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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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Pemilihan Rute Optimal Penjemputan Penumpang Travel Menggunakan Ant Colony Optimization Pada Multiple Travelling Salesman Problem (M-TSP) Yosua Christopher Sitanggang; Candra Dewi; Randy Cahya Wihandika
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

Multiple salesman problem (M-TSP) is an advanced problem from TSP that is looking for minimal cost from tour in some location which can only be visited once. There are many problems that are included in the case of M-TSP, one of them is the passenger pickup route. Choosing the right path in the process of picking up passengers will certainly affect the effectiveness and cost in those activities. Ant colony optimization (ACO) is an algorithm that adopts the intelligence of a group of ants in a food search and able to solving the M-TSP problem. In this study there are two parameters used in finding the best solution that is distance and time. In equalize the value of distance and time parameters, applied min-max normalization in data. The best results are obtained when the parameter NcMax or iteration is 300, the value of α is 0.5, the value of β is 0.5, the value of τ0 is 0.5, the value of ρ is 0.5 and the number of passengers in one car as much as 5 with cost 148.829.
Penerapan Hibridisasi Algoritme Genetika dan Simulated Annealing untuk Optimasi Vehicle Routing Problem pada Kasus Pengangkutan Sampah Kota Denpasar Putu Gede Pakusadewa; Candra Dewi; Randy Cahya Wihandika
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

Handling municipal garbage is one of the problems that exist in a big city including the city of Denpasar. The amount of waste on certain days such as religious holidays will increase significantly where the 4-shift schedule used is inadequate to transport all the waste at certain TPS. Determination of the optimal route of garbage transportation is needed to save work time, lower operational costs and capable to transport all the waste. This research applies hybrid genetic algorithm and simulated annealing to optimize municipal garbage collection transportation route. The representation of chromosomes used is permutation representation with two segments namely the route segment and the truck segment. The process stage uses crossover with order crossover method and mutation with one-cut point method. The test results show the best fitness value is 1,042568623 with optimal parameters using population number = 400, crossover rate and mutation rate = 0.9 and 0.1, number of generations = 200, initial temperature = 1000, final temperature = 1, and alpha/cooling rate = 0.1. The result of this research is recommendation of optimal transportation route to collect garbage from a number of TPS.
Pengenalan Emosi Berdasarkan Ekspresi Mikro Menggunakan Metode Local Binary Pattern Nova Amynarto; Yuita Arum Sari; Randy Cahya Wihandika
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 basic human emotions have been widely investigated cross-culturally, one of them by using facial expressions. Through the micro expression on the face can be known even one's psychological emotions. Basic expression is universal means that the child or the blind can know or form a basic expression. Micro expression is an expression that appears subtle and unconscious. Micro expression is very difficult or even can not be hidden. This research uses Local Binary Pattern (LBP) method to get features of facial micro expression and classification using K-Nearest Neighbor (K-NN) method to determine the emotion of micro expression. The result of k-value determination test on K-NN classification method shows that when k value 5 and 7 is able to recognize emotion based on micro expression with 56,03% accuracy. The result of determination test of R value and P value on LBP method showed an increase of accuracy in emotional recognition to 63,83%. The test results on the dimension of the image shows that the dimension of the image that produces the best accuracy is 200×200 pixels with an accuracy value of 63.83%. The observation using distance method on K-NN classification shows that Manhattan distance calculation method can increase accuracy in emotional recognition to 70.21%.
Penerapan Algoritma Evolution Strategies Dalam Permasalahan VRPTW Pada Optimasi Pendistribusian Pupuk Lalu Muhammad Ivan Natania; Randy Cahya Wihandika; Suprapto Suprapto
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

