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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 33 Documents
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Search results for , issue "Vol 9, No 1 (2021)" : 33 Documents clear
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.
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%.
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.
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.
Sistem Keamanan pada Kendaraan Bermotor Roda Dua dengan Arduino dan Android berbasis Suara Andreas Wijaya Kangnata; Agustinus Noertjahyana; Justinus Andjarwirawan
Jurnal Infra Vol 9, No 1 (2021)
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Abstract

Along with the development of the number of motorcycle that are growing very fast and also the development of information and communication technology which is also high has brought benefits to the development of human civilization progress in the world and in Indonesia, especially smartphone, but problems related to crime, especially against motorcycle theft can also be said to be very high, so it is necessary to design a security system on motorcycle with Android and Arduino that can be commanded by voice.The system is created using an Android smartphone as a voice command input receiver and Arduino as a tool that controls hardware based on commands. This system will send voice commands from Android that have been converted into text with the speech to text method and send commands according to the command input via a message that sent via SMSManager to the SIM800L V2.0 module that installed on the Arduino Uno. Message received on the SIM800L V2.0 module will be processed by Arduino Uno, so that Arduino Uno can control each module installed, such as the buzzer, the GPS (Global Positioning System) module, and the relay as a controller of the security system, contact system, and starter system on motorcycle.Based on the results of the tests that have been carried out, it shows that this system can work properly to control motorcycle with Android and Arduino in providing a security system for motorcycle which is also equipped with a location feature to determine the location of the vehicle.
Pelaporan Untuk Mengurangi Tindak Kriminal dan Non Kriminal Di Kota Mojokerto Dengan Menggunakan Metode Haversine dan Metode Multiple Criteria Utility Assessment Antonius Wibisono; Justinus Andjarwirawan; Rudy Adipranata
Jurnal Infra Vol 9, No 1 (2021)
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Abstract

Crime is a form of violation of the law, which always exists in society. Crime, crime, high unemployment rate that can lead to criminal action. For example, during the pandemic, there were several crimes committed, of course, for each city, it was different, Mojokerto City had a lot of criminal acts of drug use. Not only do criminal acts occur, non-criminal acts also occur, such as accidents, fires, etc. Based on the criminal and non-criminal problems that occur in society, it must have a media for reporting against criminals and non-criminals directly and quickly and can handling when many criminals are reported. So this program uses the Haversine method to see the shortest distance so that the shortest route can be created, and the Multiple Criteria Utility Assessment method to get a score for handling reporting at the same time. With this method, the reporter can see the shortest route and the estimated time between the user and the police, as well as the application with the next method when there are many reports. Then admin sees the existing weight so that he immediately takes care to reduce unwanted things. 
Electrocardiogram Biometrics Recognition Menggunakan Artificial Neural Network William Sim Jayapranata; Rolly Intan; Liliana Liliana
Jurnal Infra Vol 9, No 1 (2021)
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Abstract

Research on biometrics recognition has become popular in the last two decades. Electrocardiogram signal is one among many data that can be used in biometrics recognition purposes. It is unique for each individual, easy to obtain, and hard to forge made electrocardiogram well suited for biometrics recognition. In this research, an identifier will be made using the electrocardiogram signal of each individual.In this research, non-fiducial approach on MIT-BIH Arrhythmia Database from physionet with Artificial Neural Network as classifier was used. Non-sequential classifier offers lower computational complexity compared to sequential classifiers. Non-fiducial approach does not require feature extraction but a method of truncating the signal to each heartbeat is still required. Artificial Neural Network method uses neuron on each layer to classify digitalized electrocardiogram signal data.Experiment result using our method achieved 98.886% accuracy using MIT-BIH Arrhythmia Database. This research demonstrates Artificial Neural Network method capability as non-sequential classifier to identify electrocardiogram with non-fiducial approach.
Pengembangan Aplikasi DVR Driving dengan Fitur Remote Live Streaming dan Speedometer Berbasis Android Nico Gufron; Justinus Andjarwirawan; Agustinus Noertjahyana
Jurnal Infra Vol 9, No 1 (2021)
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On this era, motor vehicles already help people on daily basis, helping people to deliver goods, or transporting people. But on the way, there is a disaster waiting, either accidents on other vehicles or other accidents. Therefore, in this thesis will develop an application for DVR based on Android, equipped with additional features, such as GPS, Speedometer, and Live Streaming. In this application, users are able to record and take pictures with location and description about the videos and photos they take. Furthermore, live streaming feature added to help other users to join live streaming just entering channel name. Live streaming library helped by Agora Video Broadcasting library. The tests were carried out by adding applications to different smartphone devices 
Feature Selection pada Phishing Detection dengan Menggunakan Parallel Genetic Algorithm dan Ensemble Learning Alles Sandro Oktavio Gandadireja; Henry Novianus Palit; Alvin Nathaniel Tjondrowiguno
Jurnal Infra Vol 9, No 1 (2021)
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Abstract

Phishing sites could become a threat, which retrieves personal information without the user knowing this action. Every site has numerous records, which will be converted to features. Not all features extracted are relevant. Feature selection becomes the main topic of this case. This research uses Genetic Algorithm, using Ensemble Learning as fitness function. This process requires a lot of time, parallelization then used to improve the execution time of the system. The results show that with feature selection, an improvement could be obtained. Parallelization also helps improving execution time up to 2 times faster. Using this system, it is possible to improve the effectiveness of phishing detection.
Sistem Monitoring Solar Charge Controller Menggunakan Raspberry Pi 3 Secara Mobile Aldo Kris Barlianto; Djoni Haryadi Setiabudi; Resmana Lim
Jurnal Infra Vol 9, No 1 (2021)
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Abstract

In monitoring the charging of power source using solar panels, it is very important to find out the process of charging resources. Research about monitoring process has been carried out previously, but the monitoring process still depends on other software, and it cannot be done by mobile. In this research, the monitoring of solar charge controller will be carried out where user is no longer depends on additional applications / software and also can be done via PC / smartphone.The solar charge controller itself comes with a factory default software for data monitoring, but the usage of the application is very limited to the wiring system and also the monitoring process cannot be carried out by mobile. This research aims to be able to carry out the monitoring process by mobile using Raspberry Pi, so that users are no longer limited by wiring system and monitoring can be done in application which based on mobile web application, so that users can find out the monitoring process from a website on a desktop and also via smartphone.Through several test that has been held, it can be concluded that monitoring process can be done online using Raspberry Pi and modbus rs485 devices in mobile web application. The power parameters taken by the application are solar voltage, solar current, battery voltage, charge current, and load power. The application is also able to run / monitor several existing devices or more than one device in one application. During testing process, it is using 1 scc device and for other devices using a virtual device. The result of the percentage error from the measurement of the monitoring device is the reading of the solar voltage parameter data has an accuracy rate of 99.26% with an average 0.1 V selection, solar current has an accuracy rate of 95.6% with an average difference of 0.03, and the battery voltage has an accuracy 96.31 with an average difference of 0.18V.

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