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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Imam Cholissodin
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Prediksi Nilai Tukar Rupiah Indonesia Terhadap Dolar Amerika Serikat Menggunakan Metode Recurrent Extreme Learning Machine Neural Network Daneswara Jauhari; Imam Cholissodin; Candra Dewi
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

The exchange rate of money by some people who are involved in the economy, especially the inter-state economy is very payed, often influencing one's decision in taking a policy. However, the exchange rate is a very unstable value, has a lot of noise and fluctuation, it is very difficult to predict the exchange rate. Research on exchange rate prediction has become the most challenging research among researchers, and that is considered one of the most important areas of research in international finance. Therefore, an application is needed, which can better predict the exchange rate of Indonesian Rupiah against the US Dollar. In this study the authors use the method of Recurrent Extreme Learning Machine Neural Network (RELMNN), the method can handle time-ordered datasets and can improve the ability of the Extreme Learning Machine (ELM) method in training and adapting. After testing with optimum parameters, and compared with ELM method, we found out that RELMNN method is superior to ELM method with Mean Absolute Percentage Error (MAPE) value of 0.069502%, while ELM method get MAPE 0.090423%.
Sistem Pendukung Keputusan untuk Rekomendasi Wirausaha Menggunakan Metode AHP-TOPSIS (Studi Kasus Kab. Probolinggo) Ghulam Mahmudi Al Azis; Imam Cholissodin; Muhammad Tanzil Furqon
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

Along with the growing number of Indonesian population, also raises the competition in looking for work. The limited job vacancy impacts the increasing number of unemployed every year. Until February 2016, the labor force in Indonesia reached 127 million people with an overall unemployment rate of 5.5% or 7 million people. To overcome this increasing number of unemployment, needed step solution that is in the form of decision support for entrepreneurship. Decision support systems can be used to recommend an entrepreneur for unemployment or everyone. AHP method and TOPSIS method is one of the methods of decision support system that can be combined with calculating the weight of criterion using AHP method then continued by calculating the value of preference for ranking from entrepreneurial alternative using TOPSIS method. The AHP-TOPSIS method will recommend the results of 3 entrepreneurs with the highest preference value. In accordance with the test results, that these application can help to recommend entrepreneurs in helping decisions support for user to choose an entrepreneur.
Implementasi Algoritma Particle Swarm Optimization (PSO) untuk Optimasi Pemenuhan Kebutuhan Gizi Balita Leni Istikomah; Imam Cholissodin; Marji Marji
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

Toddlers are children with 1-5 years age range. According to Riskesdas, in the year 2007, 2010, and 2013 the percentage of cases of malnutrition tends to increase, especially in toddlers. In the fulfillment of nutrients, one type of food alone is not enough so it requires a variety of food ingredients that contain all the elements of nutrients. Efforts to improve child nutrition have been done by the government through Posyandu to monitor and provide more servants to toddlers. Nutrition needs of Indonesian people has been set in the guidelines of Pedoman Gizi Seimbang by the Ministry of Health Republic Indonesia, including nutritional guidelines to meet the nutritional needs of infants. However, the nutritional guidelines only provide the value of the nutrient content of each foodstuff, making it difficult for Posyandu staff to provide menu variations to fit the needs of children according to their health condition. In this research give recommendation of variation of foodstuff automatically by using optimization process of Particle Swarm Optimization algorithm so that it can facilitate Posyandu and parents of toddlers in providing daily food according to the nutritional needs of toddlers. Based on the test results, the most optimal parameter is the number of particles = 30, Wmin = 0.4, Wmax = 0.7, C1 = 2, C2 = 1.5, Number of iterations = 40 and Upper Limit Permutation number of 75 resulting in average energy, protein, fat and carbohydrate difference of 16.04%, -8.08%, 2.85% and 25.98% which can save parents toddlers by 28.56%.
Optimasi Biaya Bahan Menu Makanan bagi Penderita Penyakit Jantung dengan Menggunakan Metode Evolution Strategies Veronica Kristina Br Simamora; Imam Cholissodin; Mochammad Ali Fauzi
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

