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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Randy Cahya Wihandika
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Deteksi Tepi Danau Pada Citra Satelit Menggunakan Metode Canny Koko Pradityo; Budi Darma Setiawan; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 3 (2017): Maret 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Lake is an important land feature for human life. Changes in a lake's condition would affect the environment and the people living nearby. One of the method being used to detect changes in lake's condition is by using an edge detection of the lake based on satellite image for further analysis such as measuring the change in lake's total area. Appropriate implementation and optimization of such algorithm can lead to a better analysis of the lake's condition. In this research, the system implemented Canny Edge Detection algorithm to detect the edge of a lake on a satellite image. A segmentation algorithm based on color thresholding is used to improve the edge detection algorithm. The test result shows that Canny Edge Detection algorithm has 57% error detection rate, while segmentation process using color thresholding improves the detection performance by 67%.
Penerapan Fuzzy K-Nearest Neighbor (FK-NN) Dalam Menentukan Status Gizi Balita Satria Dwi Nugraha; Rekyan Regasari Mardi Putri; Randy Cahya Wihandika
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

Infants or so-called children is a group that have an important period in physical growth. Infants itself is categorized as a group of children between age 1 to 3 as a teddler group, and age 3 to 5 as a pre-school group. Some says children has a big role in order to attaining of growth success in the future for human, hence they call it as the golden age of living. Children's growth not only discribing as an increasing of body dimensions but also as the continuity of intake and nutrient needs. An indicator to know the children's health is by determining their nutritional status. Based on SK Minister of Health in Indonesia, they use a method called anthropometry to determining children's nutritonal status. While this method only reviewing 4 internal factors, there're some other factors which influence of children's nutritional status itself such as genetic, disease, education, knowledge, and income. Therefore Fuzzy K-Nearest Neighbor is used in this study as a classifiaction method that can determining children's nutritional status because this method using the data training as the knowledge to clasify and would adjust other factors of nutritional status itself right in the future. From the test results of the study, this system can clasify well with maximum accuracy of 84,37% when using 160 training data with k value = 4.
Verifikasi Citra Tanda Tangan Berdasarkan Ciri Pyramid Histogram of Oriented Gradient (PHOG) Menggunakan Metode Klasifikasi K-Nearest Neighbor Latifa Nabila Harfiya; Agus Wahyu Widodo; Randy Cahya Wihandika
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

Signature have been widely accepted by people as one of many tools that used to verify a person's identity. Signature verification is highly needed in order to avoid crimes regarding signature's validity. The process of signature image verification uses feature extraction based on Pyramid Histogram of Oriented Gradient (PHOG) for extracting feature from global to local image area that used for the next process, classification using K-Nearest Neighbor method. There are some parameters that can affect the feature extraction of PHOG and K-NN as classification method such as number of bin, level, range of angles, and K. As for the additional parameters, namely the amount of training data that affect the overall results of the classification used. Feature extraction and classification by the method with the best parameter values and training data used produces the highest accuracy of 99.5% on Indonesian original signature data and 98.5% on the data of the Persian original signatures. While the forgery signatures data produces accuray only as much as 56% on data from Indonesia and 35,5% on data from Persian. Results from tests show that the algorithm is not good enough for distinguishing forgery signature that has high similarity with genuine signature even it is works well for recognizing genuine signature.
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
Klasifikasi Standar Produk Baja PT. Krakatau Steel (Persero) Tbk. Berdasarkan Komposisi Kimia dan Sifat Mekanis Baja Menggunakan Fuzzy K-Nearest Neighbor (Fuzzy K-NN) Ardisa Tamara Putri; Muhammad Tanzil Furqon; Randy Cahya Wihandika
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

The occurrence of chemical composition deviations or mechanical properties in steel production causes the clasification of steels based on standards can't be defined. The deviation that occurs is the deviation from the maximum limit of the chemical composition and the minimum limit of the mechanical properties of steel. This is the background of researchers to create a system using the Fuzzy k-Nearest Neighbor method. The Fuzzy k-Nearest Neighbor (Fuzzy K-NN) method used for classifying steel standards based on the chemical composition of the steel produced. The data used for this study is data steel products with the specifications of the steel composition, the mechanical properties of the steel and the classification of standard of steel produced. The steps performed are data normalization, Fuzzy k-Nearest Neighbor, calculate Euclidean distance, take the shortest distance k, calculate the membership value of each class and determine the target class. The highest accuracy resulted by testing k values using k-fold cross validation is 74,44% with k value equal to 74,44 and total of training data is 267 data.
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.
Optimasi Komposisi Menu Makanan bagi Penderita Tekanan Darah Tinggi Menggunakan Algoritme Genetika Adaptif Raden Rafika Anugrahning Putri; Muhammad Tanzil Furqon; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 2 (2018): Februari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

