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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 6,480 Documents
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Pengembangan Permainan Edukasi Simulasi Astronomi Menggunakan Teknologi Mobile Virtual Reality Firly Wahyudi; Wibisono Sukmo Wardhono; Amminul Akbar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 11 (2017): November 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Virtual Reality Technology in this era could be implemented toward every aspect in life. One of those aspect is Education. The implementation of this technology in education field has a goal to increase the student reception toward information. Virtual Reality implementation with head mounted display on an android platform can increase student reception toward information by stimulating student's senses through those technology. Another positif effect by using both of those technology can make the game more interactive, intuitive and fun. The development process begins with planning and evaluation. The design process is done by determining the formal elements in the game, determining the rules, goals and so on. The elements will work as a whole to form a game in accordance with the design. The process will continue at the digital stage of prototyping and evaluation. The prototyping stage will illustrate the initial draft that will describe the game as a whole. The prototypes will be evaluated for their feasibility to be implemented. From the results of implementation on the development, will be tested that will measure the feasibility of the system that has been developed
Voting Based Extreme Learning Machine dalam Klasifikasi Computer Network Intrusion Detection Sindy Erika Br Ginting; Agus Wahyu Widodo; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 6 (2018): Juni 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Intrusion Detection System (IDS) is useful software or system to detect intrusion on computer networks. It works by utilizing artificial intelligence to identify anomalies or signatures from the activity on computer networks. To refine more the IDS, it requires the development of intrusion classification algorithms with high accuracy. Voting based Extreme Learning Machine (ELM) is a new scheme algorithm which updates the Extreme Learning Machine (ELM) in improving ELM classification performance and is known more reliable for many data. In this study, the performance of the V-ELM has been evaluated on the Knowledge Discovery and Data Mining (KDD) Cup 99 dataset to support IDS development. This study showed that V-ELM was produced bad performance when using some data from KDD Cup 99. It was using 1000 training data and 250 testing data from KDD Cup 99 datasets. The data was divided into 3 variants are 40 classes, 5 classes, and 2 classes attack. The parameters which tested are the values of hidden neurons (L), independent training (K), and sensitivity of each intrusion class. This study found that the best accuracy result on independent training (K) was 3 and 100 hidden neurons in 2 attack class data with an accuracy of 72%. The lowest accuracy was obtained on hidden neurons was 100 and independent training (K) was 11 in 40 attack classes with an accuracy of 12%. This result showed that good classification capability in 2 classes and bad classification capability in 40 classes.
Peringkasan Literatur Ilmu Komputer Bahasa Indonesia Berbasis Fitur Statistik dan Linguistik menggunakan Metode Gaussian Naive Bayes Muhammad Fhadli; Mochammad Ali Fauzi; Tri Afirianto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 4 (2017): April 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In this era which require big amount of data, text summarization becomes a needs. With text summarization, everyone can get information that describe all of big text in just few of sentences. The problem in text summarization is quality of the summarization result. One of the known method for text summarization is TFIDF, this method is a method for summarizing text using statistical approach. The other approach for summarizing text is statistical approach. In a general way, summarization result is consist of sentences with statistical features such as total of words, total of keywords, and sentence position in the original text. Those features can be used to classify a text into class of summary or class of non summary. The summarization result come from the composite of every sentence in summary class. In this research, writer combines the use of statistical feature and linguistical features to summarize text. The testing result of this research show that summarization with statistical and linguistical features using Naive Bayes method came with f-score average 0.206538 and realive utility average 0.116657.
