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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal POINTER Sinkron : Jurnal dan Penelitian Teknik Informatika Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Jurnal Informatika dan Multimedia JAST : Jurnal Aplikasi Sains dan Teknologi TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Sistem Informasi, Teknologi Informasi, dan Edukasi Sistem Informasi (JUST-SI) DEDIKASI PKM Jurnal Informatika dan Multimedia Enrichment: Journal of Multidisciplinary Research and Development Majority Science Journal
Dian Eka Ratnawati
Brawijaya University, Malang
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other

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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.
Identifikasi Penyakit Gagal Ginjal Menggunakan Metode Neighbor Weighted K-Nearest Neighbor (NWKNN) Azizul Hanifah Hadi; 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

Kidney disease can be caused by several factors such as hypertension, uric acid levels, creatinine levels, diabetes, and many others. From that factors, we know about the level of kidney disease risk. Some people are unaware, lazy and indifferent about health, especially on kidney disease because of the long process and complicated. According to the Indonesian Renal Registry, in 2014 patients with kidney disease in Indonesia reach 12,770 inhabitants. Therefore, we need a system that can detect or identify the kidney disease. In this research, we will identify the kidney disease using Neighbor Weighted K-Nearest Neighbor (NWKNN) method. This method is similar to the KNN method but the differentiates are in the weighting process in each identification class. Identification class in this study decided in two part, ckd or exposed to kidney disease and notckd or not affected kidney disease. The results of this study indicate that the NWKNN method can identify kidney disease when the data are 150 data and the test data are 50 data with K = 2 and E = 2 and accuracy level is 88%.
Optimasi Asupan Makanan Harian Ibu Hamil Penderita Hipertensi Menggunakan Algoritme Genetika Novirra Dwi Asri; Imam Cholissodin; Dian Eka Ratnawati
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

Hypertension is a risky disease and one of the main causes of death in pregnant women. For Hypertension pregnant women, the wrong food arrangement can affect the growth and development of the fetus. The recommended food arrangements for pregnant women with Hypertension is arrange the portion of food that can increase hypertension but not reducing the nutrition for fetus. There is one way that can be used to serve food of pregnant women with Hypertension is use a Genetic Algorithm. Genetic Algorithm is a heuristic method that uses rules to get the best solution. The process of Genetic Algorithm in research using representation chromosome integer number, crossover using extended intermediate crossover, mutation using random mutation and selection using elitism selection. The results provided are food recommendations for several days consisting of breakfast, lunch, and dinner. Based on the research results, the optimal generation size is 240 with the average fitness value is 525.0720, the optimal population size is 90 with the average fitness value is 525.0680 and the combination of cr and mr is 0.6 and 0.5 with average fitness value is 525. 0695.
Klasifikasi Tingkat Risiko Penyakit Stroke Menggunakan Metode GA-Fuzzy Tsukamoto Vina Adelina; Dian Eka Ratnawati; Mochammad Ali Fauzi
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

Stroke is clinical syndrome which usually comes sudden, quick, in a form of focal or global neurological deficits that happen within 24 hours or sometimes can cause a death. Stroke problems in Indonesia need a serious attention because of the number of death is high and always inCreasing. On of the necessary handling is detecting the symptoms of stroke in a form of SKD (Sistem Kewaspadaan Dini). Research found that to estimate the risk of stroke, it can use Fuzzy logic inference. From the 15 data test that has been done, the result gets 60% accuration. To optimize the result of membership degree function, it uses genetics algorithm in Fuzzy tsukamoto inference. Representation of chromosomes used is real code which every chromosome initialize the limitations in all Fuzzy variables. Crossover method using one cut point, random mutation used for mutation method and elitism selection used for election method. It is known that the result from optimization from the system accuration using Fuzzy tsukamoto-GA is 86.66% and the number of popsize which from the best parameter of the optimum result is 500, and the number of generations is 1000 as well as the combination Cr = 0,5 and Mr= 0,6. Keywords: stroke, genetics algorithm, Fuzzy tsukamoto, classification
Diagnosis Penyakit THT Menggunakan Metode Fuzzy K-NN Afrida Djulya Ika Pratiwi; Dian Eka Ratnawati; Agus Wahyu Widodo
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

Humans are one of the living beings that exist in the world. One of the important organs that exist in humans are the ears, nose, and throat. This causes the organs to be connected to each other and can cause the spread of infection if one of the three organs are infected. Diseases that attack ENT is still considered trivial by the community, so the public awareness to check to the doctor is still low. Therefore, to facilitate the community to making their own diagnosis of ENT disease, then made a diagnosis system ENT disease. This diagnostic system uses Fuzzy-K nearest neighbor method. The used of the Fuzzy-K nearest neighbor method occurs in some studies that using this method can get high scores. In this study using four pieces of testing, namely testing of variations in the amount of training data, testing of variations in the number of values ​​k., testing of comparison between the number data training and data testing, and cross validation testing. Based on four types of test scenarios performed using 122 data related to ENT disease, obtained results with an average rate of 99,2%.
Optimasi Komposisi Makanan Untuk Ibu Hamil Menggunakan Hybrid Algoritme Genetika dan Simulated Annealing Fatthul Iman; Dian Eka Ratnawati; Titis Sari Kusuma
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

