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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Community Empowerment
Randy Cahya Wihandika
Fakultas Ilmu Komputer , Universitas Brawijaya
Arts Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Public Health Social Sciences

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Optimasi Fungsi Keanggotaan Fuzzy Mamdani menggunakan Algoritme Genetika untuk Penentuan Kesesuaian Lahan Tanam Tembakau Fikri Hilman; Budi Darma Setiawan; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 3 (2018): Maret 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

One of the requirements for good quality tobacco is a good land use. Improved quality of the land will result in increased quality and quantity of tobacco plants produced. The main constraints experienced by tobacco farmers in determining land suitability are the limited knowledge and difficulty of obtaining correct data on the quality of land suitable for tobacco plants. Therefore, a computerized system is needed to assist farmers in making decisions on prospective land to be used. This system is implemented using Fuzzy Inference System (FIS) Mamdani and optimized using Genetic Algorithm. Some of the factors used in this system include the percentage of land affected by the disease, the openness of the region, the degree of weight of the soil, the thickness of the layer, the ease of irrigation, terrain conditions, and soil pH. The reproduction method used is extended intermediate crossover and random mutation, while the selection method used is elitism. Based on the results of the tests that have been done, the most optimum solution obtained on the total number for 90 population , the combination of cr and mr value of 0.2 and 0.8 respectively and the number of generations of 500, with the average of fitness value generated of 0,917. The Accuracy generated by this system is 80 % using 10 test data.
Klasifikasi Kualitas Susu Sapi Menggunakan Metode Support Vector Machine (SVM) Puspita Sari; Lailil Muflikhah; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 3 (2018): Maret 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Cow milk has a lot of animal protein and have benefit for children and whoever in process for grow up. Cow milk contains good essential amino acids. Malang Animal Health Laboratory as the unit executor in east java Animal Husbandry Department do a test in kesmavet for efforts to secure milk as a farm product with appropriate testing in suitable with the Indonesian National Standard (SNI). The classification of cow milk quality is still using organoleptic (smell, taste, color) that are linguistic, so that variable and parameter are uncertain and become themain obstacle of expert in determining good milk quality. To resolve this issue, this can be done with schizophrenia classification using support vector machine (SVM) algorithm, which SVM performace is more suitable than other classification methods. In this study there are 269 data that is divided into two data that is data training and data testing with three classification result, that is low, medium, and hight. The result in this paper get the best acuracy based ratio data 50%:50%, with Kernel RBF and λ (lambda) = 0,001, C (complexity) = 0,01, γ (gamma) =0,00001, maximum iteration = 30 and σ kernel RBF= 2. The average result of accuracy using SVM method in cow milk quality classification was 92.82% and highest accuracy was 94.02%.
Implementasi Metode Backpropagation Untuk Klasifikasi Kenaikan Harga Minyak Kelapa Sawit Dwi Rahayu; Randy Cahya Wihandika; Rizal Setya Perdana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 4 (2018): April 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Palm oil is a plantation product that is the main export commodity of Indonesia. The increasing amount of processed materials that can be made by using palm oil makes the rise of oil palm demand. The main factor causing an increase in demand for palm oil is a relatively low price compared to its competitor prices such as soybean oil, sunflower seed oil, peanut oil, cotton oil and rapeseed oil. Price becomes an important factor to determine the selling point of the product. Prices also affect the producer's profit. The classification of the possibility of rising or falling prices of palm oil becomes a major consideration of a consumer to buy. This writing discusses the classification of palm oil prices using Backpropagation method. The Backpropagation method will model the coconut oil price data 5 months earlier to find the classification results in the 6th month. Classification results obtained have an accuracy of 69.57% with the number of hidden neurons as much as 50, the value of learning rate as big as 0.1 and the number of maximum iterations of 70,000.
Implementasi Algoritme Support Vector Machine (SVM) untuk Prediksi Ketepatan Waktu Kelulusan Mahasiswa Arif Pratama; Randy Cahya Wihandika; Dian Eka Ratnawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 4 (2018): April 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Graduate on time is the desire of all students. In reality, not as expected many students who graduated more than four years. necessitating the application of predictive graduation students can classify graduation prediction data based on parameters that have been determined. Because it is necessary for the application of intelligent systems can classify graduation prediction data based on parameters. Algorithm Support Vector Machine (SVM) to classify the data into two classes using kernel Gaussian RBF with a combined value of parameter λ = 0,5, constant γ = 0,01, and ε (epsilon) = 0,001 itermax = 100, c = 1 by using training data as much as 170 datasets , this study resulted in an average accuracy of 80,55 %.
Optimasi Fuzzy Time Series Untuk Peramalan Kebutuhan Hidup Layak Kota Kediri Dengan Menggunakan Algoritme Genetika Tahajuda Mandariansah; Budi Darma Setiawan; Randy Cahya Wihandika
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

