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All Journal Jurnal Ilmu Pendidikan CommIT (Communication & Information Technology) Journal of Food and Life Sciences Journal of Innovation and Applied Technology Journal of Environmental Engineering and Sustainable Technology Jurnal Teknologi Informasi dan Ilmu Komputer AGRIVITA, Journal of Agricultural Science Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) JINOP (Jurnal Inovasi Pembelajaran) Premiere Educandum Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Pendas : Jurnah Ilmiah Pendidikan Dasar Journal of Education Technology Jurnal Ilmiah Sekolah Dasar Istawa: Jurnal Pendidikan Islam UPEJ Unnes Physics Education Journal AMALIAH: JURNAL PENGABDIAN KEPADA MASYARAKAT Journal of Research and Educational Research Evaluation Pendagogia: Jurnal Pendidikan Dasar Journal of Community Health and Preventive Medicine (JOCHAPM) Cendikia Pendidikan Advances In Social Humanities Research JURNAL ILMIAH EKONOMI, MANAJEMEN, BISNIS DAN AKUNTANSI Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research
Candra Dewi
Fakultas Ilmu Komputer, Universitas Brawijaya
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Peramalan Curah Hujan Menggunakan Metode High Order Fuzzy Time Series Multi Factors Ahmada Bastomi Wijaya; Candra Dewi; Bayu Rahayudi
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

Malang Regency is one of the regencies in East Java which has a high level of agricultural production in almost every district has agricultural land. The problem is when high rainfall is not a few farmers who experienced crop failure. Rainfall is one of several factors that affect climate change so it is very important to determine the yields obtained. The problem of this harvest failure can be overcome by forecasting rainfall, with rainfall forecasting farmers can determine the time of the appropriate cropping patterns so as to anticipate the occurrence of crop failure. On the research of forecasting rainfall in dasarian based on several factors namely temperature, humidity, and wind speed. The methods used for forecasting rainfall dasarian is a High-Order Fuzzy Time Series Multi factors. In this method the formation of subinterval using fuzzy C-means. In calculating the error of forecasting result using Mean Square Error (MSE). Based on the results of tests conducted the smaller threshold and the greater data training as well order the value error is obtained increasingly low. The result of forecasting dasarian rainfall for forecasting one year ahead using this method get the best MSE result of 539,698.
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.
Klasifikasi Aritmia Dari Hasil Elektrokardiogram Menggunakan Support Vector Machine Dengan Seleksi Fitur Menggunakan Algoritma Genetika Reiza Adi Cahya; Candra Dewi; Bayu Rahayudi
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

Electrocardiogram (ECG) can be used to recognize abnormal heart beats or arrhythmia. Automatic arrhythmia recognition can be achieved through the use of machine learning techniques. However, ECG generates raw numerical data with large amount of features that can reduce the quality of automatic recognition. Genetic algorithm (GA) can be utilized to perform a feature selection, reducing the amount of features. Data with reduced features then will be used to train a support vector machine (SVM) classifier. ECG data from the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database is used as training and testing data. Each data is a six-second ECG recording, and is classified into normal heartbeat and 3 different kind of arrhythmias. Result shows that GA-SVM yielded average accuracy of 82.5% with 120 training data and 20 test data, and reduced the amount of feature from 2160 original features to an average of 406 reduced features.
Penerapan Metode Average-Based Fuzzy Time Series Untuk Prediksi Konsumsi Energi Listrik Indonesia Yulian Ekananta; Lailil Muflikhah; 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

