customers also have features such as chat, notifications, customer profile, determine the date and time of delivery, choose the address of delivery and delivery, and features to view details of the order that is have been done. In addition this application also helps laundry owners to enter, edit, and delete categories that they have, and laundry owners also have a notification, chat, profile laundry owner, and features to update order status. The test results show that this application runs well on devices such as Android 8.0 (Oreo), and also the marketplace concept is proven to be applicable to the laundry business in terms of the system by having a web admin as a third party that managing the marketplace where the seller (the laundry) and the buyer (the customer) meet, and in terms of the convenience provided to the customer and laundry side.
Klasifikasi Pakaian Berdasarkan Gambar Menggunakan Metode YOLOv3 dan CNN Michael Christianto Wujaya; Leo Willyanto Santoso
Jurnal Infra Vol 9, No 1 (2021)
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Abstract

Clothing is one of the primary human needs and have many functions. It’s function not solely to cover and protect the wearer, but also to look stylish. Mass media, the internet, and social media are the main place for people to find inspiration to look fashionable. But sometimes it is difficult to determine the type of clothing so it will be easy to find. Therefore, a program that is able to differentiate and classify clothes will be a great help. The method we used are You Only Look Once to detect the clothing object from an image. The output of detection will be cropped and the result will be processed and classified by Convolutional Neural Network using ResNet50 architecture. In the training process of ResNet50, various things will be tuned which is learning rate, dropout, epoch, number of dense layer and its value, freezing layer, and data augmentation. Then program will search similar image using k-nearest neighbor.The result of this study will classify clothes in an image that is worn by the model in the image. The average accuracy obtained using the fine-tuned ResNet50 is 86.44%.
Klasifikasi Topik dan Analisa Sentimen Terhadap Kuesioner Umpan Balik Universitas Menggunakan Metode Long Short-Term Memory Doenny Auddy Lionovan; Leo Willyanto Santoso; Rolly Intan
Jurnal Infra Vol 8, No 2 (2020)
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Abstract

In evaluating and improving the quality of services and facilities, Petra Christian University (PCU) took feedback questionnaires given to students via online. At this time, reading the comments in the suggestion column is still read manually. So that it becomes less effective and efficient in analyzing sentiments and classifying topics for many comments. This study will apply word2vec and Long Short-Term Memory method to create a program that can help classify topics and sentiment analysis.Word2vec is used as a method to convert a word into a vector along with mapping the meaning of existing words. The parameter tested on word2vec are the number of iterations and windows size. Whereas the Long Short-Term Memory method is used to classify sentiment and topics. The parameter tested are the number of layers, the number of units, the batch size, and the percentage of dropout.The result of this study indicates that the word2vec method along with Long Short-Term Memory can be used to analyze sentiment and topic classification. The best configuration results obtained average accuracy in the implementation of the sentiment classification is 89,16 % and for implementation of the topic classification is 92,98 %.
Aplikasi Pengoptimalan Rute Pengiriman Barang pada PT.XYZ Fandy Ong; Alexander Setiawan; Nova Sepadyati
Jurnal Infra Vol 9, No 1 (2021)
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Abstract

The target company is a company engaged in the distribution of goods located in the city of Manado. Problems often faced by PT. XYZ, namely because of the large number of delivery destinations which resulted in the difficulty of arranging an effective travel sequence to distribute goods to customers according to the vehicle capacity and time desired by the customer. Therefore an information system is needed that is able to provide recommendations for a more effective delivery order based on each vehicle in the company. The system is implemented on website by using Django framework and MySQL Database. The process carried out by the system is by considering the constraints that the company has, namely in the form of maximum vehicle volume and office working hours, the system will provide recommendations for the order of delivery obtained through Google OR-Tools. The Genetic Algorithm method is also used as an alternative for later comparison. The end result of this program is a system that is able to answer the company's needs by providing recommendations for the order of delivery and information on detailed delivery for each vehicle. The test results obtained, namely Google OR-Tools got 17.04% better total distance results and 19.14% better total travel time results compared to the Genetic Algorithm method. Google OR-Tools also had 41.53% better total distance results and 41.46% better total trip time results than the company's current system. Meanwhile, the Genetic Algorithm method results in a total distance of 14.56% worse and a total trip time of 16.06% worse than Google OR-Tools. And when compared to the current company system, the Genetic Algorithm gets a total distance of 20.93% better and the total trip time result is 18.73% better than the current company system.
Identifikasi Varietas Koi Berdasarkan Gambar Menggunakan Zero Parameter Simple Linear Iterative Clustering dan Support Vector Machine Amadea Sapphira; Alexander Setiawan; Endang Setyati
Jurnal Infra Vol 8, No 2 (2020)
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Abstract

