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All Journal Bulletin of Electrical Engineering and Informatics Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Knowledge Engineering and Data Science
Agus Wahyu Widodo
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Prediksi Jumlah Follower Official Account Line Menggunakan Regresi dan Algoritma Genetika Nizar Riftadhi Prabandaru; Rekyan Regasari Mardhi Putri; 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

This research used a case study of LINE IKI MALANG official account. The result of the interview showed that LINE IKI MALANG did not have a basis of its marketing service price change. Therefore, the author tried to provide assistance by giving a basis for any price change of the marketing service based on the predicted number of its followers on each month. The method used in this research was a regression method built with genetic algorithm. Regression was used to predict the followers, while the genetic algorithm was used to optimize the variables that influenced the predicted result. To find optimal predictive results, every optimized variable will be tested on a particular vulnerable numbers. But from the experiment, the researcher got a non-optimal result which was 7,801E-03 because of the minimum data so that the prediction was not close to the training data.
Pengelompokan Lagu Berdasarkan Emosi Menggunakan Algoritma Fuzzy C-Means Muhja Mufidah Afaf Amirah; Agus Wahyu Widodo; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 12 (2017): Desember 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Digital music has grown dramatically in recent years. They offering musics in various type and emotion that are random. Therefore, there is a need to organize the songs, they need to somehow clusterize their files based on a specific characteristic. The purpose of such organization is to enable users to navigate to pieces of music they like, and also to give them advice and recommendation for people or music-related industries. This research proposed a clustering of songs based on their emotion using the Fuzzy c-means algorithm. Audio attributes of valence, energy, loudness, and tempo are used as features that represent the emotions of the song. The cluster of each data is determined based on their membership degree. Cluster validity index is used to evaluate the fitness of partitions produced by clustering algorithms. The algorithm is tested on different amount of data, which is 20%, 40%, 60%, 80%, and 100% data of total 150 songs. The testing result obtained a minimum error value of 0.00000001 (1x10-8). The results showed that the optimal number of clusters that are best to be used in this research is 5. While, the optimal fuzzifier value to be used in this research is 2 with the cluster validity value reaches 0.7 or 70%
Optimasi Komposisi Pakan Untuk Memenuhi Kebutuhan Nutrisi Ayam Petelur dengan Biaya Minimum Menggunakan Improved Particle Swarm Optimization (IPSO) Nur Firra Hasjidla; Imam Cholissodin; Agus Wahyu Widodo
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

In a business of laying hens farm, the feed costs constitute as much as 60-70 percent of the total cost of livestock production. Breeders can compose rations for their laying hens independently to save the feed costs. However, in the making of rations, breeders must examine the nutrient content and price of each feed ingredient that will be combined first. Breeders also have to evaluate manually whether the ration formula that will be given can fulfill the nutritional needs of laying hens. Therefore, to improve the efficiency of feeding in accordance with the nutritional needs of laying hens and with minimum cost, this study designed a system to determine the optimal layer feed composition using Improved Particle Swarm Optimization (IPSO) algorithm, an optimization technique which is a development of the PSO algorithm. Particles move in search space to find solutions. From the test results obtained optimal values for each IPSO's parameter, population size = 250, maximum iteration = 350, and the interval of feed ingredient weight = 1-70%. IPSO algorithm is able to give solution of feed composition with cost 50.41% cheaper than one of the data from laying hens breeder.
Optimasi Pemupukan pada Pertanian Rempah dengan Algoritme Genetika Muhammad Fahmi Hidayatullah; Imam Cholissodin; Agus Wahyu Widodo
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