With the ever-increasing amount of demand for consumption, for now the concept of forecasting is increasingly necessary as an important input to take planning and control decisions. Referring to the prediction activity, one of the techniques contained in the activity is the fuzzy time series technique. Fuzzy time series is an algorithm used for prediction. Prediction using this fuzzy time series works to store data in the past then generate new value in the show in the future. The resulting output is the result of the prediction. The advantage of time series method is not to require assumptions compared to other prediction methods. The method of fuzzy time series process is not too complicated so it is easy to develop. There are many types of methods using fuzzy time series in its development, one of them is the average-based fuzzy time series. This method is an average-based fuzzy time series method that is able to determine the effective interval length, so as to provide predictive results with a good degree of accuracy. In its implementation, this research applies method of average-based fuzzy time series for prediction of electric energi consumption. The data of electric energi consumption is chosen because it has the right characteristic that is included in the trend data class. In the test section performed using test while using the traning data as much as the total amount of data 43 produces AFER 9.24. While using the MAPE 14,27%. These results include good criteria.
Implementasi Metode Dempster-Shafer untuk Diagnosa Defisiensi (Kekurangan) Vitamin pada Tubuh manusia Yudha Eka Permana; Edy Santoso; 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

In modern times, many people do not pay attention to the intake of nutrients in their daily food cosumption, especially the vitamin content. Vitamin is a complex substance that is needed by our body that serves to help the process of body activities. Vitamin deficiency can lead to an increase in the chances of getting disease in our body and allow the body functions not to work optimally. Checking the level of vitamin deficiency is very rarely done by the community, because it needs a blood test and the cost for the test is quite expensive. In this study the problems are solved by creating an expert system, a system that can diagnose the type of vitamin deficiency in the human body, so it can easily be known which type of vitamin deficiency suffered by the users. This system is implemented using Dempster Shafer method. Testing is done by comparing the conformity of the output of the system to the expert diagnosis. From the test of 30 case data obtained an accuracy of 87%. After testing by increasing the weight value of the symptoms, the accuracy rate increased to 90%. So this expert system can be used to assist users in making a diagnosis of deficiency or vitamin deficiency.
Implementasi Algoritme Fuzzy K-Nearest Neighbor untuk Penentuan Lulus Tepat Waktu (Studi Kasus : Fakultas Ilmu Komputer Universitas Brawijaya) Andhika Satria Pria Anugerah; Indriati Indriati; Candra Dewi
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

Along with the increasing interest of studying in the collage, therefore the data of student graduation which is filed will keep increasing. However, those data could be in a very large amount if it is processed manually, therefore it is needed to apply the student graduation classification which able to classify the graduation data based on the determined parameters. There are some ways to classify the object that have been developed, one of them is Fuzzy K-Nearest Neighbor. Fuzzy K-Nearest Neighbor is one of the methods which is used to classify the object by calculating the membership degree in each class. The experiment of Fuzzy K-Nearest Neighbor is done toward the problem of time of student graduation which is categorized into graduate on time and graduate out of time. In this experiment, Fuzzy K-Nearest Neighbor is used to identify the students based on the achievement index that they have got. Based on the experiment results, Fuzzy K-Nearest Neighbor is able to get an accuracy score around 98%. This accuracy is from the given weight of the membership in each output class. This is able to minimize the doubtful in determining the output class
Optimasi Fungsi Keanggotaan Fuzzy Menggunakan Algoritma Genetika Dalam Penentuan Kebutuhan Gizi Bayi MPASI Marwa Mudrikatussalamah; Candra Dewi; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 7 (2018): Juli 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In determining the nutritional needs for infants required several factors, one of the strengthening factors is to determine the nutritional status of infants. In determining the nutritional status of infants, it need a rangewhhich contain of the limit on each nutitional category. The method used in this determination is fuzzy tsukamoto which will be used for the optimization of membership function with genetic algorithm. Genetic algorithms are used to form the boundaries formed on a chromosome. Boundaries of grade that have been used in genetic algorithm will be a function grade of membership in fuzzy tsukamoto. The next process is fuzzy tsukamoto will process the data in accordance with the value that has been optimized by the genetic algorithm to determine the final result. Further testing is done to determine the best parameters in making chromosomes. The Test are obtained an average accuracy of 53.5%. Accuracy is obtained from the calculation of the optimization results compared with the value of the expert.
Klasifikasi pada Penyakit Dental Caries Menggunakan Gabungan K-Nearest Neighbor dan Algoritme Genetika Dennes Nur Dwi Iriantoro; Candra Dewi; Delvi Fitriani
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

