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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 40 Documents
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Search results for , issue "Vol 1 No 11 (2017): November 2017" : 40 Documents clear
Optimasi Komposisi Bahan Makanan bagi Pasien Rawat Jalan Penyakit Jantung dengan Menggunakan Algoritme Particle Swarm Optimization (PSO) I Gusti Ayu Putri Diani; Imam Cholissodin; Suprapto Suprapto
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

Heart is an organ which is very important in the body that pumps blood. Many people can suffered heart disease caused by unhealthy lifestyle. Most of the deaths, according to the report of the World Health Organization (WHO), caused by cardiovascular disease that cause 17.7 million or approximately 45%. For people who suffers with heart disease, take care of food consumption is important in order to be healthy again. This research will be conducted on the giving food ingredients for the patients who suffers cardiovascular disease whose can continue their treatment in their home.Research conducted is optimizing the composition of the food ingredients for cardiovascular disease outpatient by using particle swarm optimization algorithm which the results will be displayed in the program is data such as age, weight, height, along with recommended of food ingredients and minimum price of each food ingredients.This algorithm consists stages of initialize particles, calculating fitness value, define pbest and gbest value, calculating velocity and position of particles. The results from this research, it is found that the optimal parameters are the number of particles are 40 particles, the value of ωmax is 0,75, the value of ωmin is 0,25, the value of C1 is 2, the value of C2 is 2 and the number of maximum iterations are 80 iterations. The results of the program using these parameters resulted in an average difference from actual patients data and the results from the program of 4,67%. Moreover, the result of this research can reduce expenses up to 14,68%.
Implementasi Metode Klasifikasi Fuzzy K-Nearest Neighbor (FK-NN) Untuk Fingerprint Access Point Pada Indoor Positioning Baiq Findiarin Billyan; Adhitya Bhawiyuga; Rakhmadhany Primananda
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

Positioning is a technique used to determine the position of an object. There are two types of positioning technique: outdoor positioning and indoor positioning. An example of a system that can be used to measure outdoor positions is the Global Positioning System (GPS). GPS is a very common technology that known to know a position and as a pointer for displacement of objects through signals from satellites. GPS can provide good positioning in an outdoor environment, but the signal is very weak when used in a closed / indoor environment. Accordingly then developed a technology that serves to know the position of an object in indoor called Indoor Positioning. In this research we implements Indoor Positioning with Fingerprint method (signal strength recognition method) using measurement of signal strength (Received Signal Strength/RSS), that is by analyzed patterns strength of signal access point coming to receiver from every room. The first thing we did is to collect training data first as a basis for classification, then give the label. Next, we create a classifier based on training data. After that we re-measure as data testing to test its accuracy by Fuzzy K-Nearest Neighbor (FK-NN) classification method, and to make it easier to access the classifier that has been made, we use web service. The result of client position gives an accuracy level on K-Nearest Neighbor (K-NN) method with value k = 1 has value reaches 96%, for k=2 to k=7 has value reach 76%, and for k=8 to k=10 has value reach 73%. Meanwhile, FK-NN method with value k=1 and k=2 has value reach 96%, for k=3 to k=8 has value reach 76%, for k=9 has value reach 73%, and for k=10 has value reach 76%. Therefore, the implementation of Fuzzy K-Nearest Neighbor (FK-NN) classification method for Fingerprint Access point on Indoor Positioning has an enough accuracy level than the K-NN method.
Pengembangan User Interface Aplikasi Guide Me! Berbasis Web dengan Pendekatan Human-Centered Design Mohamad Rendiansah; Hanifah Muslimah Az-Zahra; Mochamad Chandra Saputra
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

Traveling is an activity that can be done for spending holiday. However, the tour guide is still limit so that Guide Me! was made. Guide Me! is a system web-based that can help traveler who visited East Java for searching tour guide. This research focus on how developing user interface Guide Me! with involving user. A Method that can be involve user through the development is Human-Centered Design (HCD). HCD is a method for developing interactive system that focusing on making system that can be used and useful. This research will discuss about developing user interface Guide Me! from context of use, user requirement, making design solution and evaluating design solution. The result from this research showed that user interface design after applied HCD had better usability than before applied HCD. For effectivity aspect, the result was 96% for traveler and 96% for tour guide. For efficiency aspect, average time result was decreased than average time result in first design. Then, for user satisfaction, the result was better because it has fifteen statements good and only one statement bad for traveler and thirteen statements good and three statements bad for tour guide.
Manajemen Bandwidth dan Manajemen Pengguna pada Jaringan Wireless Mesh Network dengan Mikrotik Galeh Fatma Eko Ardiansa; Rakhmadhany Primananda; Mochammad Hannats Hanafi Ichsan
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