Rancang Bangun Aplikasi Mobile Media Informasi Wisata Suroboyo Carnival Berbasis Augmented Reality Alfin Noor Afyuddin; Issa Arwani; Tri Afirianto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Tourism includes human needs and becomes an important sector for generating regional and state revenues. In general, tourists use print media to obtain information and become a guide in a tourist location. But the media has limitations, so it needs an interactive and effective media to be used as a medium of information of a tourist location. Auxiliary media is an application that provides navigation features that show the direction and distance of the user location with the location of the intended rides as well as suggestions of the order of visits and information of the required rides. The media used are smartphones by utilizing augmented reality technology as well as the use of combinations, permutations and algorithms dijkstra to suggest the order of visits with the shortest path. Features used Android smartphone is a camera, GPS, accelerometer, and compass. System design using the framework beyondAR. Testing on the system in the form of functional testing, angle accuracy testing, and distance accuracy testing. The function of determining the direction and distance with the markers and suggestions of the order of visits can run. On the results of the results of accuracy test results arising from the implementation of the formula heading on the application has a percentage of accuracy of 97.43%. And on the test of accuracy of distance has the accuracy percentage of 99.79% with distance calculation using haversine method. Accuracy test results show the implementation on the system has a high accuracy.
Sistem Rekomendasi Psikotes untuk Penjurusan Siswa SMA menggunakan Metode Modified K-Nearest Neighbor Muchlas Mughniy; Randy Cahya Wihandika; Barlian Henryranu Prasetio
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Major selection for high school student intended to facilitate students to focusing on specific field for higher education. However, assigning academic potential for each student through school counselor needs plenty of time. A recommendation system can generate a recommendation for major selection based on cognitive ability by Intelligenz Struktur Test (IST). Modified k-Nearest Neighbor is applied to system which classifying academic potential based on neighborhood by training data. Training data consist of nine cognitive intelligences and two majors. So, system will provide a recommendation for major. From the testing process that has been done, has obtain highest averaged accuracy on 90% dataset is 67,95%, averaged accuracy on 4-fold Cross Validation is 63,58%, averaged Sensitivity and Specificity is 23,64% and 92,34%, accuracy comparison between MKNN and KNN is 63,58% and 57,11%, and then highest accuracy for feature reduction using PCA is 55,26% which is reduced to 6 features. According to test result indicate that Modified k-Nearest Neighbor recommendation system not optimal yet to generate a recommendation for major selection.
Deteksi Penyakit Kucing dengan Menggunakan Modified K-Nearest Neighbor Teroptimasi (Studi Kasus: Puskeswan Klinik Hewan dan Satwa Sehat Kota Kediri) Fitri Dwi Astuti; Dian Eka Ratnawati; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 11 (2017): November 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Cats are animals that are widely nurtured by people, so there are now many findings related to cat disease caused by many factors. Knowledge and understanding of the symptoms that occur in the cat to be an important factor, so that people can better anticipate the occurrence of more severe disease. With some of the problems that have been described before then give the idea to built an application "Deteksi Penyakit Kucing". In this study the method used is Modified K-Nearest Neighbor, but the method has a weakness in the biased k value, so the accuracy of the resulting level sometimes less than the maximum. Given the problem, the genetic algorithm is used to optimize k value in the Modified K-Nearest Neighbor method. Data used in this research is cat disease data at Puskeswan Klinik Hewan dan Satwa Sehat of Kediri with amount of training data as many as 105 and test data counted 35. From all data will be classified into 7 class with criterion as much as 19. Accuracy result of Modified K-Nearest Neighbor using genetic algorithm for optimal k 1 is 100%. From these results the application of cat disease detection with optimal k value can be used by the public to recognize diseases in cats.