People who suffered heart disease should get serious handling. Not only taking medicines regularly, maintaining diet and nutritional intake for the body is also important. The price of the food ingridients which tend to be unstable makes it difficult for patients to consume foods in meeting their nutritional needs. This research used evolution strategies algorithm to optimize the cost of food ingidients for people with heart disease. Evolution strategies algorithm consists stages of initialization population with the real-vectors chromosome representation, reproduction method using intermediate recombination, and mutation, evaluation, and selection with method called elitism. The parameters were tested by the number of population testing, number of offspring testing, number of recombination testing, and generation testing. The greater the number of populations, number of offsprings, and generations does not guarantee produce more optimal results. The greater the number of population, the number of offspring, and many generations will bring up the various chromosomes, so the chances of this algorithm produce more optimal results will be even greater. This result can happen because the basic concepts of evolution strategies algorithms that use random values in the calculation process. Number of recombination testing indicates that the fewer parent's chromosomes involved in recombination will result a varied number of offspring's chromosomes. The more varied the result of offspring's chromosomes then the chances to achieve optimal results are greater. From the parameter tests results, this research obtained that the system can meet the nutritional needs of patients using the initial 105 population, 430 offspring produced, involving 2 parents on recombination, and 400 generations. Comparison of recommended food system recommendations with expert recommendations shows that the system has provided more optimal results compared to expert recommendations. This proved that the system delivers recommendations with cheaper prices and foods that varies.
Optimasi Komposisi Bahan Makanan bagi Pasien Rawat Jalan Penyakit Jantung dengan Menggunakan Algoritme Particle Swarm Optimization (PSO) I Gusti Ayu Putri Diani; Imam Cholissodin; Suprapto Suprapto
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

Heart is an organ which is very important in the body that pumps blood. Many people can suffered heart disease caused by unhealthy lifestyle. Most of the deaths, according to the report of the World Health Organization (WHO), caused by cardiovascular disease that cause 17.7 million or approximately 45%. For people who suffers with heart disease, take care of food consumption is important in order to be healthy again. This research will be conducted on the giving food ingredients for the patients who suffers cardiovascular disease whose can continue their treatment in their home.Research conducted is optimizing the composition of the food ingredients for cardiovascular disease outpatient by using particle swarm optimization algorithm which the results will be displayed in the program is data such as age, weight, height, along with recommended of food ingredients and minimum price of each food ingredients.This algorithm consists stages of initialize particles, calculating fitness value, define pbest and gbest value, calculating velocity and position of particles. The results from this research, it is found that the optimal parameters are the number of particles are 40 particles, the value of ωmax is 0,75, the value of ωmin is 0,25, the value of C1 is 2, the value of C2 is 2 and the number of maximum iterations are 80 iterations. The results of the program using these parameters resulted in an average difference from actual patients data and the results from the program of 4,67%. Moreover, the result of this research can reduce expenses up to 14,68%.
Sistem Rekomendasi Bahan Makanan Bagi Penderita Penyakit Jantung Menggunakan Algoritma Genetika Elisa Julie Irianti Siahaan; Imam Cholissodin; Mochammad Ali Fauzi
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

Lack of public awareness in regulating the consumption of food based on nutrition can cause several diseases including heart disease. Heart disease is caused from blockage of cholesterol and fat in the coronary artery. It is very important for people with heart disease to regulate food intake in order to reduce the blockage. Managing the food for the heart diet is difficult because heart diet is different from the other diets, because the amount of protein and fat is reduced. Genetic algorithms can solve the problem of managing food by computation process. The data that are used in this research are diet food ingredients data that consist of 8 kinds of food ingredients, carbohydrate, animal protein, vegetable protein, vegetable, fruit, milk, sugar and oil. In converting food into chromosome, chromosome real code representation is used. The crossover method that is used is extended intermediate crossover, the mutation method that is used is random mutation and the selection method is elitism selection. From the results of the testing, the optimal parameter scores of the genetic algorithm are the population number of 280 with the average fitness score of 103.7, Cr and Mr scores are 0.5 and 0.5 with the average fitness score of 103.3 and for the generations score is 100 with average fitness score of 111.2. Output of the system is food ingredients recommendation with 5 times a day meal time, which consists of breakfast, snack, lunch, snack and dinner with number of days based on user choice.
Optimasi Penjadwalan Mata Pelajaran Pada Kurikulum 2013 Dengan Algoritme Genetika (Studi Kasus: SMA Negeri 3 Surakarta) Radita Noer Pratiwi; Imam Cholissodin; Putra Pandu Adikara
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

Scheduling is one of the most difficult computing problems to solve. Problems in scheduling also occur in SMA Negeri 3 Surakarta which has implemented the 2013 curriculum with the system of university credit unit which for the implementation consists of two courses, namely 4 semester program and 6 semester program. Genetic algorithm is a search method that can be used to obtain optimal solution. Representation of chromosome in the research is divided into two segments, those ares chromosome length 748 for 6 semester program and 86 4 semester program. The optimal solution is obtained from the test that conducted 10 times and obtained the optimal parameter value of population size 600 individuals, the number of generations 1000 times, the value of cr 0.5 and the value mr 0.5. The results of the optimal solution in the form of course schedules for the 6 semester program and 4 semester program obtained from the highest fitness value of 0.16208. The result of the solution obtained from the highest fitness value is not optimal because there are still violations on the constraint in the scheduling of the courses in SMA Negeri 3 Surakarta.
Penentuan Komposisi Pakan Ternak untuk Memenuhi Kebutuhan Nutrisi Ayam Petelur dengan Biaya Minimum Menggunakan Particle Swarm Optimization (PSO) Brigitta Ayu Kusuma Wardhany; Imam Cholissodin; Edy Santoso
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