Proper living needs (KHL) is a standard requirement for a worker or single person physically can live well for the needs of one month, the value of KHL is one of the five minimum wage determinataion factors. The value of KHL is determined based on survey value from january to september, while in determining regional minimum wage (UMR) shall be done no later than 60 days or two months before january 1st of the following year. Therefore it's necessary to forecast the value of KHL. This forecasting is helpful for the goverment in the process of determining UMR. In forecasting using fuzzy time series method optimized with genetic algorithm. The optimization is done on the interval value in the fuzzy time series method to get good accuracy in forecasting. Based on the results of tests on value of KHL Kediri from 2009 to 2015, using the parameter of the interval number 7, using the combination of Cr 0.9 and Mr 0.5, the population number 1050, and the number of generations 100 using the average forecasting error rate (AFER) has obtained an error value of 4.7211%
Optimasi Pemodelan Regresi Linier Berganda Pada Prediksi Jumlah Kecelakaan Sepeda Motor Dengan Algoritme Genetika Sema Yuni Fraticasari; Dian Eka Ratnawati; Randy Cahya Wihandika
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

Traffic accidents are increasing from year to year according to the Badan Pusat Stastistika record from 1992 to 2003. According to the World Health Organization (WHO), it noted that nearly 3,400 people per day died due to traffic accidents. Surabaya is one of the metropolitan cities in Indonesia. Population growth is quite fast because the city of Surabaya is also the capital of East Java province. The system predicts the area of ​​frequent traffic accidents based on the parameters used such as the length of the road, the width of the volume body, the velocity, the number of lanes, the number of directions, the boundary / median, the plot access and the shoulder width by using linear regression optimized with the genetic algorithm. The genetic algorithm uses real numbers with 10 of gene chromosome lengths. The crossover method used by the extended intermediate crossover while the mutation uses random mutation, and the selection uses elitism selection. From the results of the experiments conducted to produce population is 125, the best combination of cr and mr is 0,6:0,4 and the best generation is 700. Comparison of error rate by showing a lower error value of 0,5% compared with regression Which results in an error value is 1,5%.
Pemodelan Sistem Pakar Diagnosis Penyakit pada Tanaman Tembakau Virginia dengan Metode Dempster-Shafer Chandra Tio Pasaribu; Nurul Hidayat; Randy Cahya Wihandika
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

Knowladge of the nature of the pathogen, symptoms of disease, as well as the factors that influence the development of plant diseases is one of the important things that should be known to determine the appropriate control methods for pathogen targeted. The lack of knowledge possessed by farmers and the lack of consultation with Virginia's Tobacco plant experts has caused farmers to experience delays in handling the affected plants. So, on the problems of Virginia Tobacco plants can be with the creation of an expert system. The method used is Dempster-Shafer is a theory that is capable of handling various possibilities that combine one possibility with existing facts. The Dempster-Shafer theory is based on belief function and plausible reasoning used to combine separate pieces of information to calculate the probability of an event. In this study there are 9 types of disease in Virginia Tobacco plant with input system in the form of facts that occur in Virginia Tobacco plants. Based on the data used obtained accuracy value of 84.6% so it can be concluded the system goes well.
Penyelesaian Multiple Travelling Salesman Problem (M-TSP) Dengan Menggunakan Algoritme Genetika: Studi Kasus Pendistribusian Barang Di Kantor Pos Lumajang Anang Hanafi; Randy Cahya Wihandika; 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