The imbalance between the nutritional intake of pregnant women to meet the needs and energy expenditure must always be monitored, because the imbalance itself can result in Chronic Energy Deficiency both in mother and fetus in the womb. Therefore it needs an appropriate food composition to meet the nutrients and energy for pregnant women, so it can help them to determine their own food. The problem of food composition for pregnant women can be solved by hybrid genetic algorithm and Simulated Annealing. The purpose of combining this method is to produce a better solution than using a genetic algorithm alone. This problem solving process have used crossover method is one-cut point, mutation using reciprocal exchange method, selection using elitsm, and Simulated Annealing. Based on the results of the test of the parameters used in the optimization system of food composition that using genetic algorithm hybrid and Simulated Annealing, was obtained the best parameter values ​​are: population number = 2900, Cr = 0.4, Mr = 0.6, T0 = 1, alpha = 0.7 and the number of generations = 220. So the results of the system is in the form of food composition recommendation using hybrid genetic algorithm and Simulated Annealing that can meet the tolerance limit set by the nutritionists at ± 10%.
Penjadwalan Dinas Pegawai Menggunakan Algoritma Genetika Pada PT Kereta Api Indonesia (KAI) Daerah Operasi 7 Stasiun Besar Kediri Yolanda Nailil Ula; Dian Eka Ratnawati; Satrio Agung Wicaksono
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

Scheduling is one thing that very important to create regularity organizational activities in the company, especially about the scheduling employee service. In this study data schedule employee PT Kereta Api Indonesia Kediri Besar Station in 2017, for optimal scheduling result use genetic algorithm method base on company regulation. In the genetic algorithm process initial population process is done by chromosome representation using permutation number with length of gene 98 representing 14 employees in 7 days. The reproduction process is divided into crossover and mutation, the crossover method use one cut point, and the mutation method use reciprocal exchange mutation. The selection process is done by elitism selection with selecting the fitness value based on the best result to be the parents in the next generation. Based on the test results are obtained the optimal parameters of cr value 0,1 mr value 0,9 in the 50 th generation and population 50 with average fitness value 0,093.
Estimasi Hasil Produksi Benih Berdasarkan Karakteristik Tanaman Kenaf Menggunakan Metode Backpropagation (Studi Kasus: Balai Tanaman Pemanis dan Serat Kota Malang) Davia Werdiastu; Dian Eka Ratnawati; Bayu Rahayudi
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

Kenaf plants have many benefits. However, currently it has limitation production of Kenaf palnts. According to Research and Development Agency, Malang City stated that Kenaf seed production was just about 0.3-0.5 tons/ ha, while farmers' need for superior seed of Kenaf plants was about 0.7-1.0 tons/ ha. Balai Penelitian Tanaman Pemanis dan Serat (BALITTAS) Malang city was directly elected to carry out certification of seed consist of field inspection, laboratory test, and labeling. Seed certification aimed to ensure seeds quality. For seeds certification, BALITTAS has difficult to estimate resulted seeds. This estimate was required to prepare certification requirements such as laboratory equipment, yarn, gunny sack, and workers. This can be solved by built an estimation system using backpropagation algorithm. The number of neurons in the input layer was 4 inputs ie the number of seeds production was the age of flower I, bottom diameter, the weight of 10 plants seeds, and the number of mature capsules, and produced 1 output as resulted seeds. The calculation process starts from initialled initial weight with nguyen-widrow, feedforward and backpropagation, then update weight and bias. Test result showed the best mean of MAPE value was 0,938% with 90% testing test scenario, 10% test data, 5 neurons in hidden layer, learning rate 0,3, maximum 1% MAPE and maximum limit of iteration 5000.
Estimasi Hasil Produksi Benih Tanaman Kenaf (Hibiscus Cannabinus L.) Menggunakan Metode Extreme Learning Machine (ELM) Pada Balai Penelitian Tanaman Pemanis dan Serat (Balittas) Audia Refanda Permatasari; Dian Eka Ratnawati; Bayu Rahayudi
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