Feeding in accordance with nutritional needs of laying hens is the most important thing to be considered. This is because, the feed given will affect the amount and quality of the eggs produced. In addition, feed also affects the success of a chicken breeding business, where required a big amount of feed costs. So farmers must make an appropriate combination of the feed in order to obtain the minimum cost but with adequate nutrition. To obtain that feed combination, a research is conducted using Particle Swarm Optimization (PSO). PSO is one of the optimization methods that can solve the problems of feed combination to obtain the adequate nutrition of laying hens, so the farmer's income will be maximize. This research uses a real representation of code where each particles have long number with the data feed material used is 40. Each dimension in a particle represents the weight of the feed material. According to the test results, obtained the best parameters, such as swarm size = 350, number of iteration = 500, ωmax = 0.9 and ωmin = 0.4, c1i = 2.5 and c1f = 0.5 also c2i =0.5 and c2f = 2.5, then the best number of iteration according to the convergence test is 330. The final result is a combinational of best feed ingredients with nutritional met and minimum cost.
Optimasi K-Means untuk Clustering Kinerja Akademik Dosen Menggunakan Algoritme Genetika Budi Santoso; Imam Cholissodin; Budi Darma Setiawan
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

Lecturers are teacher for students, besides teaching, lecturers also have many other activities by utilizing the expertise they have to develop the potential of the lecturer. Some of the characters that each lecturer are so different, such as education, research, dedication, administration, and support. The difficulties faced by the campus, one of them is related to the grouping of assignments to lecturers. The assignment is related to further studies, recommendations, structural related positions, filling an event, commission, etc.So that required a system that can classify the academic performance of lecturers optimally. In this study to classify the academic performance of lecturers using K-Means method is optimized with genetic algorithm. Genetic algorithm acts to optimize the cluster's initial center on K-Means.Data algorithm used in this research is the data of lecturers in UB's Computer Science faculty in 2016. The data obtained from GJM faculty of computer science of Universitas Brawijaya. The result of clustering test of academic performance of lecturer using GA-Kmeans algorithm has higher cluster quality that is 2,74% compared to K-Means algorithm without genetic algorithm, where the cluster quality obtained using Silhouette Coefficient method.
Optimasi Menu Makanan Untuk Pemenuhan Gizi Penderita Kanker Dengan Algoritme Genetika Dellia Airyn; Imam Cholissodin; Budi Darma Setiawan
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