There’s currently 120 types of koi fish that has been bred around the world. The types of koi fish depends on the color patterns and shapes they have. There’s alot of patterns that has similarity between one type with another. For example, sanke and showa koi fish will look similar from a non-expert’s point of view, because both type has same color pattern, which is red, black and white. In actuality, sanke koi is dominantly red and white with slight black accent, while showa’s dominant color is red and black, with white accent.In this research, Zero Parameter Simple Linear Iterative Clustering (SLICO) method and Simple Linear Iterative Clustering (SLIC) will be tested and used to process the image segmentation process to eliminate the background of the image. Color Local Binary Pattern method is used to get the textures on images through the RGB, HSV, and grayscale colorspace. Support Vector Machine is used to identify types of koi fish. To test the SVM, two kind of kernel is used, which is linear kernel and Radial Basis Function (RBF) kernel.The results of this study are the program able to recognize types of koi from iamges. The test results show an accuracy of 36% in grayscale colorspace, 50% in RGB colorspace, and 48% in HSV colorspace.
Aplikasi Mobile Pengukuran Kwh Meter Rumah Tangga Menggunkan Arduino ESP8266 Edwin Surya Darmawan; Anita Nathania Purbowo; Resmana Lim
Jurnal Infra Vol 8, No 2 (2020)
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Abstract

Technology progress is so fast that everyone is using computers all the time. Making it easier for users to do something. Thus encouraging people to combine hardware and software to help in technological progress. Nowdays many things need electricity so that without electricity humans can experience great difficulties. Example smartphone is the most widely used technology and has become a very important technology in human life. But if the smartphone battry runs out, the smartphone needs to be recharged.For this reason, one solution to this problem is the existence of an pplication that can monitor the use of electrical energy in order to help humans to control electricity usage, such as a notification when excessive amounts of electricity are detected.The test results show that the factors that influence the accuracy of the photodiode Light Sensor are the light around the sensor and the blinking speed of the kWh meter. The more light around the photodiode Light Sensor, the smaller of sensitivity of the sensor and the faster of the Led on the kWh meter allows for missed sensor readings when sending data.
Implementasi Program Presensi Mahasiswa Dengan Menggunakan Face Recognition Richard Lawrence Thiosdor; Kartika Gunadi; Lily Puspa Dewi
Jurnal Infra Vol 9, No 1 (2021)
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Abstract

The problem of using a physical attendance list causes a cheat where the student does “fake attendance” by asking another students to sign the attendance list on his/her behalf. This problems are often found in college activities.Detection of student faces uses the Face Recognition library as a mean of validation in the attendance check process. Face recognition requires face images that have been preprocessed and uses the K-Nearest Neighbor model (KNN) or Support Vector Machine (SVM) to validate student faces in the attendance check process.Testing on 15 sample face images with 40 total face classes yields an average accuracy of 99%. Face Recognition cannot detect faces if the facial features are obstructed. This validation of student attendance successfully uses Face Recognition to minimize cheating in taking attendance.
Adaptive AI Pada Survival Horror Game Menggunakan Fuzzy Leonard Evan Widodo; Rolly Intan; Hans Juwiantho
Jurnal Infra Vol 8, No 2 (2020)
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Abstract

There are many methods used by developers to create artificial intelligence in their games. The method most often used by developers because of it’s flexibility is the scripting method. Scripting method is done by writing several rules in the source code in the form of if - then. The problem with this method is that the NPC’s artificial intelligence is easily exploited by gamer who have understood the pattern of the NPC’s behavior.Therefore the fuzzy logic is used to overcome these problems.The use of the fuzzy inference method is to make the AI to be adaptive to certain situation where depending on the situation the AI will give different decision making. In this case, Tsukamoto Fuzzy inference method is used in this design. In the method, all rules have their respective values which then will be calculated to look for the average score which then was used to determine which decision to make. Before constructing the fuzzy rules, determining the design of the game and the design of the map must be made first. After all are done, the appropriate fuzzy rules can be constructed.The results of the survey showed that the game that uses the Tsukamoto fuzzy inference method provides an adaptive decision according to the conditions at a moment in a game. Ninth of the players who played the game agreed that game A and game B had different decisions despite using the same AI as much as 77.2%, while those who said that AI was the same as much as 22.8%. From the results of this survey it can be said that the Tsukamoto fuzzy inference method can produce adaptive decisions based on the condition of the game at a certain moments.

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