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INDONESIA
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Published by Universitas Brawijaya
ISSN : -     EISSN : -     DOI : -
Core Subject : Science, Education, Engineering,
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering
Jurnal Pengembangan Teknlogi Informasi dan Ilmu Komputer (J-PTIIK) Universitas Brawijaya merupakan jurnal keilmuan dibidang komputer yang memuat tulisan ilmiah hasil dari penelitian mahasiswa-mahasiswa Fakultas Ilmu Komputer Universitas Brawijaya. Jurnal ini diharapkan dapat mengembangkan penelitian dan memberikan kontribusi yang berarti untuk meningkatkan sumber daya penelitian dalam Teknologi Informasi dan Ilmu Komputer.
Arjuna Subject : -
Articles 6,972 Documents
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Pengembangan Sistem Informasi Penjualan Sayuran berbasis Web dengan menggunakan Metode Waterfall Studi Kasus : (Agro Techno Park Universitas Brawijaya) Riski Ida Agustiyan; Imam Cholissodin; Arief Andy Soebroto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 12 (2021): Desember 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Agro Techno Park is a place for the development of agricultural products that are managed for agricultural entrepreneurship and a place for agricultural technology services. the purpose of the Agro Techno Park is as a center for the application of technology in agriculture, fisheries, and animal husbandry. One example of an Agro Techno Park located in East Java is owned by Brawijaya University which is located in Cangar and Jatikerto. In the marketing of Agro Techno Park products, UB still uses the manual method, namely by marketing products through the social network WhatsApp. By using this method, Agro Techo Park UB faces certain difficulties when receiving orders from customers. Because customers sometimes order products at the time of delivery, Agro Techno Park UB will come back again to take orders that have been added. In this case, of course, it takes a lot of time to make buying and selling transactions. People don't even know that Agro Tecno Park UB's vegetable products can be sold with quality vegetables. To solve this problem, the authors developed a Vegetable Sales Information System in Agro Techno Park UB. This system was developed to facilitate buying and selling transactions at Agro Techno Park UB and to expand the marketing segment of the vegetable products being sold. System development is carried out on a-based website and using the model waterfall using theprogramming PHP language on the Laravel framework. The system will be tested using the method white box, black box, integration testing, validation testing, and compatibility testing.
Analisis Sentimen Ulasan Kedai Kopi Menggunakan Metode Naive Bayes dengan Seleksi Fitur Algoritme Genetika Naziha Azhar; Putra Pandu Adikara; Sigit Adinugroho
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 13 (2020): Publikasi Khusus Tahun 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Artikel dipublikasikan di JTIIK
Pengelompokan Ulasan Produk HP pada Marketplace Tokopedia menggunakan Metode Semi Supervised K-Means Rizky Ardiawan; Yuita Arum Sari; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 1 (2022): Januari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The internet has grown rapidly in accordance with the changing times. It also changes shopping behavior that was originally face to face now can be done online. Cell phones or smartphones are the most sought after items today. To buy these items online, there are many marketplaces available in Indonesia, such as Tokopedia. A product review is rated as the main factor for consumers to buy goods. To perform analysis on reviews, a method is needed that can classify and group reviews into existing categories. By combining the two understandings between Supervised and unsupervised, one can create a grouping method based on training data consisting of labeled data. The method that is suitable for this case is the Semi Supervised K-Means method. From the results of this study, it was found that in 4 different experiments, the evaluation of the cluster value using Silhouette was 0.013647 which was the largest value using the Semi Supervised K-Means method. Which is very small, namely 3 clusters. However, the results of clustering the clusters produced in the same method proved to be better than the K-Means method in general with the review data according to the original label.
Klasifikasi Teks Pengaduan Sambat Online Menggunakan Support Vector Machine (SVM) Nanda Samsu Dhuha; Fitra Abdurrachman Bachtiar; Ahmad Afif Supianto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 13 (2020): Publikasi Khusus Tahun 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Artikel dipublikasikan di SENTRIN 2020
Perancangan User Experience Aplikasi Media Pembelajaran Interaktif Berbasis Mobile Pada Materi Geometri Dimensi Tiga Dengan Metode Human Centered Design Iqbal Setya Nurfimansyah; Komang Candra Brata; Ahmad Afif Supianto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 13 (2021): Publikasi Khusus Tahun 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Geometry has sub-sections, namely three dimensions which talk about spatial shapes. Building space contains three important elements, namely length, width, and height so that it is said to be a three-dimensional shape. Three dimensional learning, must start with real objects with three dimensions, then it can be implemented through images that seem to look like two dimensional shapes. To realize three-dimensional images at this time, it can be done with the help of technology, namely mobile applications to make it easier in the abstraction process. This study aims to simplify the process of building abstraction involving user experience as a reference in designing solution designs made for high school, vocational, and MA students to assist in the learning process. The Human Centered Design method is used to place potential users in the main center of research by providing a good user experience. There are four main stages that are carried out in the development of research. The first analysis is in the form of user analysis then persona to emphaty map. The two identifications are in the form of features and user tasks. The three implementations are wireframe design, screenflow and prototype. The fourth evaluation is in the form of usability test and system usability scale test. Derived from the testing process carried out resulted in an efficiency of 0.181 and 100% effectiveness as well as 64.17 for user satisfaction which means that it is considered sufficient. Therefore, it can be concluded that the design of the solution that has been given is quite successful in solving the problem even though it has satisfaction, there are several shortcomings.