Balai PenelitianTanaman Pemanis dan Serat (Balittas) develops various types of fiber plants, one of them is kenaf. Balittas is put forward kenaf seeds production. In producing kenaf seeds, Balittas has constraints that can inhibit the production processing of kenaf seeds. The constraint is when estimating seed production. In this research the author make an estimation system of kenaf seed production using Extreme Learning Machine method. This method is one of the artificial neural network method that has an advantage of learning speed. There are steps in ELM method, such as normalization,training, testing and denormalization. In this research, the result of system evaluation using Mean Absolute Percentage Error (MAPE). Based on the test performed, this method got the best average MAPE. The value is 0,160% using 8 number of neuron, binary activation function, and the percentage comparison of training data and testing data is 90%:10%.
Prediksi Jumlah Produksi Kelapa Sawit Dengan Menggunakan Metode Extreme Learning Machine (ELM) (Studi kasus: PT. Sandabi Indah Lestari Kota Bengkulu) Ema Agasta; Imam Cholissodin; Dian Eka Ratnawati
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

Palm oil is a plantation that became the number one sector in Indonesia. This plant has a cost and a better production than other plantation crops such as sugar cane and rubber. In a company, palm oil production becomes the driving force of the economy, as well as what happened to PT. Sandabi Indah Lestari. In every week the company plans to predict the production. Planning done sometimes still give less than optimal results. This is because the calculation process is still using manual analysis. In this research will use four prediction features that are plant age, number of trees, land, and production. The prediction technique used is the learning method of Extreme Learning Machine (ELM). This method has advantages in learning speed and accuracy in predicted results. The calculation process starts from the process of data normalization, training a number of training data and test data, calculation of the prediction error value and produce the final value. The data used is production data in the period 2015 - 2017 with a total of 297 data. From a number of data will be divided into two data with percentage of 80% training data and 20% test data. The result of the research was obtained the optimal parameter value that is 13 hidden neuron in testing the number of neurons with Mean Absolute Perscentage (MAPE) value of 21.25%, 20.42% on the data feature test with the best 2 technical features and 20,19% on testing the pattern with the final result of the data pattern 1.
Co-Authors Abdurrahman Airlangga, Aria Abhiram, Muhammad Tegar Achmad Arwan Achmad Ridok Achmad, Riza Putra Adhitya, I Made Yoga Adrian Firmansah, Dani Afif Ridhwan Afrida Djulya Ika Pratiwi Agus Wahyu Widodo Agustin Kartikasari Ahmad Afif Supianto Akbar, Rozaq Aldy Satria Alfa Fadlilah Alifah, Syafira Almira Syawli, Almira Alvian Akmal Nabhan Amonito, Kurnia Ana Mariyam Puspitasari Anak Agung Bagus Arisetiawan Anam, Syaiful Ardhiansyah, Muhammad Hanif Arief Andy Soebroto Arif Pratama Asmoro, Priandhita Sukowidyanti Asroru Maula Romadlon Audia Refanda Permatasari Ayu Dwi Lestari, Cynthia Ayulianita A. Boestari Azizul Hanifah Hadi Bayu Rahayudi Bayu Satriawan, Eka Bayu Septyo Adi Bella Krisanda Easterita Bening Herwijayanti Berton, Freddy Toranggi Buce Trias Hanggara Buce Trias Hanggara Buchori Anantya Firdaus Budi Darma Setiawan Cahyo Gusti Indrayanto Candra Dewi Dany Primanita Kartikasari Darma Setiawan, Budi Darmawan, Riski Davia Werdiastu Denny Manuel Yeremia Sinurat Deny Tisna Amijaya, Fidia Devi Nazhifa Nur Husnina Dewi Yanti Liliana Dhiva Mustikananda Dimas Diandra Audiansyah Dimas Fachrurrozi Azam diniyah, zubaidah Diva, Zahra Djoko Pramono Dwi Ari Suryaningrum Dwi Febry Indarwati Dwi Purwono, Prayoga Dwija Wisnu Brata Dyva Pandhu Adwandha