Evaluasi dan Perbaikan Usability pada Dashboard PT.PLN (PERSERO) APD Jawa Timur Berorientasi Human Centered Design dan Key Performance Indicators Gayuh Syahqila Ravdania; Ismiarta Aknuranda; Retno Indah Rokhmawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 5 (2018): Mei 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

PT.PLN APD Jatim is an organization of PT.PLN Distribution Jatim who served as a controller of distribution. This makes PLN APD Jatim has a lot of data to managed, so that need monitoring of the system such as the dashboard. The current dashboard is still less from interface side and does not match with needs of the user seen from Key Performance Indicators (KPI). Therefore, this research discusses about evaluation and usability improvement on dashboard PT.PLN (Persero) APD Jatim oriented human centered design and key performance indicators. Information gathering such as problem identification and usage context are obtained using interview method and system viewing for dig up information in more detail. Then for the framework of improvement, this research using Human Centered Design (HCD) because at each step of the research involves the user. The dashboard prototype was evaluated using a system usability survey and measured by System Usability Scale (SUS). SUS aims to generate the value of system usability. SUS is suitable for use because it can measure system using the minimal responden and can apply extensively. The evaluation results state that the solution design is good enough and according to needs of user so that no such repair.
Klasifikasi Gangguan Jiwa Skizofrenia Menggunakan Algoritme Support Vector Machine (SVM) Daisy Kurniawaty; Imam Cholissodin; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 5 (2018): Mei 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Insanity is the most common disease. One of insanity is schizophrenia. The process of diagnosis of schizophrenia is difficult, because there is no specific characteristic of behavior or appearance for the sufferer, some sufferer can behave and look like normal people and expensive treatment. It will make the patient's condition worse. To resolve this issue, this can be done with schizophrenia classification using support vector machine (SVM) algorithm. In this study there are 75 data that is divided into two types of schizophrenia, that is paranoid and simplex. The method in this study using support vector machine algorithm, wich to the category of good classification method, provides a statistical approach in pattern recognition, and is a linear method, but SVM provides kernel trick, which can solve problems related to non-linear classification. The result obtained using SVM 100% accuracy using ratio data 90%:10%, gamma = 0,00001, lambda = 3, C = 0,01, kernel polynomial of degree, maximum iteration is 1000.
Pengembangan Sistem Informasi Bimbingan Konseling Siswa Pada SMP Negeri 1 Panarukan Ahmad Taufiq Hidayatullah; Fajar Pradana; Mochammad Chandra Saputra
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 7 (2017): Juli 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

SMP Negeri 1 Panarukan has one goal, namely the establishment of a students' noble character. To achieve this objective, the codes of conduct and counseling services were established. Based on the interview, there are some problems in the counseling services. Firstly, many violation points are not accumulated because the point record is still manual, so the sanctions given are not appropriate. This affects the results of student character values that require the total violation points as the indicator. Secondly, the ineffectiveness of parent notification letter which is rarely given by students to their parents. Lastly, the input process of the counseling services that seems to use too much paper. Based on these problems, it can be given a solution to develop an information system that has the function to overcome these problems. The method used in the development of the system is the waterfall method which includes needs analysis, design, implementation, testing, and maintenance. While in the testing process, basis path testing, validation testing, and testing compatibility are used. The results of basic path testing are the two functions having a structure that is easy to understand and easy to implement and 1 function having a more complex structure. The result of the validation testing is a software function that can be run in accordance with its functionality. The results of the compatibility testing is the software that can be used in 10 different types of browsers.
Implementasi Metode Delta-Extract untuk Sinkronisasi Data Pada Aplikasi Kasir Smart Laundry Assistant and Management (SINADME) (Studi Kasus: CV. Citridia IT Solution) Shidqon Alkaaf; Satrio Agung Wicaksono; Aryo Pinandito
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Database synchronization is an activity to equalize the data contained in multiple databases. It is utilized by the SINADME Mobile app in the process of retrieving primary data on servers temporarily stored in mobile applications for offline transactions. Currently SINADME Mobile uses the Full-Load method to synchronize, so if sync is done on a regular basis it will result in increased load. This research will implement Delta-Extract method in synchronizing to reduce load during synchronization routinely. The focus of this research is the analysis of the loads received by mobile applications using Full-Load and Delta-Extract. Based on the test results, the Full-Load Method eases the burden received by the mobile application during initial data retrieval and the Delta-Extract method reduce the loads received by the mobile application during data retrieval after changes.

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