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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.
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Articles 30 Documents
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Search results for , issue "Vol 1 No 9 (2017): September 2017" : 30 Documents clear
Rekayasa Kebutuhan dengan Metode Pemodelan Berbasis Linguistik dan Ontologi pada Sistem Penilaian Prestasi Kerja Pegawai Dinas Kominfo Kota Malang Nurwida Mariatul Sadila; Fajar Pradana; Bayu Priyambadha
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

Software requirements engineering is crucial in the software engineering process. One of the main causes of software requirements engineering failure is that the stages are not done quite well. The structuring and clearly defined semantic will make the requirement spesification easy to be understood and validated. Linguistic based modeling method and ontology be used for modeling specification and its validation base. Sistem Penilaian Prestasi Kerja Dinas Kominfo Kota Malang is used as case study in this thesis. The requirement specification which is obtained in the development process is modified and modeled into semantic model. DITA (Darwin Information Typing Achitecture) is used as semantic method which work for documenting the requirements in scenario format with additional ontology annotations. The additional ontology function is to be the reference from DITA to ontology or vice versa. It aims to facilitate the requirements understanding during the maintenance process. The requirements validation and verification is using the ontology method by applying the query to the requirements. The query results show the completeness, consistency, and correctness status toward the requirements. The benefits of performing the validation and verification to the requirements using this method are the requirements which have errors can be detected very soon and easily with the level of completeness, consistency, and correctness up to 100%.
Pembangunan Sistem Pengelolaan Bank Soal Ujian Pilihan Ganda Secara Online Silvia Ajrini; Tri Astoto Kurniawan; Denny Sagita Rusdianto
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

Abstract Multiple choice test in Faculty of Computer Science, Brawijaya University has been constructed manually. Such construction encounters some problems, e.g. similarity in some questions created by some lecturers. In addition, lectures often forget to save every question that they ever made. All of these problems can be solved by an online questions bank management system for the multiple choice test. This system is expected to assist lecturers in creating and storing the questions safely as well as to detect the similarities among the questions. This system will be made in web, such as lectures can access anywhere and anytime. The system has been successfully tested using white box technique for unit and integration testings, and black box technique for validation testing. Keywords: online questions bank management system, multiple choice test, object oriented, waterfall model
Pemodelan Sistem Pakar Diagnosis Penyakit pada Sistem Endokrin Manusia dengan Metode Dempster-Shafer Didin Wahyu Utomo; Suprapto Suprapto; Nurul Hidayat
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

The endocrine system is a gland system that acts on the human body whose secretedness called as hormones. Hormones are chemicals which carried within the bloodstream to tissues and organs and then stimulate hormones to perform certain actions. Hormones work directly into the blood without going through the ductus. Endocrine disease is very dangerous and can even lead to death if it were not treated immediately. In the BPJS system that implemented by the Indonesian government, general practitioners serve as the main gateway in diagnosing the disease or determining whether to be referred to a specialist. In the case of endocrine disease patients, it is very dangerous if not treated early, whereas referral process to a specialist or hospital takes a long time due to many patients who come. The purpose of this modelling system is one way done that aims to provide early help for patients with endocrine diseases. This application is developed by using PHP programming language using CodeIgniter framework and MySQL database. The process of calculating the diagnosis of disease using the Dempster-Shafer method. Testing is done by comparing the conformity of results between the diagnosis of the system and the results of expert diagnosis. Based on 35 tested data, obtained 91.428% test accuracy level indicating that modeling expert system diagnosis of endocrine disease with dempster-shafer method can well functioned
Analisis Perbandingan Metode K-Means Dengan Improved Semi-Supervised K-Means Pada Data Indeks Pembangunan Manusia (IPM) Gusti Ngurah Wisnu Paramartha; Dian Eka Ratnawati; Agus Wahyu Widodo
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