Distribution is one of important aspects of marketing. Distribution is a process of transporting goods to consumers by supplier. Without good planning, the distribution process cause loss and damages for the distributor and also the retailers. The loss could be form the cost of fuel and also the time consumed. As for the retailers, goods supply is a crucial element for their business process. To minimize loss, a system is needed to determine the route of delivery with distance and service time as consideration due to limited capacity of container. Vehicle Routing Problem with Time Windows (VRPTW) is the main issue of this research. VRPTW needs great computational processing to deliver good quality of solution. Therefor methods are required to manage and solve the VRPTW issue. Evolution Strategies algorithm is one of many that could be use as a solution of this matters. Based on the experiments, the highest fitness is 0,52421 where the population size is 100, the offsprings size is 10, the generations size is 100, and the SP value is 5. The lowest fitness is 0,45145 where the offspring size is 1, populations size is 100, the generations size is 50, and the SP value is 3.
Optimasi Kandungan Gizi Dan Biaya Bahan Pangan Pada Makanan Sehat Untuk Penderita Kolesterol Tinggi (Dyslipidemia) Menggunakan Algoritma Evolution Strategies Rayindita Siwie Mazayantri; Randy Cahya Wihandika; Sutrisno Sutrisno
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

Nowadays there are changes that occurring in our community, especially in technology department, that causes changes in lifestyle which results in imbalanced nutrition. Something like this could lead the body to catch symptoms of dyslipidemia, which is a disease wherein the level of blood lipids is high and hence higher possibilities of causing many more dangerous diseases. To reduce the level of cholesterol, it is highly recommended to examine the food contents and ingredients. For some people, it may not be easy to manage what ingredients they should consume due to lack of knowledge in that aspect, so to solve the problem we could apply Evaluation Strategies method, which has initialization process of chromosome representation as real-vector. In this study, the ES cycle that we apply is (µ+λ) that only requires mutation without recombination. The next process is fitness calculation, and evaluation, and then do the selection process. From the testing of parameters, we can conclude that the system can yield the most optimized results when the size of population is set to 120, offspring is set to 160, and generation is set to 40. A solution that the system can come up with compared to the experts' recommendation shows that the solution this system gave is more optimal, with 2.2825 as a fitness value, higher than the fitness that we get from experts' recommendation which only 0.4003, so the system can provide recommendations for cheap ingredients while reckoning the needs for nutrients intake of the patients.
Implementasi Metode Triangle Geometry Untuk Pengenalan Arah Pergerakan Kepala Irnayanti Dwi Kusuma; Fitri Utaminingrum; Randy Cahya Wihandika
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