Dental caries disease is a disease commonly encountered in cases of dental problems. Indonesia is ranked 6th in dental caries cases 60% - 80% in the population in Indonesia. Therefore, early treatment expected to reduce the high caries disease in Indonesia. Classification Caries using computer programs is expected to improve performance in the field of dentistry. The problem with using the K-Nearest Neighbor method has been widely applied to other cases. This method has a deficiency in determining the value of K that must be sought alone for K. This study will discuss about the optimization of KNN K method. This study will use the combined K-Nearest Neighbor and Genetic Algorithm. Genetic algorithms can produce optimal solutions with various variations and have advantages in terms of ability. The use of optimization with this genetic algorithm makes K-Nearest Neighbor method easier to use because it does not have to choose manually. The results obtained on the accreditation test by Genetics algorithm quality are optimal K with 88% honesty and 0.9 fitness. Classification of dental caries disease would be better to use this combined method
Optimasi Batasan Fungsi Keanggotaan Fuzzy Tsukamoto Menggunakan Algoritme Genetika Untuk Kelayakan Pemberian Kredit (Studi Kasus: PD. BPR. Bank Daerah Lamongan) Naily Zakiyatil Ilahiyah; Dian Eka Ratnawati; Candra Dewi
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

Before the credit is given to the prospective debitor, the lender needs to select the prospective debitor's data first by considering several criteria. This is because the creditors get some problems that often occur when giving credit worthiness such as inconsistency to credit analysis that can change and the length of time required to select the data of prospective debitor due to the data that many and varied. These problems can be solved by building a classification system using the fuzzy tsukamoto method to classify the data and determine the creditworthiness of the debitor. However the use of the fuzzy tsukamoto method can not provide optimal results. It is shown with the accuracy value obtained is 90.476% from the test using 63 sample data. To obtain a more optimal accuracy, the workable solution is to optimize the fuzzy membership function constraint using genetic algorithm. Based on the results of testing system that has been optimized, the system obtained accuracy value of 93.651% with parameter popsize 220, Cr 0.7, Mr. 0.3 and generation number 220.
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.
Co-Authors Abdul Fatih Achmad Yusuf Adam Sulthoni Akbar Adinugroho, Sigit Aditya Chandra Nurhakim Aditya Septadaya Adiyasa, Bhisma Afrialdy, Firman Aghata Agung Dwi Kusuma Wibowo Agi Putra Kharisma Agus Wahyu Widodo Ahmad Afif Supianto Ahmad Afif Supianto Ahmada Bastomi Wijaya Akmal Subakti Wicaksana Alan Primandana Almasyhur, Muhammad Bin Djafar Amalia Luhung Amita Tri Prasasti, Pinkan Anang Tri Wiratno Andhika Satria Pria Anugerah Anggita Mahardika Ani Budi Astuti Ani Rusilowati Anim Rofi'ah Annisa Puspitawuri Annisa Salamah Rahmadhani Aprianto, Anda Bagas Arbawa, Yoke Kusuma Aria Bayu Elfajar Arief Andy Soebroto Arjunani, Rusmalistia