Online buying and selling currently more and more in demand by all societies, the provider of application companies that bring together sellers and buyers also do not stop releasing promotions on every occasion. The increasing of online trading market it caused the rise of goods delivery process. The freight forwarding company also strives to provide the best service in delivery process. The companyy also need to minimize the cost to be made during the shipping process. In the post office company, especially in Lumajang had 4 sales and 16 delivery destinations, the problem is called Multiple Traveling Salesman Problem (M-TSP). This research discussed issues for optimized the distance, weight, and volume of goods to be delivered from the starting point to some point of destination. From the research that had been done in this case by using genetic algorithms optimal parameters were obtained with a population size of 200, the maximum generation of 500, with a combination of crossover rate 0.4 and mutation rate 0.6 and also uses elitism selection methods and the result of fitness was 0,05288.
Segmentasi Pembuluh Darah Pada Citra Retina Menggunakan Algoritme Multi-Scale Line Operator dan Preprocessing Data dengan K-Means Winda Cahyaningrum; Randy Cahya Wihandika; Agus Wahyu Widodo
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

The vascular changes that occur in retinal are precursors of a diseases, such as heart disease, diabetic retinopathy, stroke and hypertension. Changes can be seen by analyzing retinal image, but it takes a long time. In this study we propose the automation of vascular segmentation processes in retinal image so that can assist in analysis process, which is an important step in retinal image analysis. The segmentation process is done by detecting the line using the Multi-Scale Line Operator algorithm and preprocessing image using K-Means algorithm. Line detection is performed on several different scales, then combines the results of each scale. Image preprocessing using the K-Means algorithm aims to ignore the optic disc area, which in that area will probably be detected as false positive. The performance of proposed algorithm was evaluated using the DRIVE and STARE dataset, the result showed that average accuracy of the DRIVE dataset reaches 0,940980219 with AUC 0,7462, and for STARE dataset reaches 0,949293361 with AUC 0,778. The results are obtained by using the number of K as much as 3 on the K-Means algorithm, which consists of background, foreground, and vessel.
Implementasi Metode Binary Decision Tree Support Vector Machine (BDTSVM) untuk Klasifikasi Penyakit Gigi dan Mulut (Studi Kasus: Puskesmas Dinoyo Malang) Nindy Deka Nivani; Muhammad Tanzil Furqon; Randy Cahya Wihandika
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

