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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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Penentuan Penerima Bantuan Ternak Menggunakan Algoritma K-Means & Naive Bayes Moh Fadel Asikin; Dian Eka Ratnawati; Mochammad Ali Fauzi
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

Indonesia is a vast country with many islands suitable for the development of livestock business. In reality, the livestock sector has not been able to encourage public and private participation. To overcome these problems, some of the budget of the Ministry of Agriculture is allocated in the form of social assistance expenditures, such as for community empowerment and poverty alleviation in the form of goods to farmer groups. One of the forms of assistance allocated to farmer groups is the provision of livestock. Determination of potential recipients is still not effective and sometimes leads to the giving of livestock assistance is not right on target, so that every expenditure of state money does not provide maximum benefits for the community. In this research, K-Means Naive Bayes (KMNB) method is considered capable of giving accurate classification results on the determination of livestock recipients. The KMNB learning approach is formed by combining clustering and classification techniques. K-Means is used as a pre-classification component to group the same data at an early stage. Furthermore, for the second grouping of data will be classified by category Accepted or not using Naive Bayes. Thus, the data with the wrong group during the first stage will be classified according to the category in the second stage. Based on the test results by comparing the results of grouping on conventional K-Means method it is proven that KMNB gives the highest accuracy of 100% while conventional K-Means has an accuracy of 95.91%
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.
Implementasi Metode Gabungan Multi-Factors High Order Fuzzy Time Series dan Fuzzy C-Means Untuk Peramalan Kebutuhan Energi Listrik di Indonesia Sigit Pangestu; Dian Eka Ratnawati; 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

Indonesia is one of the countries consuming electricity which always experience the increasing need of electric energy every year. Electricity needs in the household sector from 2003 to 2013 in Indonesia increased by an average of 8% per year. While in the commercial sector the average increase of 10.1%. Growing demand for electrical energy should be properly handled in order to avoid the lack of electricity supply that can lead to inhibition of economic activity in Indonesia. Therefore it is needed a program that can help the supplier of electrical energy in Indonesia (PLN) to determine the amount of electrical energy that must be prepared. The Combined method Multi-Factors High Order Fuzzy Time Series and Fuzzy C-Means (FCM) can be used to forecast electrical energy requirements. Fuzzy C-Means replaces one of the processes in the Multi-Factors High Order Fuzzy Time Series method when creating subintervals. The path of the method is the determination of the Universe of Discourse, the determination of the number of clusters, the formation of subintervals with Fuzzy C-Means, the formation of fuzzy sets, the fuzzification process, the formation of Fuzzy Logic Relationship (FLR), and the defuzzification process. From the test results obtained the smallest MAPE (Mean Absolute Percentage Error) value of 1.7857%. MAPE results obtained that less than 10% indicate that Combined Methods Multi-Factors High Order Fuzzy Time Series and Fuzzy C-Means (FCM) is very good used to forecast electricity demand in Indonesia.
Penerapan Metode K-Means-ACO Untuk Pengelompokan Biji Wijen Berdasarkan Sifat Warna Cangkang Biji Pangestu Ari Wijaya; Rekyan Regasari Mardi Putri; Dian Eka Ratnawati
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

Sesame is one kinds of the groceries that produce vegetable oil. Nowadays, the needs of sesame is increasing so it is necessary to pick a good quality in producing sesame. To conduct sesame plants crossing, the color of sesame seed shell is very infuential on its quality. Several previous studies used in this research has been done to cluster sesame seed with qualitative and quantitative method. The qualitative method in this research is conducted by field observation while the quantitative method is conducted by processing the sesame data from measurement result by using chromameter which resulted of an L*, a* and b* color. Several previous studies has successfully done the clustering by using qualitative method namely IWOKM, PSOKM and GAKM method. This study will categorize and compare the result of sesame data with same of data by using K-Means-ACO method with the previous method. From several journals, the method is proved that K-Means-ACO method has optimal results because in the analysis step combined the optimization and clustering algorithm method. Based on the test results of the K-Means-ACO method compared with the previous method, the good result of clustering sesame seed based on the color of the seed shell. It is proven by the grouping result is 233:58. After all, this research could be concluded that the K-Means-ACO method could be used as the alternative method to conduct the sesame seed classification based on its seed shell color.
Implementasi Algoritme Support Vector Machine (SVM) untuk Prediksi Ketepatan Waktu Kelulusan Mahasiswa Arif Pratama; Randy Cahya Wihandika; Dian Eka Ratnawati
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