At this time with the growing amount of information, the concept of data mining getting known as an important tool in the management information. Refers to the concept of data mining, the most popular concept in data mining is a clustering technique. One well known clustering method is k-means traditional. But in its application, k-means method has some problems such as determining the value of K cluster and determining the initial cluster centers were done randomly making process was inconsistent and the results of the cluster becomes worse. Therefore, there is a method to overcome these problems are improved semi-supervised k-means clustering. With improved semi-supervised method that combines the supervised and unsupervised method, users only need to label a bit of data that has not been labeled, then the labeled data is used to find the optimal value of initial cluster center and K cluster that will optimizes the process and result of clustering process. On implementation, this research combine k-means algorithm and improved semi-supervised k-means to clustering human development index (HDI) data. HDI data chosen because it has the right characteristics for clustering such amounts of data and the data is divided into several clusters. On the testing improved semi-supervised k-means method giving out the average accuracy of 90.3%, better than k-means clustering that giving 73.7% accuracy. In the second testing, improved semi-supervised k-means method produces an average time for one convergent 1222.9959 seconds, better than k-means with 1504.75 seconds. The third testing, improved semi-supervised k-means generates an average number of iterations for one convergent more efficient than k-means with the number of iterations of 7.11 compared 9.72. Last, on the cluster quality testing using silhouette coefficient, improved semi-supervised k-means method giving average value 0.69880, better than the traditional k-means with an average value of 0.62734.
Sistem Pendukung Keputusan Budidaya Tanaman Cabai Berdasarkan Prediksi Curah Hujan Hilal Imtiyaz; Barlian Henryranu Prasetio; Nurul Hidayat
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

Abstract Chili is one of holticultura product wich is needed every day by Indonesian people. They use chili for spice in cooking. Chili supply not any time to meet demand. It causes price increases in accordance with the law of demand and supply. The surge in prices because of limited supplies occur every year. One of the problems that cause unavailability of supply throughout of year is chili crop failure cause chili cultivation is not good. pepper cultivation planning must consider the rainfall so that water for plants is available. Chili plants would not grow well if the plants lack of of water or if the water is too much. It will disturb chili growth, fertilization and crop becomes susceptible to pests. The main source off plants irrigation is rain. Knowledge of rainfall in the future will help farmers in cultivating planning. This research will discuss about decision support systems of chilli cultivation based on the rainfall prediction using simple linear regression method. Regression method used to predict the rainfall with modeling rainfall data in previous years. Based on the data the rainfall forecasts, system will recomanded best ways of pepper cultivation. Results of rainfall prediction using simple linear regression method has the accuracy rate of 91.6% which inluantial to the good of chili cultivation. Keywords: Decision Support Systems, Chili, Simple Linear Regression, Rainfall.
Implementasi Sistem Pervasive Pada Smart Home Berbasis Bluetooth Versi 4.0 Menggunakan Modul BLE HM-10 dan Sensor I Wayan Boby Astagina Naghi; Sabriansyah Rizqika Akbar; Barlian Henryranu Prasetio
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

Smart Home with pervasive concept can find Bluetooth device and the services. Smart home constructed can control many node so energy saving is required. Thus, appropriate Bluetooth for this pervasive Smart Home is Bluetooth 4.0 (BLE). Bluetooth 4.0 is derivated from Classic Bluetooth technology which low-cost, long-life battery caused by minimum energy consumption, and easy development. Author implements the pervasive smart home system with smartphone as the controller through BLE communication. Smart Home consists of lamp node (Arduino Nano, LED, and modul BLE HM-10), temperature and humidity node (Arduino Nano, sensor DHT11, and modul BLE HM-10), and fan node (Arduino Uno, kipas DC, dan modul BLE HM-10). Android application as the controller constructed using MIT App Inventor 2. Scanning done by application then continued by choosing BLE HM-10 node and connect them through CONNECT button. When connection formed, SERVICES button pushed to knowing the services given by BLE HM-10 node. If the service has been displayed on smartphone, user can input number instruction to operating the BLE HM-10 node. Feedback of operation result will be displayed on the smartphone. DISCONNECT button pushed to disconnect the connection. BLE HM-10 performance also tested in case of signal quality and energy consumption comparison with Bluetooth HC-05. Based on the test result, caused of pervasive concept, when scanning process, application can recognize BLE HM-10 node and the services displayed when requested by user. Feedback and service displayed in the form of sentence with maximum amount of 20 characters because maximum payload size of BLE HM-10 is 20 byte, and the sentence more than 20 characters will be displayed one by one. BLE HM-10 has maximum signal quality of 98% and minimum quality of 20% and better in term of energy saving (5,69 mW) than Bluetooth HC-05 (13,56 mW)
Penggunaan Ciri Geometric Invariant Moment pada Pengenalan Tanda Tangan Rahma Juwita Sany; Agus Wahyu Widodo; 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