Indonesia is an agricultural country which has many agricultural commodities such as spices demanded by foreign countries and has a high trade value. Currently, the production and export of Indonesian spices no longer dominate the global market, Indonesia has lost its glory in the world spices trade. It is caused by many farmers who only use limited experience and knowledge to fertilize the spices which can lead to crop failure and a big loss. Based on these problems, I will design an intelligent system that can optimize the fertilization in agricultural spices so the farmers could get optimal fertilizer for agricultural spices by using Genetic Algorithms. Genetic Algorithms was chosen because this algorithm can be used in problem optimization in a wide search space quickly. Test result using 2 type of plant, 3 types of fertilizers, 100 population size, 700 total generation, 0.3 cr and 0.7 mr combination can meet the nutrient needs of plants. The best result of this system testing can save cost of 0.23%.
Klasifikasi Penyakit Gigi Dan Mulut Menggunakan Metode Support Vector Machine Ana Mariyam Puspitasari; Dian Eka Ratnawati; Agus Wahyu Widodo
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

Oral diseases is one of the most serious diseases that impact to human health in general, as the mouth is a place where the germ and bacteria oral diseases should be handled immediately but not all dental expert can quickly do the handling due to the lack of a dental expert that is available in the hospital for 24 hours. Knowing the types oral diseases since the beginning is very important. Therefore, a system that has the ability to classify types of oral diseases will be very helpful in order to help the community in conducting early diagnosis of oral diseases. This research used classification system using of SVM method because SVM method can resolve the problem of classification and regression with linear or non linear kernel with its capability as a learning algorithm on the classification or regression. This research used One-Againts-All strategies for non linear process and used RBF kernel. The results obtained using SVM method has a mean median values of accuracy - 94,442% using the dataset as much as 122 data and with the parameter λ value SVM training sequential (lamda) = 0.1, y (gamma) = 0.1, C (Complexity) = 1, ε (epsilon) = 1.10-10 with itermax = 50 and ratio data 80%: 20%. The results shows good accuracy, and the research can be applied to help perform classification of oral disease using support vector machine method.
Identifikasi Kondisi Kesehatan Ayam Petelur Berdasarkan Ciri Warna HSV Dan Gray Level Cooccurence Matrix (GLCM) Pada Citra Jengger Dengan Klasifikasi K-Nearest Neighbour Maharani Tri Hastuti; Agus Wahyu Widodo; Candra Dewi
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 way of the good maintenance to laying chickens is separate the healthy and unhealthy chicken in defference cage quickly and correctly. But, in reality there's so many stock farmer who don't have fast response about the issue. Other than that, in the rural area we couldn't find any veterinarian or farm expert easily. So, we need a system to identify the condition of chicken health automatically. In this case, clinical symptoms in sick laying chickens can be observed through changes in color brightnes and texture in the wattle. Healthy laying chicken has bright red wattle and it tends to feel rough. The solution that can be applied to this problem is image processing with HSV color and graylevel coocurence matrix (GLCM) feature extraction. In this study GLCM method oriented by 4 angles that are 00, 450,900 and 1350 with d=1. From the extraction results we will get the values of HSV and statistic feature of GLCM such as entropy, energy, homogeneity, contrast and correlation for K-NN classification's input. A total of 26 testing data features will be calculated its euclidean distance with training data to search classes from input data. Based on the result of this study, the best accuracy obtained when classification with (GLCM 4 directions or 00) + all component of HSV and the number K = 3, K = 11 or K = 15 that is 100% correctness.
Penentuan Keaslian Tanda Tangan Menggunakan Shape Feature Extraction Techniques Dengan Metode Klasifikasi K Nearest Neighbor Dan Mean Average Precision Willy Karunia Sandy; Agus Wahyu Widodo; Yuita Arum Sari
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

The pace of technological development introduces the automatic identification of signature authenticity which is an important task in many activities requiring legitimate evidence. The process of authenticating signatures begins with preprocessing, which consists of gray transformation, median filter, binary transformation, cropping, and edge detection. After the process of preprocessing followed by the process of determining the extraction of form characteristics with the method of Shape Feature Extraction Techniques consisting of area, perimeter, centroid, rectangularity, eccentricity, roundness. Then classified based on training data obtained from calculations Shape Feature Extraction Techniques. After classification with K Nearest Neighbor then done calculation process Mean Average Precision to determine the authenticity of signature and percentage calculation of Mean Average Precision. In the system accuracy test results obtained 61% accuracy with the retrieval of random data for 25 data. Then obtained an accuracy of 61% accuracy with the retrieval of random data for 15 data and 58% on the retrieval of 5 data. Highest accuracy was obtained on the largest data collection with an accuracy of 61%.
Optimasi Sisa Bahan Baku Pada Industri Mebel Menggunakan Algoritma Genetika Andika Indra Kusuma; Agus Wahyu Widodo; Mochammad Ali Fauzi
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

