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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 58 Documents
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Search results for , issue "Vol 8, No 1 (2020)" : 58 Documents clear
Pembuatan Aplikasi Pengiriman Berkas Reyner Wijoyo; Alexander Setiawan; Agustinus Noertjahyana
Jurnal Infra Vol 8, No 1 (2020)
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Abstract

The file sending process still done manually so the sender and recipient don’t know the location of the file and can’t track the file. furthermore, the total cost of sending file outside is still recorded manually so BAUK does not know the costs each unit spent.Because of that problem, file sending application based on website and android was created using PHP, MySql, and Java. Starts by creating a database to save all data and then create a website so that users can view and input data, then proceed with creating an android application using SOA and Rest so website database can be used on android and have the same data.This application can help the process of sending files by recording them automatically, tracking the files location, and see the total cost each unit.
Aplikasi Pelayanan Asisten Tutor Berbasis Android di Universitas Kristen Petra Dieni Lucky Prayapitesha; Andreas Handojo; Anita Nathania
Jurnal Infra Vol 8, No 1 (2020)
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Ethics Enrichment is a coaching program for new students during the first semester. This development program will divide new students into several small groups which led by Asisten Tutor (Astor). Besides making a development program, Asisten Tutor (Astor) must join another development program like intensive fellowship and Bible study groups. Each group has a mentor in order to lead the group. At this moment, every equippment that is used for new students, Asisten Tutor (Astor), and mentor is still printed in papers. With the numbers of new students, Asisten Tutor (Astor), and mentor that are increasingly rise every year; the usage of papers is such a waste and it is not simple. Therefore, web application dan mobile application are exist in order to help Asisten Tutor (Astor) and mentor; and also help new students to follow this development program effectively. This application is a technology-based because the usage of technology is a need for everyone in this era. The users of web application consist of administrator, asisten tutor observer, and students observer. Thus, the users of mobile application consist of mentor, Asisten Tutor (Astor), and new students. According to the test result, web application and mobile application is accesible. This application also helps management system of Ethics Enrichment service become well-organized.
Sistem Peminjaman Loker Otomatis Menggunakan QR Code dan Arduino William Winarto; Alexander Setiawan; Resmana Lim
Jurnal Infra Vol 8, No 1 (2020)
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Bank locker is a much needed facility, especially in public places. The lack of these bank lockers are very unsettling for those who carry a lot of luggage. From those many locker lending places in Indonesia, mostly still operated manually or using human labor. In the current era of globalization, automation is a major demand in all fields of work. Therefore, an automatic locker loan system is created from combining arduino WeMos D1 mini and android application. Android application is created using Android Studio, whereas the arduino is coded with Arduino IDE. The result of research showed that the integration of arduino and android application was successful in terms of automation and effectiveness.
Sistem Pembacaan Kode Pos yang Terintegrasi dengan Pencarian Alamat pada OpenStreetMap Adrian Evan; Leo Willyanto Santoso; Rudy Adipranata
Jurnal Infra Vol 8, No 1 (2020)
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Abstract

Postal code consist of sequential data which refers to a certain address in detail to their smallest form such as rural areas that are seperated by its own respective digits except the tiniest rurals. On the contrary, these pieces of data cannot be used conveniently on map database due to its thorough categorization and filtering process. Some of them may uncorrelated and may cause misunderstanding as of commonly existing digital maps merely processing longitude, latitude, also address data to city level simply using plain text.To solve the database system and postal data system disjoint problem, these two separate yet potentially powerful systems has to be integrated. With the continuous web development and securer HTTPS protocol into practice, also putting Progressive Web Apps into consideration, these core address finding functionsnamely geocoding, geolocation, also reverse geocoding majorly functions optimally without any need to concern users’ convenience on using this merged system at any sort.Test results conclude that this merged system has been significantly improving location finding accuracy, as long as the system works within the right hands. Basic knowledges of mapping system and GIS are inevitably mandatory to unleash existing maps capability of location finding into deeper levels. This will operates even optimally when the postal data system are wholefully implemented into the querying process, in addition to another smart features, such as shortest/fastest route tracking also traffic/riot detection into play.
Perangkat Lunak Logistik Kemanusiaan untuk Memantau Distribusi Bantuan Korban Bencana Alam Efraim Owen Gunawan; Djoni Haryadi Setiabudi
Jurnal Infra Vol 8, No 1 (2020)
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Abstract

