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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 6,850 Documents
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Pengembangan Sistem Informasi 3 Pilar Dalam Penyelesaian Perkara Tilang Di Kota Kediri Menggunakan RESTful Web Service Pramuditya Ananta Nur; Adam Hendra Barata; Agi Putra Kharisma
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 10 (2018): Oktober 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The traffic and the transportation is an unified system which is consist of the traffic, the public transportation, the traffic network, the infrastructure, the vehicles, the drivers, the road user and also it's management. Although there is a certain regulation about the traffic, there are still a lot of traffic violation. The road user or the driver who violate the traffic will get such kind of ticket. The mechanism of the settlement of traffic violation involved three law government institutions. They are Indonesian National Police, Supreme Court of Indonesia and Attorney Office. In Kediri, they create a memorandum of understanding (MoU) which is known as the “Surat Keputusan bersama Tiga Pilar” in settlement the traffic violation cases. But there are some problems appear, like data that are not well organized, making reports that take time, the lack of information for the citizens, and also the difficulties in accessing the information to other government institutions in Kediri. Sistem Informasi Tiga Pilar was created using RESTful web service in order to make all of the business process in each institutions become easier. Implementation is done using Spring Boot framework as the web service of the system and AngularJs to connect between client and web service. Testing is done by using validation testing, unit testing, data integrity testing, and usability testing. The result of validation testing and unit testing is 100%, and usability test result with Software Usability Scale (SUS) is 72,5 with effectiveness value 90,9%.
Implementasi Metode K-Medoids Clustering Untuk Pengelompokan Data Potensi Kebakaran Hutan/Lahan Berdasarkan Persebaran Titik Panas (Hotspot) Dyang Falila Pramesti; Muhammad Tanzil Furqon; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 9 (2017): September 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Forest / land wildfire is one of the disasters that occur every year in some countries in the world. This incident got more attention from the government because it caused many losses both in the economic, ecological, and social. Indonesia is a country with a high rate of forest / land wildfire disasters. Indonesia suffered losses of up to Rp 209 trillion by 2015. As a result of losses incurred an early prevention is needed, which one can be done by grouping areas with potential forest fires by utilizing hotspot data. Forest wildfires are marked by the detection of fire spots by satellites indicated as hot spots. This research uses hotspot data with parameter of latitude, longitude, brightness, frp (fire radiative power), and confidence by using K-Medoids method. K-Medoids method is a clustering method that serves to split the dataset into groups. The advantages of this method is able to resolve the weakness of K-Means method that is sensitive to outlier. The result of this research shows that the use of K-Medoids method can be used for the process of hot spot data clustering with the best silhouette coefficient in amount of 0.56745 on the use of 2 clusters by using 7352 data. The results of the clustering analysis showed that using 2 clusters resulted in a group of data with the potential of high potential with an average brightness of 344.470K with average confidence of 87.18% and medium potential with average brightness of 318.800K with Average confidence of 58.73%.
Sistem Diagnosis Penyakit Hati Menggunakan Metode Naive Bayes Novianto Donna Prayoga; Nurul Hidayat; Ratih Kartika Dewi
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