The problem of the utilization of raw materials in the furniture industry is the difficulty of cutting raw materials with the right combination of sizes. To adjust the furniture production requirements, standard-sized raw materials must be cut to fit the needs of the furniture model to be produced. If not done the exact calculation when cutting the raw materials will certainly produce a lot of waste materials unused. The abundance of unused raw materials is what causes the maximum profit can not be achieved so that optimization of the remaining raw materials needs to be done. In this research optimization of the remaining raw materials is done with Genetic AlgorithmCorner Junction (GA+CJ). Stages performed are initial population generation, mutation with Rectangle &Junction Gene Swap Mutation(RJGSM) and Rectangle Rotation Mutation(RRM), evaluation, and selection. The results obtained in the form of chromosome-shaped solution arrangement of pieces of material. The highest fitness is 0.0026 which means consuming 16 pieces of raw material located on generation input parameter as much as 120 generations, mutation rate equal to 0.9, and 60 populations.
Optimasi Pembagian Barang Alat Tulis Kantor Menggunakan Algoritme Genetika Ardiansyah Setiajati; Imam Cholissodin; Agus Wahyu Widodo
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

Nowadays almost all companies need technology in helping business activities. Therefore information technology can help the company's activities in achieving its goals effectively and efficiently. Office stationery is one of the important supporting tools in running the operational functions of a company. Currently, office stationery management system in some companies or agencies are still done manually, so there is still often error information. Genetic algorithm is a population-based algorithm that can solve problems related to optimization with a very wide search space. Genetic algorithms can solve problems by providing a set of solutions and finding the most optimal solution. The chromosome representation consists of 801 genes comprising the sum of each item that each position can take. The optimal solution result is obtained on the test which is done 10 times using parameter that is the number of generation 2250, cr value 0,1, mr value 0,9, and population size 100, with fitness value equal to 7,288. However, there are still violations which is the number of some items that exceed the stock. Therefore, the solution is still not optimal.
Pengenalan Plat Nomor Mobil Menggunakan Metode Learning Vector Quantization Beryl Labique Ahmadie; Agus Wahyu Widodo; Fitri Utaminingrum
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