The development on the topology of the Internet network is now very wide, one of them is the topology of wireless mesh network (WMN) which has several advantages compared to other wireless based network. From these developments, the use of the Internet on each user in one network can become irregular without any bandwidth management and user management. Based on these problems, the need for research that can be applied user management and bandwidth management in WMN topology, so it can be used to monitor internet usage in accordance with bandwidth management and user management. This research uses 4 nodes that make up WMN topology, one of them as a gateway that is connected directly with mikrotik and local server as database storage media to perform user management. Mikrotik main role is for bandwidth management in accordance with commands provided by the server so that bandwidth usage can be controlled in accordance with the bandwidth owned by the user. From the research finished done, got some conclusion. The first conclusion is the integration of server to mikrotik maupn otherwise can be done well with the results of self-healing test with an average of 27.5 seconds and self-configure 26 seconds. In addition, QoS testing on the network is not solid with an average gain of 10 tests ie the first user (Host 1) uploaded 0.04 Mbps download of 0.512 Mbps, the second user (Host 2) uploaded 0.113 Mbps download of 0.971 Mbps , And a third user (Host 3) uploaded 0.238 Mbps download of 1,942 Mbps, the test also performed on solid network obtained average of first user uploaded 0.051 Mbps download of 0.488 Mbps, second user upload of 0.113 Mbps download of 0.976 Mbps, And the third user uploaded 0.251 Mbps download of 1.962 Mbps, from the test results can be the second conclusion that the bandwidth management is able to do well by the system, and the third conclusion is the user management can be done by the server from the results of design and testing on the system admin . From several test results and three points of conclusion, it can be concluded that the system is able to perform bandwidth management and user management well on the WMN network and WMN network is able to apply self-healing and self-configure well.
Optimasi Fuzzy Inference System Mamdani Menggunakan Algoritme Genetika untuk Menentukan Lama Waktu Siram pada Tanaman Strawberry Agung Nurjaya Megantara; Budi Darma Setiawan; Randy Cahya Wihandika
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

Soil is a crusial component for plant growth. There are many parameters that used for soil examination, and one of its parameter is soil's dampness. Soil Laboratory Balai Pengkajian Teknologi Pertanian Jawa Timur is one of the work units that has a duty to examine the soil for plant nursery purpose. However, due to the conventional tools that they used sometimes the examination result is not as accurate as they expected. Because of that problem the author did some research to make a smart computing system that can be implemented on a tool that can maintain the soil's dampness automatically. Fuzzy Inference System Mamdani is used to calculate how long does it take to water the plants by using two variable inputs; initial dampness and water volume. Genetic algorithm is used to get an optimal membership function by optimizing the boundaries of each membership function. The output of this research will display the optimal time to water the plants. From the examination result we got an error value for about 2,516651, but after optimization the number is reduced to 0,000121. With that result we can conclude that using Fuzzy Inference System Mamdani and optimized with genetic algorithm is able to calculate how much time that it takes to water the plants and still able to get a good outcome. Keywords: Plants, fuzzy inference system, Mamdani, genetic algorithm, optimization
Optimasi Support Vector Regression (SVR) Menggunakan Algoritma Improved-Particle Swarm Optimization (IPSO) untuk Peramalan Curah Hujan Husin Muhamad; Imam Cholissodin; Budi Darma Setiawan
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

Climate change that happens because of global warming also cause change in rainfall patterns. Knowing rainfall patterns is really important for some activity and works. So, rainfall forecasting is needed to understand the rainfall patterns in the future. One of the method used in forecasting is Support Vector Regression. But, SVR still has weakness in determining the right values for the parameters. So, an optimization algortithm is needed to help determining the values of the parameters in SVR. The purpose of this research is to do rainfall forecasting in Pujon area, Malang using Support Vector Regression that's been optimized by Improved-Particle Swarm Optimization. Optimization of SVR is done for getting the optimal values of SVR's parameters. The optimized SVR's parameters are (learning rate constants), (complexity), (Hessian's coefficient), (error rate) dan (kernel's coefficient). The rainfall forecasting for the first ten days of January from 2007 until 2015 by using IPSO-SVR resulted value of 0.213389 in RMSE compared to using only SVR which resulted value of 25.839085 in RMSE. This proved that optimization of SVR using IPSO is better compared to using the unoptimized SVR.
Optimasi Biaya Bahan Menu Makanan bagi Penderita Penyakit Jantung dengan Menggunakan Metode Evolution Strategies Veronica Kristina Br Simamora; Imam Cholissodin; Mochammad Ali Fauzi
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