Signature as a personal attribute is one of the person's identity verification equipment that is accepted widely by the society. The process of signature recognition starts from starts from preprocessing, which consist of filtering, thresholding, thinning, cropping and resizing. After preprocessing continued by feature extraction process using Geometric Invariant Moment to get the value of a feature that will be used for the classification process using K-Nearest Neighbour. The variations Geometric Invariant Moment feature that has the smallest of FAR value and FRR value on each data source are different. For data from Indonesia the smallest FAR obtained while using moment 7 with value is 7% and the smallest FRR obtained while combining moment 1,2,3,6 and 7 and using all of the moment with each value is 61.5%. For data from Spain the smallest FAR obtained while combining moment 3,4,5 and 7, moment 1,3,4,5 and 7 and combining 1,3,4,5,6 and 7 with each value is 7% and the smallest FRR obtained while combining moment 2,3,4,5,6 and 7 and using all of the moment with each value is 72%. For data from Persia the smallest FAR obtained while combining moment 3 and 5 and combining moment 3,5 and 6 with each value is 9.5% and the the smallest FRR obtained while combining moment 1,2,3,4,6 and 7 with value is 37%. The testing results of FAR and FRR is inversely proportional. The system can recoginize the fake signatures well that proven by getting FAR value is relatively small on all of data sources. But the system can't recognize the original signatures well that proven by getting the high FRR value on all data sources. Features of Geometric Invariant Moment that applied globally on an image don't provide high accuracy. Perhaps, it happened because when apply global feature, the local features can't recognize properly. It occurs on the original signature image, while the application of the features of Geometric Invariant globally on the fake signature image provide high accuracy.
Optimasi Penjadwalan Damping Mahasiswa Difabel Menggunakan Algoritma Genetika (Studi Kasus PSLD Universitas Brawijaya) Mukh. Mart Hans Luber; Imam Cholissodin; 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

Mentoring scheduling for Disabled student is the preparation schedule implementation to a companion who served in the division of working time. On the good scheduling process then will maximize service to disabled students. This scheduling problem is difficult because the number of accompanying relative limited compared to the number of disabled students. The schedule created by the workload evenly to each escort. In this study applied the concepts of problem solving scheduling by using genetic algorithms. Application of genetic algorithm to find the optimal solution. In the settlement of this problem use an integer representation with the length of chromosome 45 genes that each section of the gene showed code mentoring. The method used is the crossover one-cut method of point mutation process, using the method of reciprocal exchange and mutation on the selection process using the method of elitism selection. From the results of testing that has been done optimal parameters obtained using a 100 generation with fitness value 0.966. The final results obtained in the form of a mentoring schedule for 5 days.
Implementasi Load Balancing Di Web Server Menggunakan Metode Berbasis Sumber Daya CPU Pada Software Defined Networking Riski Julianto; Widhi Yahya; Sabriansyah Rizqika Akbar
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

Nowadays, there has been a great traffic in the network. It is characterized by an increasingly high users will increase the complexity of the network such as increased server load and hard to configure any devices from different vendorss, so there needs to be a good web server. If a single web server, it will cause SPOF (Single Point of Failure). The use of cluster servers with load balancing will improve the performance of web servers implemented in Software Defined Network. Load balancing with resource-based methods is a load-sharing method using the smallest CPU usage of the server as a reference. Through the implementation of the system obtained server divide the load well. Testing with many connections and rate divided into 3 parts that is low to rate 40, medium to rate 80 and high for rate 160. The testing parameters used are throughput, response time, and CPU usage using Httperf and psutil tools. The results of the test obtained with the average throughput value of 947.9 KB / s, response time average of 6.2 ms, and CPU Usage of 59.82% on the first server, 69.73% on the second server and 93,24% on the third server. By comparison of the Round Robin algorithm, the CPU-based method is better than Round Robin based on the tests performed.
Identifikasi Diagnosis Gangguan Autisme Pada Anak Menggunakan Metode Modified K-Nearest Neighbor (MKNN) Jojor Jennifer BR Sianipar; Muhammad Tanzil Furqon; Putra Pandu Adikara
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

Autism is a neurological disorder that shows significant result as a lack of ability to form social relationships, normal communication, and behavior in children. This symptoms generally appear before children reach the age of 3 years. It is not classified as a psychiatric disease because autism is a disorder that occurs malfunction of children's brain and it is manifested on children's behaviour. Some research states that autism causes as the neurodevelopmental disorder that causes abnormalities in children's brain structure. Different experts mentioned that autism in children caused by the kind of food they consumed or they living environment that contain many harmful substances that shows in children's behaviour. Therefore, the system for the identification of autism disorders in children will be create to help identifies autism disorder by using the method of Modified K-Nearest Neighbor (MKNN). It is one of classification method based on the appearance of largest classes in data training. There are 14 symptoms from 4 aspects that are used as parameters in the development of the system. The output of the system is showing whether a child is autistic individuals or not. Based on the testing that has been done on the system that using Modified K-Nearest Neighbor (MKNN), maximum accuracy shows 100% accuracy while minimum accuracy is 92%. Based on those results, the uses of Modified K-Nearest Neighbor (MKNN) method can be implemented in our daily life.

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