Teeth and mouth are gates for entry of germs and bacteria that can interfere with health. Complaints against dental and mouth disease are mostly complained by most people in Indonesia, this is corroborated by the fact obtained data from PDGI (Persatuan Dokter Gigi Indonesia) which states that 87% of the people of Indonesia suffer from toothache and among them do not check his teeth to the doctor . Seeing this dentist has an important role in determining the right classification of dental and oral diseases so that patients can immediately treat the disease that is suffering. This research implements the method of Binary Decision Tree Support Vector Machine (BDTSVM) to help classify dental and oral diseases. The Binary Decision Tree method is used to construct binary trees in order to separate classes into two groups, positive and negative. While the Support Vector Machine method is used for the classification process. In this study used 4 kinds of testing that is the test of maximum iteration, lambda parameters, gamma parameters, and complexity parameters. The results obtained from this research is the classification of dental and mouth disease with 6 classes of diseases. Based on the results of the tests that have been done, the average accuracy of 94.28% using the parameter values lambda = 0.5, parameter complexity = 0.1, parameter gamma = 0.01 and maximum iteration = 5
Co-Authors Achmad Arwan Achmad Ridok Achmad Yusuf Adam Hendra Brata Adam Sulthoni Akbar Adinugroho, Sigit Aditya Putra Pratama Agi Putra Kharisma Agung Nurjaya Megantara Agus Wahyu Widodo Akhmad Sa'rony Amar Ikhbat Nurulrachman Anang Hanafi Angky Christiawan Rongre Ani Enggarwati Ardisa Tamara Putri Ardiza Dwi Septian Arif Pratama Arynda Kusuma Dewi Barlian Henryranu Prasetio Bayu Kusuma Pradana Bayu Laksana Yudha Bayu Rahayudi Budi Darma Setiawan Budi Dharma Setiawan Candra Dewi Chandra Tio Pasaribu Cindy Cunday Cicimby Cornelius Bagus Purnama Putra Cusen Mosabeth Dani Devito Daris Hadyan Tisantri Denny Sagita Rusdianto Devinta Setyaningtyas Atmaja Dhan Adhillah Mardhika Dhanika Jeihan Aguinta Diajeng Sekar Seruni Dian Eka Ratnawati Dimi Karillah Putra Dito Rizki Pramudeka Dizka Maryam Febri Shanti Dwi Rahayu Eka Putri Nirwandani Emma Wahyu Sulistianingrum Ersya Nadia Candra Fachril Rachma Zulfidar Fachrur Rozy Faizatul Amalia Fajri Eka Saputra Fanny Aulia Dewi Fera Fanesya Fida Dwi Febriani Fikri Hilman Firda Oktaviani Putri Fitra Abdurrachman Bachtiar Frisma Yessy Nabella Gilang Widianto Aldiansyah Glenn Jonathan Satria Gregorius Ivan Sebastian Hafiz Ari Putra Hamim Fathul Aziz Heykhal Hafiddhan Rachman I Gusti Ngurah Ersania Susena Imam Cholissodin Indriati Indriati Irnayanti Dwi Kusuma Jonathan Reynaldo Kevin Haidar Kevin Nastatur Chatriavandi Koko Pradityo Lailil Muflikhah Lalu Muhammad Ivan Natania Latifa Nabila Harfiya M. Rikzal Humam Al Kholili Moh. Dafa Wardana Mohammad Rizky Hidayatullah Muchlas Mughniy Muh. Arif Rahman Muhamad Ilham Dian Putra Muhamad Wahyu Budi Santoso Muhammad Alif Fahrizal Muhammad Amin Nurdin Muhammad Faiz Abdul Hamif Muhammad Ihsan Diputra Muhammad Shidqi Fadlilah Muhammad Tanzil Furqon Muhammad Tegar Kanugroho Naufal Akbar Eginda Nindy Deka Nivani Nova Amynarto Novanto Yudistira Nur Wahyu Ningtyas Nurul Hidayat Nurul Muslimah Pindo Bagus Adiatmaja Pupung Adi Prasetyo Puspita Sari Putra Pandu Adikara Putu Gede Pakusadewa Qurrata Ayuni Raden Rafika Anugrahning Putri Ratih Kartika Dewi Rayindita Siwie Mazayantri Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Rizal Setya Perdana Rizky Nur Ariyanti Ruri Armandhani Sarah Najla Adha Satria Dwi Nugraha Satyawan Agung Nugroho Sema Yuni Fraticasari Sevtyan Eko Pambudi Sigit Adinugroho Siti Robbana Sukma Fardhia Anggraini Supraptoa Supraptoa Sutrisno Sutrisno Tahajuda Mandariansah Threecia Agil Regitasari Tifo Audi Alif Putra Tri Kurniawan Putra Utaminingrum, Fitri Valen Novandi Kanasya Vandi Cahya Rachmandika Winda Cahyaningrum Yosendra Evriyantino Yosua Christopher Sitanggang Yudha Prasetya Anza Yuita Arum Sari Yurdha Fadhila Hernawan