Regional Warehouse of the Indonesian Red Cross Regional Gresik houses and handles the humanitarian logistical assistance process in East Java, Sulawesi and throughout Eastern Indonesia. Humanitarian logistical assistance is an emergency item that can be distributed when disaster strikes. Currently, in carrying out the logistics process applications are used that are embedded on the local machine. Now, the application is out to date and can not perform some functions according to the needs of the warehouse so that some processes are done manually using spreedsheet. Confirmation of receipt and delivery is also still often done via whatsapp messager so that errors often occur. Besides, giving track numbers are not unique, so that items are difficult to track. This causes the logistics process in the warehouse to be effective less, so we need an online software that can facilitate the logistics process. The Software developed is a web-based logistics assistance system. This system also adapted to the results of the analysis of existing applications with several additional features to adjust the needs of the warehouse. The web system was developed using serverside PHP programming language 7.12.13 with Laravel Framework 5.7 and also several libraries that support clienside css, javascript like bootstrap or jQuery. The final result of the software development contains movement of goods that occur in the warehouse, such as input of goods entering and leaving, as well as by renewal the tracking number and assigning the tracking number automatically to the each of relief item.
Klasifikasi Artikel Berita Bahasa Indonesia Dengan Naive Bayes Classifier Anthony Setiawan; Leo Willyanto Santoso; Rudy Adipranata
Jurnal Infra Vol 8, No 1 (2020)
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Human access to latest news now becoming more easier and much more, caused by advanced technological development in latest years. But, the article categorization is still manually inserted by the writer, so sometimes by human error, some mistake can be happening, like inserting wrong category or sometimes the writer purposely insert wrong category just because that category is so popular just to boost his viewer count. That’s why there is an application in the form of website to automatically categorizing the article that fit mostly to their its category.This application is using N-Gram feature and Naïve Bayes Classifier method to classifying news content. N-Gram feature is a feature that group words based on the amount of N, like unigram or bigram. Naïve Bayes Classifier is a method that using probability to solve some problem.According to the test using Naïve Bayes Classifier, in dataset training and test with ratio of 50 : 50, at unigram section the correct accuracy result are 0.901,  and the bigram result are 0.508. In dataset ratio of 60 : 40, at unigram section the correct accuracy result are 0.904, and the bigram result are 0.498. In dataset ratio of 70 : 30, at unigram section the correct accuracy result are 0.947, and the bigram result are 0.519. In dataset ratio of 80 : 20, at unigram section the correct accuracy result are 0.887, and the bigram result are 0.507. So, the conclusion is dataset training and test with ratio of 70 : 30 yield highest accuracy, in unigram (0.947) and also bigram (0.519).
Pengenalan Jenis Bunga Anggrek Menggunakan Metode Color Local Binary Pattern dan Support Vector Machine Debby Meliani Prayogo; Kartika Gunadi; Endang Setyati
Jurnal Infra Vol 8, No 1 (2020)
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Abstract

Orchid flowers are the flowering plants with the most types or species. One of them is the moon orchid flower which is one of the three national flowers in Indonesia. Orchid flowers can be found in city parks and many tourist attractions because of its beauty. However, people will certainly have difficulty in recognizing the type of orchid. Therefore, a program is made to help people in identifying the types of orchids that are around. Orchid flower recognition has already been researched to recognize the texture of its flower. However, this study uses 25 species of orchids that is from Indonesia to be recognized.You Only Look Once (YOLO) method is used for detecting flower objects in the image. Before classifying the orchid species, the background image need to be removed using Image Segmentation. The Color Local Binary Pattern descriptor is used to get the texture of the image through several colorspaces, namely grayscale, RGB, HSI, YIQ, and oRGB. Support Vector Machine is then used to recognize the type of orchid.The result of this program can recognize the species of orchids in the picture. From the test results using the researcher’s dataset show an accuracy of 30.7% using color space grayscale, 37% using color space RGB, 34.6% using color space HSI, 41% using color space YIQ, and 40.2% using color space oRGB in recognizing the species of orchid.
Implementasi Convolutional Neural Network untuk Mengetahui Buah Tomat yang Matang pada Pohon Tomat Menggunakan Perangkat Android Timothy Christian Yunanto; Kartika Gunadi; Anita Nathania Purbowo
Jurnal Infra Vol 8, No 1 (2020)
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Abstract