People who suffered heart disease should get serious handling. Not only taking medicines regularly, maintaining diet and nutritional intake for the body is also important. The price of the food ingridients which tend to be unstable makes it difficult for patients to consume foods in meeting their nutritional needs. This research used evolution strategies algorithm to optimize the cost of food ingidients for people with heart disease. Evolution strategies algorithm consists stages of initialization population with the real-vectors chromosome representation, reproduction method using intermediate recombination, and mutation, evaluation, and selection with method called elitism. The parameters were tested by the number of population testing, number of offspring testing, number of recombination testing, and generation testing. The greater the number of populations, number of offsprings, and generations does not guarantee produce more optimal results. The greater the number of population, the number of offspring, and many generations will bring up the various chromosomes, so the chances of this algorithm produce more optimal results will be even greater. This result can happen because the basic concepts of evolution strategies algorithms that use random values in the calculation process. Number of recombination testing indicates that the fewer parent's chromosomes involved in recombination will result a varied number of offspring's chromosomes. The more varied the result of offspring's chromosomes then the chances to achieve optimal results are greater. From the parameter tests results, this research obtained that the system can meet the nutritional needs of patients using the initial 105 population, 430 offspring produced, involving 2 parents on recombination, and 400 generations. Comparison of recommended food system recommendations with expert recommendations shows that the system has provided more optimal results compared to expert recommendations. This proved that the system delivers recommendations with cheaper prices and foods that varies.
Implementasi Metode Improved K-Means untuk Mengelompokkan Titik Panas Bumi Al-Mar'atush Shoolihah; Muhammad Tanzil Furqon; 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

Disaster is an incident or a series of incidents that threaten and disturb people's lives and livelihoods caused by both natural and / or non-natural factors. One of the disasters that happen is fire. Fire is a flame that occur either in small or large size, burning in an unexpected area and difficult to control. Therefore, early prevention is needed. one of the way is with geothermal point which is detected by the satellite. It is used as the indicator of land and forest fires in a region, so that the more geothermal point exist, the more potential for landfill incidents in a region. Hence, it is necessary to implement a system that can cluster the geothermal point data that has the potential in causing fire with farious status such as high, middle, and low potential. Improved K-Means is one of the most popular clustering methods and it can be used for geothermal point grouping. This algorithm performs clustering process based on the maximum distance as the cluster center and the cluster center distance will be calculated with the other data to be grouped. The calculation is done continuously until the data clustering does not change. That case is proven in this research where the evaluation result that uses silhouette coefficient give the highest point of 0.908000874 for the value of cluster 2 and the amount of data 700.
Prediksi Nilai Tukar Rupiah Indonesia Terhadap Dolar Amerika Serikat Menggunakan Metode Recurrent Extreme Learning Machine Neural Network Daneswara Jauhari; Imam Cholissodin; Candra Dewi
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

The exchange rate of money by some people who are involved in the economy, especially the inter-state economy is very payed, often influencing one's decision in taking a policy. However, the exchange rate is a very unstable value, has a lot of noise and fluctuation, it is very difficult to predict the exchange rate. Research on exchange rate prediction has become the most challenging research among researchers, and that is considered one of the most important areas of research in international finance. Therefore, an application is needed, which can better predict the exchange rate of Indonesian Rupiah against the US Dollar. In this study the authors use the method of Recurrent Extreme Learning Machine Neural Network (RELMNN), the method can handle time-ordered datasets and can improve the ability of the Extreme Learning Machine (ELM) method in training and adapting. After testing with optimum parameters, and compared with ELM method, we found out that RELMNN method is superior to ELM method with Mean Absolute Percentage Error (MAPE) value of 0.069502%, while ELM method get MAPE 0.090423%.
Optimasi Fungsi Keanggotaan Fuzzy Tsukamoto menggunakan Algoritma Genetika untuk Diagnosis Autisme pada Anak Indra Eka Mandriana; Candra Dewi; Muhammad Tanzil Furqon
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

Autism is a developmental disorder that cause children to experience social disruption in certain areas, such as communications, social interaction, emotional and behavioral symptoms that is difficult to be identified. According to research in autism, the number of children who suffered from autism is estimated to grow every year around the world, including in Indonesia. This research implement Fuzzy Tsukamoto method to optimized genetic algorithm in order to diagnose autism in children, by optimizing the constraints on all fuzzy variables.Chromosome representation that is used in this research is real code genetic algorithm which every chromosome will initialize the limitations on all fuzzy variables. Method that is used to the process of crossover is extended intermediate crossover and random mutation for mutation process while selection method used elitism selection. Based on the results, the system obtained the most optimal parameters on a method of CARS in a population of 50, 200 generations, as well as the combination of Cr = 0.8 and Mr = 0.1 with the fitness of 1, while on the CHAT population method 10, 100 generations, as well as the combination of Cr = 0.9 and Mr = 0.1 with fitness by 1

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