The amount of vehicles in Indonesia increases every year, this causing long queues at gates, mall, or tolls that require the process of recording license plates. This research will help simplify the process of recording license plate by creating a vehicle license plate recognition system. The system will try to recognize the license plate from a digital image. The first step in the license plate recognition system is to detect the location of the license plate by applying vertical edge detection because the area of license plate contains rich edge and texture information. The next step is character segmentation, this is a process to get characters from license plate image. this can be done by applying connected component algorithm. The last step is character recognition using learning vector quantization algorithm. Based on the result of this research, the highest accuracy is 94% in the license plate detection process, the highest f-measure value is 0,88 in the character segmentation process and the highest accuracy for character recognition using Learning Vector Quantization algorithm is 86,67%.
Co-Authors Achmad Arwan Achmad Dewanto Aji Wibisono Adam Hendra Brata Adinugroho, Sigit Afrida Djulya Ika Pratiwi Aida Fitri Nur Amrina Ainun Najib Eka Christianto Aisha Laras Akmilatul Maghfiroh Al-Mar'atush Shoolihah Allifira Andara Hasna Ana Mariyam Puspitasari Andika Indra Kusuma Andreas Pardede Angelika Trivena Lodong Anggita Nurfadilla Mahardika Annisa Amalia Nur'aini Anto Satriyo Nugroho Ardiansyah Setiajati Arry Supriyanto Arya Agung Andika Aryu Hanifah Aji Asfie Nurjanah Ayu Anggrestianingsih Ayudiya Pramisti Regitha Ayustina Giusti Azizah Nurul Asri Bagas Laksono Bayu Rahayudi Beryl Labique Ahmadie Budi Darma Setiawan Budi Kurniawan Cahya Chaqiqi Candra Dewi Dani Devito Delischa Novia Sabilla Deo Hernando Dian Eka Ratnawati Diantarakita Diantarakita Dwi Retnoningrum Dyan Putri Mahardika Eko Wahyu Hidayat Erlyan Eka Pratiwi Faizatul Amalia Fajar Pangestu Fajar Pradana Fajri Eka Saputra Farizky Novanda Pramuditya Femilia Nopianti Feris Adi Kurnia Sadiva Fitri Dwi Astuti Fransiskus Cahyadi Putra Pranoto Grace Theresia Situmorang Gusti Ngurah Wisnu Paramartha Hafid Satrio Priambodo Hardyan Zalfi Haris Bahtiar Asidik Harits Abdurrohman Herman Tolle Imam Cholissodin Indriati Indriati Irwan Shofwan Javier Ardra Figo Jefri Hendra Prasetyo Kholifa'ul Khoirin Lailil Muflikhah Latifa Nabila Harfiya Laviana Agata M. Ali Fauzi Maharani Tri Hastuti Maria Sartika Tambun Miftahul Arifin Muh Arif Rahman Muh. Arif Rahman Muh. Arif Rahman Muh. Ihsan As Sauri Muhamad Rendra Husein Roisdiansyah Muhammad Dimas Setiawan Sanapiah Muhammad Fahmi Hidayatullah Muhammad Fahmi Wibawa Muhammad Faiz Abdul Hamif Muhammad Fajriansyah Muhammad Heryan Chaniago Muhammad Ikhsan Nur Muhammad Rafi Farhan Muhammad Tanzil Furqon Muhja Mufidah Afaf Amirah Nabilla Putri Sakinah Nanda Dwi Putra Miskarana Ade Natassa Anastasya Naufal Sakagraha Kuspinta Nelli Nur Rahma Ni'mah Firsta Cahya Susilo Ningsih Puji Rahayu Nizar Riftadhi Prabandaru Novanto Yudistira Nur Afifah Sugianto Nur Faiqoh Laely Ambarwati Nur Firra Hasjidla Nur Kholida Afkarina Nurudin Santoso Nurul Hidayat oktiyas muzaky Luthfi, oktiyas muzaky Olive Khoirul L.M.A. Puteri Aulia Indrasti Putra Pandu Adikara Putri Bunga Rahmalita Putu Satya Cahyani Rahma Juwita Sany Randy Cahya Wihandika Rekyan Regasari Mardhi Putri Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Restu Widodo Resya Futri Hadi Febryana Retno Dewi Anissa Revan Yosua Cornelius Sianturi Ridho Saputra Rinindya Nurtiara Puteri Rizka Husnun Zakiyyah Rizki Aziz Amanullah Rosi Afiqo Rr Dea Annisayanti Putri Ryan Iriany Satria Habiburrahman Fathul Hakim Sayyidah Karimah Sindy Erika Br Ginting Sri Rahadian Ramadhan Sakti Susiawan Hastomo Ajie Talitha Raissa Tusiarti Handayani Tusty Nadia Maghfira Umar Zaki Izzuddin Utaminingrum, Fitri Vriza Wahyu Saputra Wayan Firdaus Mahmudy Wayan Firdaus Mahmudy Wenny Ramadha Putri Willy Karunia Sandy Winda Cahyaningrum Winda Ika Praseptiyana Witriana Sumarni Yane Marita Febrianti Yosafat Vincent Saragih Yuita Arum Sari Yunita Kristanti Emilia