System Diagnosis of Liver Disease using Naive Bayes Method is an application that aims to help people for diagnosing liver disease early. This system is built based on problems that occur in society that is difficult in liver disease. Because liver disease has many symptoms and there are similarities in symptoms. This is one of the causes of high percentage of liver disease in Indonesia, recorded from Basic Health Research in 2013, one type of liver disease that is national hepatitis B prevalence reached 21.8 percent, and ranked third highest in Indonesia.The Naive Bayes method was chosen in this study because Naive Bayes paid attention to all features of data training so as to make this method optimal in classification process. This system uses the Android operating system, because Android is quite consistent popularity in the market smarthphone Indonesia until now. The data used in this study were obtained from doctor who have been validated by the institution of Universitas Brawijaya Hospital, Malang. The results of this study indicate base on the accuracy testing of 40 data testing obtained an accuracy of 87,5%.
Clustering Pasien Kanker Berdasarkan Struktur Protein Dalam Tubuh Menggunakan Metode K-Medoids Laily Putri Rizby; Marji Marji; Lailil Muflikhah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 10 (2018): Oktober 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Kanker merupakan penyakit yang kerap menjadi momok bagi sebagian besar orang memang telah memakan banyak korban. Semakin berkembangnya zaman semakin banyak virus yang tersebar di masyarakat. Kanker adalah istilah yang digunakan untuk menggambarkan ratusan penyakit berbeda dengan fitur tertentu yang sama. Kanker dimulai dengan perubahan dalam struktur dan fungsi sel yang menyebabkan sel membelah dan menggandakan diri tanpa terkontrol. Umumnya kanker dinamai sesuai organ dan jenisnya tempat pertama kali ia berkembang. Mutasi gen yang paling sering ditemukan pada kanker manusia adalah Gen P53. Gen P53 merupakan gen penekan tumor yang mengkode atau mengekspresikan protein 53. Dari berbagai banyak data yang ada perlu dilakukan proses klusterisasi yaitu pengelompokkan jenis kanker berdasarkan kelasnya. Salah satu metode klustering yang mulai banyak digunakan adalah metode K-Medoids. K-medoids atau dikenal pula dengan PAM (Partitioning Around Medoids) menggunakan metode partisi clustering untuk mengelompokkan sekumpulan n objek menjadi sejumlah k cluster. Algoritma ini menggunakan objek pada kumpulan objek untuk mewakili sebuah cluster. Objek yang terpilih untuk mewakili sebuah cluster disebut medoid. Pada penelitian clustering pasien kanker menggunakan metode K-Medoids ini menunjukkan nilai persentase kualitas cluster sebesar 77% pada percobaan pada nilai k 14 dan menggunakan 116 data.
Analisis dan Perancangan Sistem Informasi Pelayanan Informasi Pasar Kerja Dengan Pendekatan Berorientasi Objek Bambang Setiyawan; Ismiarta Aknuranda; Admaja Dwi Herlambang
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 9 (2018): September 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Labor Market Information Services is one of the services provided by the Department of Manpower (Disnaker)as meant in Regulation of the Minister of Manpower and Transmigration Republic of Indonesia Number 7 of 2008. Increasing job market information, job market, and expansion of employment opportunities and transmigration placement areas is one of the missions owned by Disnaker Malang Regency in line with the minister's regulation. Currently, labor market information services can be done by using the website of Disnaker Malang Regency. But by using this method, the labor market information service still needs to be maximized because the labor market information is mixed with other information. From these problems it is necessary to design an information system that supports in conducting labor market information service. Object Oriented Analysis and Design (OOAD) will be used in the analysis and design of the information system. The results of the analysis and design will be evaluated using the Requirements Configuration Structure and Decision table. The end result of this research is the current business process models and proposals, lists of stakeholders and users, user requirements list, features, system requirements list, use case model, system design and evaluation.
Peringkasan Teks Ekstraktif Kepustakaan Ilmu Komputer Bahasa Indonesia Menggunakan Metode Normalized Google Distance dan K-means Dhimas Anjar Prabowo; Mochammad Ali Fauzi; Yuita Arum Sari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 12 (2017): Desember 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The yearly rapid increase of digital data surface a problem for a person to be able to read every information that was served. One example of its data was a textual data document, which could be in a form of research document. This problem urges for a solution that is a technique to present all of the information in a clear and concise form, and one of its solution is a text summarization technique. This research proposed a text summarization technique using Normalized Google Distance (NGD) and K-means as its extractive algorithm, with a textual data that is a research document based on computer science studies in an Indonesian language as its research object. NGD will be used as an algorithm to derive sentences that was related to its document's title, and K-means will be used as an algorithm to obtain important sentences by its several topics that occurs in the document. The experiment result showed that this research possess an average best of precision, recall, and relative utility measures scores by 0.27, 0.43, and 0.45 respectively. In the other hand, the experiment result also showed that this research possess an average of kappa measure score by 0.41 or moderate.
Monitoring Kadar Gas Berbahaya Pada Kandang Ayam Dengan Menggunakan Protokol HTTP Dan ESP8266 Muhamad Nur Arifin; Mochamad Hannats Hanafi Ichsan; Sabriansyah Rizqika Akbar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 11 (2018): November 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In this research, Authors make a monitoring system of dangerous gas content in the chicken coop. The system able to inform air quality in the form of ammonia and methane gas contained in chicken coop and give result of reading of gas data which considered dangerous to worker in chicken coop and can be seen by platform. The system generally consists of two gas sensors, the MQ 135 sensor to detect the ammonia, and the MQ 4 sensor to detect methane, and connect to the internet network via the ESP8266 modul with Arduino Uno microcontroller that aims to upload sensor data to web Thingspeak and displayed in the form of graphs as a means of information on the chicken coop. Testing was did with 3 stages of connectivity, functionality, and delay. The connectivity test proves that the ESP8266 can connect to the Access Point and Internet network. The functionality test proves that the sensor can read the gas and retrieve the data. And the last is the delay test, which is calculating the length of the process from the beginning of the sensor readings until the data arrived at IoT web based Thingspeak. From the results of calculations that have been done in testing, it is found that the time required for a single data transmission takes as much as 5-19 seconds. The time may change because there are aspects that can hamper such as internet connection, the number of devices connected to one network internet, but the purpose of research is in accordance with expectation.
Perbandingan Performa Database Apache HBase dan Apache Cassandra Sebagai Media Penyimpanan Data Sensor Internet of Things Dimas Malik Ibrahim; Rakhmadhany Primananda; Mahendra Data
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