The development of instant era makes people want something that fast and efficient. As we know, picking ripe tomatoes on the tree requires a long time if done by humans. To solve these problems, automatic robots are used that can replace the role of humans. To get a successful automated robot requires the creation of efficient algorithm function (program). The Program can be run on an Android Device. We use Blob Detection method on Computer Vision, and the result will be processed by the Convolutional Neural Network method. CNN method requires to determine whether the object is ripe tomatoes or other objects. Blob Detection is used to detect tomato objects based on previously obtained masks. Before doing the training, it is necessary to make a model that contains convolutional layer, max polling layer, flatten layer, dropout layer, and dense layer. The test is carried out with a scenario study and several cases such as bunched tomatoes, scattered tomatoes, tomatoes whose masks are not oval, and so on. The results show that the results of CNN are very dependent on the results of Blob Detection because the input from CNN is from the result of Blob Detection. If Blob Detection fails to get the tomato object, CNN will not run properly. The results show that Blob Detection will fail to detect the tomato object if the tomato is blocked by another object which causes the mask shape of the object to be chaotic. The test results from CNN also showed an accuracy value of training of 96% and testing accuracy of 93%.
Penggabungan Algoritma Markov Chain Monte Carlo dan Metode Statistik pada Named Entity Recognition Lintas Bahasa Suku di Indonesia untuk Pembelajaran Alkitab Vania Putri Minarso; Henry Novianus Palit; Justinus Andjarwirawan
Jurnal Infra Vol 8, No 1 (2020)
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Abstract

Bible is an important bilingual or monolingual text, making it a resource for training such as translation, named entity analysis, and transliteration. Named entity is a realworld object such as people, location, organization, product, et cetera, that can be symbolized with an exact name. The objective of the experiment is to help people learning the bible in understanding important names in the bible either in Indonesian or other local language in Indonesia. This can also help missionaries doing evangelism to quickly understand named entity in the local language of the place they are in. In this process, they may be a gap exists between the named entity in Indonesian and the local language.To solve this issue, designed an application that integrate Markov Chain Monte Carlo algorithm that wrapped inside efmaral tool with statistical method wrapped inside giza++ tool, and IBM Model 2 reparameterization wrapped inside fast align tool. From the product of all the tools, which is correlation between every word in Indonesian with the word in the local language, the result will be decided by finding the right consensus to find the correct named entity in the local language. The named entity will be chosen based on the strong numbering from the original language.Based on the result of the experiment, integration of efmaral, giza++, and fast align tools yields better accuracy than efmaral tool alone. Efmaral tool has the accuracy around 0,07 to 0,66. Giza++ tool has the accuracy around 0,47 to 0,90. The integrated tools (efmaral, giza++, and fast align) has the accuracy around 0,36 to 0,87.
Pengenalan Gambar Tempat Wisata Dengan Deep Local Feature Dan Support Vector Machine Angelika Dibijo; Agustinus Noertjahyana; Alvin Nathaniel Tjondrowiguno
Jurnal Infra Vol 8, No 1 (2020)
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Abstract

Saving moment at a place usually done with photos. However, due to the large number of photos, organizing photos becomes difficult. A tourist may not know the name of the tourist spot he visited, do not have time to name the photo or forget the name of the place the photo was taken. Manually searching for places names through photos will take a long time.This research will conduct a trial with the implementation of the Deep Local Feature (DELF) method and Support Vector Machine (SVM) to recognize photos of tourist attractions automatically. The DELF method is an effective method for capturing image features, especially place pictures. After capturing image features, the images will be grouped based on features with SVM.The test is carried out to get the value of the parameter taking features with DELF and classification with SVM so that the recognition of tourist attractions has a high level of accuracy. For 153 image classes, DELF is performed with an image threshold of 50 and a max feature of 1000. While the classification uses SVM with kernel rbf with cost 10 and gamma 0.01. By using the DELF and SVM obtained accuracy with a test data of 0.6178.

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