Dzulkarnain, Tsania Dzulkarnain, Tsania - Easterita, Bella Krisanda Edgar Maulana Thoriq Edy Santoso Elfa Fatimah Ema Agasta Entra Betlin Ladauw Eva Agustina Ompusunggu Fadhil, Muhammad Farrasseka Fadila, Putri Nur Faiz Anggiananta Winantoro Fanka Angelina Larasati Fathin Al Ghifari Fatthul Iman Fauzan Dwi Kurniawan, Fauzan Dwi Fauzidan Iqbal Ghiffari Figgy Rosaliana Firdaus, Muhammad Fariz Fitra Abdurrachman Bachtiar Fitri Dwi Astuti Fitria Yesisca Fitria, Tharessa Ghani Fikri Baihaqi glenando Gusti Ngurah Wisnu Paramartha Hadi Wijoyo, Satrio Hamas, radityo Hana Chyntia Morama Hanggara, Buce Trias Hanifa Maulani Ramadhan Haris Haris, Haris Harris Imam Fathoni Hasibuan, Herida Hafni Hasibuan, Raka Ardiansyah Heru Nurwasito Hilal, Khaliffman Rahmat Hilmy Ramadhan, Achmad Zhafran Huda Minhajur Rosyidin I Dewa Gede Ngurah Bramasta Darmawan Ibnu Aqli Ibnu Aqli, Ibnu Ibrahim Kusuma Ilyas, Muhaimin Imam Cholissodin Imam Cholissodin Imam Cholissodin Immanuel Tri Putra Sihaloho Indriati ., Indriati Indriati Indriati Ismiarta Aknuranda Issa Arwani Issa Arwani Isti Marlisa Fitriani Izza, Aisyah Nurul Jesika Silviana Situmorang Jibril Averroes, Muhammad Juan Michel Hesekiel Kartika, Annisa Wuri Kelvin Anggatanata Kevin Renjiro Khairi Ubaidah Khoba, Ahmad Faiz Khofifatunnabilah, Khofifatunnabilah Kirana, Urdha Egha Krishna Febianda Kusuma, Salsabila Azzahra' Zulfa Lailil Muflikhah Leonardo, Ryan Luqman Rizky Dharmawan M. Ali Fauzi Madjid, Marchenda Fayza Maghfiroh, Sofita Hidayatul Mahendra Data Mahendra Data Mala Nurhidayati Maliha Athiya Rahmani Marji . Marji Marji Marji Marji Marji Marji Maulana Syahril Ramadhan Hardiono Michael Eggi Bastian Mochammad Iskandar Ardiyansyah Rochman Moh Fadel Asikin Muh. Arif Rahman MUHAJIR Muhammad Iqbal Mustofa Muhammad Kevin Sandryan Muhammad Reza Utama Pulungan Muhammad Tanzil Furqon Muhyidin Ubaiddillah Muslimah, Fakhriyyatum Muthia Maharani Nabilah Iftah Nella Naily Zakiyatil Ilahiyah Nanang Yudi Setiawan Nanang Yudi Setiawan Nanda Alifiya Santoso Putri Nanda Petty Wahyuningtyas Nilna Fadhila Ganies Norma Desitasari Novirra Dwi Asri Nugraha Perdana, Aditya Nugraheni, Miftakhul Fitria Nur Adli Ari Darmawand Nur Khilmiyatul Ilmiyah Nuraini Anitasari Nuralam, Inggang Perwangsa Nurul Hidayat Nyimas Ayu Widi Indriana Oceandra Audrey Pandu Adikara, Putra Pangestu Ari Wijaya Panjaitan, RE. Miracle Prahesti, Suherni Prakoso, Ricky Pratomo Adinegoro Priyono, Mochammad Fajri Rahmatullah Rendra Puji Indah Lestari Purnomo, Welly Putra Pandu Adikara Putra, Alland Rifqy Putri, Nindy Alya Rachmad, Zikfikri Yulfiandi Raden Rizky Widdie Tigusti Rahma, Dzakiyyah Afifah Rahmah, Yusriyah Raisha, Serefika Raja Farhan Ramadha Pohan Rama Humam Syarokha Randy Cahya Wihandika Rani Metivianis Ratih Diah Puspitasari RE. Miracle Panjaitan Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Retno Indah Rokhmawati, Retno Indah Revi Anistia Masykuroh Rifqi Irfansyah, Nandana Rizal Setya Perdana Rizal Setya Perdana Robiata Tsania Salsabila Aditya Putri Rodiah Rodiah Ryan Leonardo Salsabillah, Dinar Fairus Saparila Worokinasih Saputro, Dimas Sarie, Riza Athaya Rania Satriawan, Eka Bayu Satrio Agung Wicaksono Satrio Hadi Wijoyo Sema Yuni Fraticasari Setiawan, Alexander Christo Setya Perdana, Rizal Setyowati, Andri Shafira Margaretta Sherly Witanto Sherryl Sugiono Sindarto Sigit Pangestu Silvia Ikmalia Fernanda Siregar, Fauziah Syifa R. Siti Fatimah Al Uswah Sobakhul Munir Siroj Sormin, Hartati Penta Angelina Sri Indrayani, Sri Suhhy Ramzini Sukmawati, A'inun Sutrisno Sutrisno Sutrisno, Sutrisno Syaiful Anam Syifa Namira Neztigaty Thifal Fadiyah Basar Titis Sari Kusuma Ulfa Lina Wulandari Utomo, Yoga Cahyo Vina Adelina Welly Purnomo Wibowo, Shinta Dewi Putri Widhy Hayuhardhika Nugraha Putra Wijanarko, Rizqi Winda Fitri Astiti Winurputra, Raihan Wiratama Paramasatya Yahya, Faiz Yolanda Nailil Ula Yudi Setiawan, Nanang Yuita Arum Sari Yunita Dwi Alfiyanti Yure Firdaus Arifin Zahra, Wardah