Intan Ayuri Alfarianti Azhari, Muhammad Rizqi Azizul Hanifah Hadi Barik Kresna Amijaya Bayu Rahayudi Brillian Aristyo Rahadian Budi Astuti Budi Darma Setiawan Chelsa Farah Virkhansa Daneswara Jauhari Daneswara Jauhari, Daneswara Dany Primanita Kartikasari Dennes Nur Dwi Iriantoro Deo Hernando Desy Wulandari Dewanti, Amalya Trisuci Diajeng Tania Ananda Paramitha Dian Eka Ratnawati Dloifur Rohman Alghifari Dwi Fitriani Dwi Novi Setiawan Dwi, Endah Dyang Falila Pramesti Edo Ergi Prayogo Edy Santoso Edy Santoso Erik Aditia Ismaya Eriq Muh. Adams Jonemaro Falih Gozi Febrinanto Faris Febrianto Febri Ramadhani Fenori, Muhammad Dajuma Feri Angga Saputra Fianti Fianti, Fianti Fitri Anggarsari Fitriana, Rosita Nur Fitriani , Dwi Fitriani, Delvi Guntur Syafiqi Adidarmawan Hartami, Edina Himawan, Alfian Iftinan, Salsa Nabila Ikhwanul Kiram, Muh Zaqi Ilham Harazki Imam Cholisoddin Imam Cholissodin Imam Cholissodin Indah Lestari, Indah Indah Wahyuning Ati Indah, Yuliana Indra Eka Mandriana Indriati Indriati Indriati Indriati Indriati, Indriati - Iqbal Santoso Putra Iskarimah Hidayatin JANAH, NURUL Jumadi Jumadi Khairiyyah Nur Aisyah Kharisma, Agi Krisyanto, Edy Kurnianingtyas, Diva Kurniawan, I Gede Jayadi Kusumawardani, Septyana Dwi Lailil Muflikah Lailil Muflikhah Maharani Tri Hastuti Mardji Mardji Marinda Ika Dewi Sakariana Marinda, Vira Marwa Mudrikatussalamah Maulan, Erika Maulana Putra Pambudi Maulida, Farida Merlya, Merlya Mochammad Tanzil Furqon Mohammad Nuh Mohammad Setya Adi Fauzi Muh Arif Rahman Muhammad Ihsan Diputra Muhammad Misbachul Asrori Muhammad Noor Taufiq Muhammad Prabu Sutomo Muhammad Riduan Indra Hariwijaya Muhammad Tanzil Furqon Muhja Mufidah Afaf Amirah Muhyidin Ubaiddillah Mukh. Mart Hans Luber Nabila Arief Nadia Artha Dewi Naily Zakiyatil Ilahiyah Naniek Kusumawati Nazzun Hanif Ahsani Nirzha Maulidya Ashar Nooriza Fariha Rumagutawan Noval Dini Maulana Novanto Yudistira Nur Hidayat Nur Sa'diyah Nurhidayati Desiani Nurul Faridah, Nurul Nurul Hidayat Nuryatman, Pamelia Nuzula, Nila Firdauzi Pande Made Rai Raditya Phutpitasari, Rosa Devi Pupung Adi Prasetyo Putra Pandu Adikara Putri Aprilia Putu Gede Pakusadewa Rachmalia Dewi Rahma Juwita Sany Randy Cahya Wihandika Rasya, Muhammad Ratih Kartika Dewi Rayhan Tsani Putra Reiza Adi Cahya Reza Wahyu Wardani Rifan, Mohamad Rina Christanti, Rina Rizal Setya Perdana Rizal, Moch. Khabibur Robih Dini Rohmah, Yushinta Lailatul Rohmanurmeta, Fauzatul Ma’rufah Rokky Septian Suhartanto Romlah Tantiati Rosyita, Elyana Santoso, Allegra Santoso, Andri Saputra, Rendi Ramadani Saputro, Rinaldi Eko Saputro Sekar Dwi Ardianti Selle, Nurfatima Selvi Marcellia Setya Perdana, Rizal Sigit Pangestu Siti Nurjanah Siti Nurlaela Sundari, Suci Sunyoto Eko Nugroho, Sunyoto Eko Susenohaji, Susenohaji Sutrisno . Syarif, Adnan Tirana Noor Fatyanosa, Tirana Noor Ulfah Mutmainnah Veni, Silvia Wahyu, Dwi Wayan Firdaus Mahmudy Werdha Wilubertha Himawati, Werdha Wilubertha Wiandono Saputro Wilis Biro Syamhuri Wiratama Paramasatya Yasin, Patbessani Septani Firman Yessica Inggir Febiola Yosua Christopher Sitanggang Yudha Eka Permana Yudistira, Indrajati Yuita Arum Sari Yulia Trianandi Yulian Ekananta Yusi Tyroni Mursityo Zulhan, Galang