High blood pressure or commonly called hypertension is a disease that can affect anyone. High blood pressure is one disease that can cause other diseases, such as heart attack and stroke. Blood pressure is high if systolic blood pressure is more than 140 mmHg and diastolic blood pressure is more than 90 mmHg. One thing that most affect the high blood pressure is an unhealthy diet. To set a healthy diet for people with high blood pressure then need to set the composition of foods with the needs of the body. A technique to get solution of foods for people with high blood pressure is by applying Adaptive Genetic Algorithm. Adaptive parameters are applied to the reproduction process mutation. The data used in the test is 146 Data of food ingredients classified into staple food, vegetable sources, sources of animal, vegetable and complementary. On this process of Adaptive Genetic Algorithm is used the permutation represented with integer with a length of chromosome 15 genes represented each digit of the number of food, methods of crossover with single-point crossover and mutation methods with reciprocal exchange mutation and elitism selection. As the results, the test performed obtained optimal parameters is the measure population of 200 individuals with an average fitness of 0,0774665, 90 generations with the average fitness of 0,0774665 and combinations cr = 0,8 and mr = 0,2 with the average fitness of 0,0780737.
Prediksi Tingkat Keuntungan Usaha Peternakan Itik Alabio Petelur menggunakan Jaringan Syaraf Tiruan Backpropagation (Kasus di Kabupaten Hulu Sungai Utara Kalimantan Selatan) Muhammad Ihsan Diputra; Candra Dewi; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 2 (2018): Februari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Predicting profits in ducks farming business is very hard to do. That's because in alabio duck agribusiness system have subsystems that can effect other subsystems. If the subsystems don't have optimal value it can make a bad impact for profits in business. To overcome this problem, this study using backpropagation artificial neural network to predict profit in alabio duck eggs business. This study using backpropagation algorithm because this algorithm often used for forecasting. The subsystems or input features used in this study are number of adult ducks, shrinkage of duck seed price, total food price, shrinkage of cages price, labor costs, and the cost of vaccines and medicine. The system in this study use net profits of duck eggs business as output. In this study, testing used to get the optimal value for each parameter. The values of each parameters are learning rate 0.8, 17 hidden neuron, MAPE learn threshold 10%, and 90% total data training. The best MAPE for forecasting result is 25,7852%.
Klasifikasi Risiko Hipertensi Menggunakan Metode Neighbor Weighted K-Nearest Neighbor (NWKNN) Bayu Laksana Yudha; Lailil Muflikhah; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 2 (2018): Februari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Hypertension or called high blood pressure caused high risk of death in Indonesia. This could trigger sustainable effect to other diseases such as heart attack and kidney failure. According to WHO, as many as 30% of Indonesians are sufferers hypertension, Indonesian Hypertension Doctor Association also said that 76% of cases of hypertension can not diagnosed earlier and therefore hypertension is called a silent killer. The way to handling hypertension earlier is by early detection of hypertension in form of Early Alertness System (SKD). In this research will classified risk of hypertension based on medical record using Neighbor Weigted K-Nearest Neighbor (NWKNN) classification method. This method is the development of the KNN method. In NWKNN there is a weighting process in each class of hypertension risk. In this study, the classification of hypertension into 4 risks that is Normal, Pre Hypertension, Stage 1 and Stage 2. The results of this research shows that the NWKNN method is able to classify the hypertension risk well when tested on 100 training data, 25 testing data, K score=10, and E score=4 with accuracy result that reached 88%.
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.
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 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 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 Rizky Nur Ariyanti Ruri Armandhani Sarah Najla Adha Satria Dwi Nugraha Satyawan Agung Nugroho Sevtyan Eko Pambudi Siti Robbana Sukma Fardhia Anggraini Supraptoa Supraptoa Sutrisno Sutrisno 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