Alat Pendeteksi Uang untuk Tunanetra menggunakan Metode Histogram of Oriented Gradients dan K-Nearest Neighbor Nico Dian Nugraha; Fitri Utaminingrum; Hurriyatul Fitriyah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 4 (2021): April 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Banknotes that distributed by scammers would causes restlessness in society, including blind people. With impairment vision, blind people would hard to distinguish between genuine and fake money. From that problem there would be a research about nominal and authenticity detection system for blind people. The detection system consists of camera as a sensor device to detect picture from the banknote, followed by ultraviolet lamp to tell about the genuine banknote, and speaker as the output from this system. Output would generate voice as the nominations and tell if it is genuine or fake banknote. Code program on this system were written in Pyhton language with Raspberry Pi hardware, Webcam sensor camera, and ultraviolet lamp. Detecting banknotes would use Histogram of Oriented Gradients method and using K-Nearest Neighbour method to classify banknote. Around 3370 data training were used to detect about authenticity of the banknotes and the detections were tried for 56 times. implementation of K-Nearest Neighbor method using k=3 obtained an accuracy result of 98.21% with an average compute time of 3608 ms.
Klasifikasi Review Produk Kecantikan Pada Aplikasi Sociolla Menggunakan Algoritme Modified K-Nearest Neighbor (MK-NN) dengan Pembobotan BM25 Alfita Nuriza; Indriati Indriati; Nurul Hidayat
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 10 (2020): Oktober 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Beauty products have become one of the many things that cannot be separated from women because of the demands to look beautiful and attractive. These products offer their advantages, there are many beauty products on the market, ranging from skin care and cosmetics from various types and brands. These products have advantages, but not all products suitable for the users needs. This is something that consumers must pay attention to before buying. Other than that, the number of beauty products that are closely related to opinions about certain products in accordance with the parameters given by consumers such as strengths, weaknesses, quality and other parameters, this is what is used as a reference. One electronic trading platform that provides beauty products is Sociolla. Not only sell beauty products, on this platform there are also reviews from consumers. Reading all these reviews in full will take up a lot of time, whereas if you only read a little, the resulting evaluation will be biased. To overcome these problems the classification of the existing review will be classified into 2 classes, namely positive and negative classes. In this study the authors used the Modified K-Nearest Neighbor (MK-NN) algorithm with BM25 as a weighting. The data used were 500 data which were divided into two, positive and negative. From the evaluation results of the test with 5-fold cross validation, the highest average values ​​of accuracy, precision, recall, and f-measure were 51.00%, 50.90%, 52.61%, and 51.70% at the time k = 11.
Rancang Bangun Sistem Deteksi Gestur Tangan untuk Pengendalian Slide Presentasi menggunakan Algoritme You Only Look Once Versi 3 Muhammad Rafi Zaman; Fitri Utaminingrum
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 8 (2021): Agustus 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Presentations have become part of the delivery of information that is very often used. However, in controlling the presentation, they still use a third device to control the presentation, such as the keyboard, mouse, and pointer. This is considered to be less effective like a keyboard and mouse because the presenter has to make a presentation by sitting in front of the screen so that it interferes with the presenter's focus and does not look natural like a pointer. Another solution that can be used as a presentation controller is human hand gestures. This study aims to create a hand gesture detection and recognition system to control presentation applications. This system will issue an output in the form of a simulated keyboard and mouse pressure. To be able to recognize hand gestures, the system uses one of the deep learning methods, namely You Only Look Once version 3 with an NVIDIA Jetson Nano device as a test. This system is designed to detect hand gestures within a distance of 1 to 2.5 meters. The training data used in this system are 7080 images of training data with 8 classes of hand gestures and the training data is taken with a predetermined distance. The results of system testing based on distance produce an average accuracy value of 91.18%. And the average computation time is 0.5988 seconds.
Klasifikasi Stres Dalam Aktivitas Kerja Kantoran Menggunakan Algoritme Extreme Learning Machine dan Seleksi Fitur One-way ANOVA F-Test Dariswan Janweri Perangin-Angin; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 13 (2020): Publikasi Khusus Tahun 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Artikel dipublikasikan di International Conference on Sustainable Information Engineering and Technology 2020
Sistem Pendeteksi Dini Lubang pada Jalan menggunakan Gray Level Co-Occurrence Matrix berbasis Raspberry Pi Audrey Athallah Asyam Fauzan; Fitri Utaminingrum
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 3 (2021): Maret 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Nowadays, the land transportation mode is the most popular. This is indicated by the data of motorized vehicles in Indonesia is increasing. Damaged roads have a huge impact in driving, because it can cause inconvenience to the driver and it can cause the effect of damage to the vehicle. Based on the causes of road accident data, infrastructure and environment factors are one of the causes of accidents, and potholes are one of them. The solution to the problem is to create a system that can detect a pothole. This research uses Gray Level Co-Occurrence method to obtain the feature characteristic of the pothole and Support Vector Machine to classify whether the detected object is a pothole or not. The system requires a camera to capture an image that will be detected and perform an object recognition. If the system can detect a pothole, the driver will get a notification sound from the speaker. Tests were carried out several times based on the d and theta values in the GLCM feature extraction and based on vehicle speed ranges between (0-30 km/h and 30-60 km/h). Based on the test, the best d and theta values are d=2 for theta =90. The best accuracy value is obtained when the speed range is (0-30 km/h) with an accuracy value 81,70%. The accuracy of the harware detection integration test is 87,5%. In testing the average computation time of the system to recognize the pothole is 134,17 ms.

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