Nowadays, applications that detect head or face are popularly used as device securing, virtual and augmented reality, computer games, and device control. However, people with physical disabilities have constraints to control the system, on the other hand there are also constraints on normal users who use headpieces to control the system that is the cost allocation for headpiece purchases. Identification of head direction movement using Triangle Geometry Method could be implemented into a system that utilizes input as a control. Utilization of inputs as controls can make easier for people with disabilities to use a system and use it interactively. In addition, this topic can help reduce the cost of system requirements and does not complicate the user, such as using a special device that put on the user's head to control a system. Skin color detection, eyes, and nose are phases that used on this topic to build a system of face detection and head direction movement. This research focuses on the success of systems that can recognize the direction of head movement with the state of the head in real-time. The direction of the head is up, down, right and left. The system processes the value of yaw, pitch, roll with triangle geometry method so it can get a range values ​​for each direction of head movement. The accuracy value of each direction is 88% for the upward direction, 82.6% for the downward direction, 84.6% for the right direction and 73.5% for the left direction. So, this system can be implemented as control input.
Prediksi Harga Pasar Daging Sapi Di Kota Malang Dengan Menggunakan Metode Extreme Learning Machine (ELM) Cusen Mosabeth; Muhammad Tanzil Furqon; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Beef is one of the basic needs whose existence is greatly increased in Indonesia. The need to consume beef is very sharp in proportion to the increase in population and the awareness of the importance of consuming very high nutritious foods. Basically the need for animal protein cannot be replaced with other proteins. Estimating future consumer demand by making production plans a challenge for an industry. This makes predictions play an important role. Effective and efficient design must be supported by an accurate prediction system. ELM Is an artificial neural network consisting of feed-forward with one or hidden layer-forwad neural. Therefore, in this study the author uses the Extreme Learning Machine (ELM) method. The experimental results showed that the ELM method had a good error measured by the Mean Absolute Percentage Error (MAPE) error rate of 0.344% using the ratio of the training data 90%: 10%, the input weight range between -1 and 1, the number of neurons in the hidden layer 7, then use the binary sigmoid activation function, and use the number of features 3. The results are proved by using the method of Extreme Learning Machine can predict the price of beef with accurate and precise and get the price of beef in the future.
Optimasi Parameter Support Vector Machine (SVM) dengan Particle Swarm Optimization (PSO) Untuk Klasifikasi Pendonor Darah Dengan Dataset RFMTC I Gusti Ngurah Ersania Susena; Muhammad Tanzil Furqon; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Blood donation is one of voluntary humanitarian activities. Blood is one of the most important substances that humans have in the human life cycle. In carrying out blood donation activities, monitoring the stock availability of blood bags is usually a major problem. To know ammount stock of blood bag we need a system that can predict the behavior of blood donors. RFMTC (Recency, Frequency, Monetary, Time, Churn Probability) is a modified RFM method in order to see the behavior of donors who can donate their blood or not to donate again. Therefore, SVM-PSO method needed to know classification of blood donors behavior. With SVM techniquesto find hyperplane that is the dividing line between data classes. Then the PSO technique to find the range of input parameters that SVM needed to get the optimal hyperplane value. This research uses 748 data from UCI dataset with 4 main features and 2 classes. Based on the test that has been done obtained the accuracy of 90% with the value of learning rate SVM small and the value of the number of PSO particles are low.
Diagnosis Penyakit Tanaman Melon Menggunakan Metode PROMETHEE Dito Rizki Pramudeka; Nurul Hidayat; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Cultivation of melon plants requires optimal care and appropriate environmental conditions, as they are susceptible to pest and disease infections. This leads to crop failure due to errors from the handling and selection of the pesticides used in tackling them. The agricultural extensions at this time are still have some difficulty to identify the diseases that attacked the melon plants despite the clear differences between each melon plants and determine the solutions for handling and to eradicate the disease. Based on the said problems, a melon plants' diseases diagnosing system is designed. The Promethee method can be used as a decision-assisting method by comparing the symptoms of one disease with another using the criteria of preference. In the melon plants' diseases diagnosing system using Promethee method's main functions are calculating the value of paired comparison deviation for each disease and calculate the value of stream flow in the form of Entering Flow, Leaving Flow, and Net Flow. The melon plants' diseases diagnosing system using 30 test data resulted in an accuracy rate of 86.67% by using Usual and Gaussian preference criteria. The difference in the level of accuracy in each type of preference is determined by the weight of each symptom from each disease as well as the indifference threshold and the preference threshold used in the calculation.
Implementasi Metode F-KNN (Fuzzy K-Nearest Neighbor) Untuk Diagnosis Penyakit Anjing Dizka Maryam Febri Shanti; Nurul Hidayat; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Dogs are one of the favorite animals used as pets. When petting and playing with dogs, oxytocin, stress-related and relieved hormones are released, helping to lower blood pressure as well as cortisol levels. Although dog maintenance has many benefits, the owners should be careful in caring for their dogs. Not a few dogs are attacked by various diseases caused by viruses, protozoa, bacteria and parasites. Dogs who are sick if not immediately get treatment and treatment have the risk of transmitting to dogs and other animals or even to humans. The method used Fuzzy K-Nearest Neighbor. (FK-NN) is a variant of K-Nearest Neighbor (K-NN) method with fuzzy technique. The FK-NN method assigns a class membership value to the sample vector instead of placing the vector in a particular class. FK-NN can be implemented for the diagnosis of diseases in dogs by several stages: calculating the distance between the train data and the test data, taking the smallest distance between the train data and the test data as much as K, Fuzzification and Defuzzification, Class with the highest defuzzification value used as the class for the result classification. The value of K affects the accuracy of the system where the higher the value of k then the tendency of accuracy will decrease. The highest accuracy obtained from the test results is when K = 5 ie with a value of 98.67%.
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