Graduate on time is the desire of all students. In reality, not as expected many students who graduated more than four years. necessitating the application of predictive graduation students can classify graduation prediction data based on parameters that have been determined. Because it is necessary for the application of intelligent systems can classify graduation prediction data based on parameters. Algorithm Support Vector Machine (SVM) to classify the data into two classes using kernel Gaussian RBF with a combined value of parameter λ = 0,5, constant γ = 0,01, and ε (epsilon) = 0,001 itermax = 100, c = 1 by using training data as much as 170 datasets , this study resulted in an average accuracy of 80,55 %.
Optimasi Pemodelan Regresi Linier Berganda Pada Prediksi Jumlah Kecelakaan Sepeda Motor Dengan Algoritme Genetika Sema Yuni Fraticasari; Dian Eka Ratnawati; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 5 (2018): Mei 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Traffic accidents are increasing from year to year according to the Badan Pusat Stastistika record from 1992 to 2003. According to the World Health Organization (WHO), it noted that nearly 3,400 people per day died due to traffic accidents. Surabaya is one of the metropolitan cities in Indonesia. Population growth is quite fast because the city of Surabaya is also the capital of East Java province. The system predicts the area of ​​frequent traffic accidents based on the parameters used such as the length of the road, the width of the volume body, the velocity, the number of lanes, the number of directions, the boundary / median, the plot access and the shoulder width by using linear regression optimized with the genetic algorithm. The genetic algorithm uses real numbers with 10 of gene chromosome lengths. The crossover method used by the extended intermediate crossover while the mutation uses random mutation, and the selection uses elitism selection. From the results of the experiments conducted to produce population is 125, the best combination of cr and mr is 0,6:0,4 and the best generation is 700. Comparison of error rate by showing a lower error value of 0,5% compared with regression Which results in an error value is 1,5%.
Sistem Untuk Deteksi Penyakit Stroke Menggunakan Metode Analytical Hierarchy Process dan Weighted Product Ibrahim Kusuma; Arief Andy Soebroto; Dian Eka Ratnawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 6 (2018): Juni 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Stroke is a disease caused by blockage of blood in the brain or rupture of blood vessels in the brain, resulting in brain nerve palsy. Stroke is one type of diseases that kill high enough third after heart disease and cancer in developed countries. The data of East Asian Medical Information Center (SEAMIC) is the highest in Indonesia. This causes the disease to be wary of. Doctors sometimes have difficulty to perform stroke disease detection due to a semi-structured problem. These constraints can be overcome by a system that is Decision Support System using the method of Analytical Hierarchy Process and Weighted Product. Analytical Hierarchy Process method is used to find the priority weight and Weighted Product method used for decision making and ranking. The result of system functionality testing is 100%. As for the system accuracy testing has an accuracy of 73.8%.
Prediksi Harga Emas Batang Menggunakan Feed Forward Neural Network Dengan Algoritme Genetika Dimas Fachrurrozi Azam; Dian Eka Ratnawati; Putra Pandu Adikara
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

Investment is an activity to buy goods, with the purpose to be sold to other investors until they reach a high enough value. There are many types of investments, one of which is gold. Some people who are just starting out in investing find it difficult in deciding to buy and sell gold. Many losses will be obtained if the investor missteps in selling or buying gold. Based on the problem, the researcher intends to help the investor by proposing gold price prediction system using feed forward neural network (FFNN) with genetic algorithm. The genetic algorithm method is used to optimize the existing weights to be used with the forward neural network feed model to process the price prediction. From the test result, the total of 126 training data, and the total of 54 testing data, the CR value 0.3 and the MR value 0.7, the number of pop size is 250, the number of generations are 200, yields an average mean root mean square error (RMSE) of 0.304587%.
Penjadwalan Dinas Pegawai Menggunakan Algoritma Evolution Strategies pada PT. Kereta Api Indonesia (KAI) DAOP 7 Stasiun Besar Kediri Winda Fitri Astiti; Dian Eka Ratnawati; Mochammad Ali Fauzi
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

Scheduling employee service of PT. Kereta Api Indonesia aims to plan the number of employees on duty in turns based on each service time. Employee service scheduling is designed to meet scheduling in accordance with established standard operating procedures. The problem of scheduling the employee service has a very high complexity because in scheduling many factors must be considered such as the hours of work and the number of employees required by the office on a daily basis. The data used in this study is employee data of 14 employees who will be scheduled service. The algorithm used in this research is Algorithm Evolution Strategies. In the process of Evoluiton Strategies Algorithm the representation of chromosomes used is a representation of permutations, with length of gene 98, adjusted for the number of employees and the number of days for scheduling the employee service. The process of reproduction, mutation process using insert mutation. Process valuate the fitness value obtained from the calculation of the number of penalty value of each individual while the selection process used is elitism selection. In this algorithm generate scheduling according to the rules based on the optimal parameter of population size of 80 and many generations of 70 with average fitness value of 0.2. The result of this system is scheduling for a seven-day official schedule that complies with standard operating procedures established.
Peramalan Produksi Gula Pasir Menggunakan Fuzzy Time Series Dengan Optimasi Algoritma Genetika (Studi Kasus PG Candi Baru Sidoarjo) Afif Ridhwan; Dian Eka Ratnawati; Bayu Rahayudi
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

Production planning is done by PG Candi Baru Sidoarjo every year as an effort for improving the quality as consumers demand continues to increase. To optimize the production strategy PG Candi Baru should be able to estimate the next production target based on existing historical data. With fuzzy time series method which is optimized by Genetic Algorithm method, the writer wants to help solving the problem to predict the production of sugar, hopefully the research result can help as reference to be used as consideration to determine the amount of sugar production for the next month. Based on the result of testing the accuracy of predictive results using Mean Absolute Percentage Error (MAPE) method obtained the percentage of error rate 1.9% which means the qualification is good.
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