Nowadays, internet has dominated the world, millions of data is exchanged daily either through web/mobile apps or internet use involving the objects around us to be able to communicate each another (currently known as Internet of Things/IoT). IoT requires a database with a good performance to be used as its storage media. Good performance it is like fast inserting data process and high level of availability. There are two types of databases at this time, Relational Database and Not Only SQL (NoSQL) Database. NoSQL Database is the proper type to be used as data storage media on IoT system because it has better scalability and availability level than Relational Databases. Of the many NoSQL Database, the author chooses HBase and Cassandra to compare their performance in this research, because both are the best in database Column-based storage model. The authors test the Throughput, Latency, Runtime CPU Usage, and Memory Usage using JMeter and YCSB to compare the performance of both these databases. The results suggest that Cassandra has Throughput, Latency and Runtime that is better than HBase. Meanwhile, HBase has CPU Usage and Memory Usage better than Cassandra.
Pengenalan Citra Tanda Tangan Off-Line dengan Pemanfaatan Ciri Centroid Distance Function Rizka Husnun Zakiyyah; Agus Wahyu Widodo; Fitri Utaminingrum
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 10 (2017): Oktober 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

A person's signature is one of the most valid proof that shows ownership of documents and transactions that contain their most important data. However, the process of analizing its authenticity is still done manually. To resolve this problem, an image recognition system for signature will be developed by applying characteristic centroid distance function. This Image recognition process begins with preprocessing, such as binerisasi, filtering, cropping, resizing, and thinning. Next the position of pixels will be searched to store all the foreground pixels and centroid pixels of the image. All pixels stored distance will be calculated using centroid function and grouped according to the amount of features that were selected so that each group has the same amount of data. The average of centroid distance function will be counted on every group so that each group will generate one feature. The results of feature extraction will be processed with the k-nearest neighbor classification method. On the research that has been done the highest accuracy obtained from extraction characteristics of centroid distance function uses 20 class is 88.5% obtained from 20 features and k= 1 with the amount of 10 and 14 training data for each class. The highest accuracy to 50 class is 67.4% obtained from 15 features and k= 3 with 10 and 14 training data for each class.
Prediksi Indeks Harga Konsumen (IHK) Kelompok Perumahan, Air, Listrik, Gas Dan Bahan Bakar Menggunakan Metode Support Vector Regression Krishnanti Dewi; Putra Pandu Adikara; Sigit Adinugroho
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 10 (2018): Oktober 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

One of the most commonly used indicators to measure the inflation rate is Consumer Price Index (CPI). Based on the consumer price index metadata published by Bank Indonesia in 2016, housing, water, electricity, gas and fuel group is the CPI group which has the highest proportion of living cost from other CPI groups, which is 25.37 %. In this research, CPI will be predicted by using Support Vector Regression (SVR) method. The stages of the SVR method include normalization of data, calculates Hessian matrix by using Radial Basis Function (RBF) kernel function, sequential learning process, calculate the regression function to get predicted results and evaluates predicted results with Mean Absolute Percentage Error (MAPE). The test results show the minimum MAPE value obtained by 4.271% with the parameter value σ = 50; λ = 1; cLR = 0.0005; ε = 0.0005; C = 1000; the number of training data is 36 for 12 testing data with 100 iterations. The average of predicted results obtained is 112.19605 with the average of the difference between the actual data and the predicted result is 1.52645.

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