One of the most feared disease in the world today is cancer. For cancer patients, various ways have been done, one of them is chemotherapy. But in chemoteraphy, patients will experience digestive and absorption of nutrients disorder, thus affecting the nutritional status of patients. So, the menu orders for cancer patients become the most important thing to reduce the side effect of chemoteraphy, especially in term to fulfill the needs of energy and protein. In this study, there are 111 food menu, consist of 31 foods source of carbohydrate, 34 foods source of animal protein, and 46 foods source of plant protein.The method in this study using genetic algorithm, which is an optimization algorithm that similar to evolution theory in case determining the chromosomes or individual.The representation used is a permutation representation, with One-Cut Point Crossover and Reciprocal Exchange Mutation methods. The results and analysis of crossover rate and mutation rate combination against the average fitness value showed 0,6;0,4 has the largest average value, which is 762,19. In population test, the highest average fitness score was 631,16 in the 300th population. While in generation test, the highest average fitness value was 666,22 in the 200th generation.
Co-Authors Achmad Arwan Adam Syarif Hidayatullah Adhipramana Raihan Yuthadi Adhitya Wira Castrena Adinugroho, Sigit Ageng Wibowo Agus Wahyu Widodo Aldino Caturrahmanto Alfen Hasiholan Alif Fachrony Ana Holifatun Nisa Anandita Azharunisa Sasmito Andika Eka Putra Andriko Hedi Prasetyo Anggi Novita Sari Anim Rofi'ah Annisa Alifia Annisaa Amalia Safitri Aqmal Maulana Tisno Nuryawan Ardiansyah Setiajati Arief Andy Soebroto Arina Indana Fahma Arsti Syadzwina Fauziah Atika Anggraeni Aulia Dinia Aulia Herdhyanti Aulia Jasmin Safira Azmi Makarima Yattaqillah Bahruddin El Hayat Bana Falakhi Bayu Andika Paripih Bayu Rahayudi Benita Salsabila Bisma Anassuka Bondan Sapta Prakoso Brendy Oscar Munthe Brigitta Ayu Kusuma Wardhany Budi Darma Setiawan Budi Santoso Candra Dewi Cindy Cynthia Nurkholis Citra Nadya Dwi Irianti Daisy Kurniawaty Danastri Ramya Mehaninda Daneswara Jauhari Daniel Agara Siregar Dellia Airyn Diah Priharsari Dian Eka Ratnawati Dieni Anindyasarathi Dinda Adilfi Wirahmi Diva Kurnianingtyas Dyah Ayu Wahyuning Dewi Edy Santoso Ega Ajie Kurnianto Elisa Julie Irianti Siahaan Ellita Nuryandhani Ananti Elmira Faustina Achmal Ema Agasta Ema Rosalina Eriq Muh. Adams Jonemaro Ersya Nadia Candra Fahri Ariseno Faizatul Amalia Faturrahman Muhammad Suryana Fayza Sakina Maghfira Darmawan Febriyani Riyanda Felicia Marvela Evanita Fendra Gunawan Ficry Agam Fathurrachman Fikhi Nugroho Fildzah Amalia Firda Priatmayanti Fitra Abdurrachman Bachtiar Franklid Gunawan Galih Ariwanda George Alexander Suwito Ghulam Mahmudi Al Azis Gregorius Dhanasatya Pudyakinarya Guruh Adi Purnomo Gusti Reza Maulana Heny Dwi Jayanti Heru Nurwarsito Himawat Aryadita Holiyanda Husada Husin Muhamad I Gusti Ayu Putri Diani Ibnu Rasyid Wijayanto Ichwanda Hamdhani Ika Oktaviandita Indriati Indriati Irma Lailatul Khoiriyah Ishak Panangian Sinaga Istiana Rachmi Izzatul Azizah Jeffrey Junior Tedjasulaksana Khairinnisa Rifna Khairiyyah Nur Aisyah Komang Anggada Sugiarta Kresentia Verena Septiana Toy Kukuh Wicaksono Wahyuditomo Laila Restu Setiya Wati Lailil Muflikhah Leni Istikomah Liwenki Jus'ma Olivia M. Ali Fauzi M. Khusnul Azhari Mahendro Agni Giri Pawoko Marji Marji Maulana Ahmad Maliki Maulana Putra Pambudi Mauldy Putra Pratama Mentari Adiza Putri Nasution Michael David Moch Bima Prakoso Moh. Ibnu Assayyis Mohammad Aditya Noviansyah Mohammad Angga Prasetya Askin Mohammad Toriq Muhammad Aghni Nur Lazuardy Muhammad Dio Reyhans Muhammad Fahmi Hidayatullah Muhammad Fuad Efendi Muhammad Halim Natsir Muhammad Hasbi Wa Kafa Muhammad Hidayat Muhammad Maulana Solihin Hidayatullah Muhammad Nadzir Muhammad Rizal Ma'rufi Muhammad Rois Al Haqq Muhammad Shafaat Muhammad Syafiq Muhammad Tanzil Furqon Muhammad Taufan Mukh. Mart Hans Luber Nabila Lubna Irbakanisa Nabilla Putri Sakinah Nadia Natasa Tresia Sitorus Nadia Siburian Nadiah Nur Fadillah Ramadhani Nining Nahdiah Satriani Noerhayati Djumaah Manis Novanto Yudistira Novirra Dwi Asri Nur Afifah Sugianto Nur Firra Hasjidla Nurul Hidayat Nurul Inayah Obed Manuel Silalahi Panji Husni Padhila Priscillia Vinda Gunawan Putra Pandu Adikara Putri Ratna Sari Radita Noer Pratiwi Randy Cahya Wihandika Ratih Kartika Dewi Rayhan Tsani Putra Renata Rizki Rafi` Athallah Restu Fitriawanti Reyvaldo Aditya Pradana Reza Aprilliana Fauzi Rien Difitria Rinindya Nurtiara Puteri Rio Cahyo Anggono Riski Ida Agustiyan Rizal Aditya Nugroho Rizal Setya Perdana Rizaldy Aditya Nugraha Rizky Ramadhan Rosintan Fatwa Rowan Rowan Sabrina Nurfadilla Salsabila Multazam Sandya Ratna Maruti Sari Narulita Hantari Satria Habiburrahman Fathul Hakim Sayyidah Karimah Shafira Eka Aulia Putri Shelly Puspa Ardina Shibron Arby Azizy Shinta Anggun Larasati Siti Mutdilah Sofi Hidyah Anggraini Stefanus Bayu Waskito Supraptoa Supraptoa Sutrisno Sutrisno Tara Dewanti Sukma Tibyani Tibyani Timothy Bastian Sianturi Tobing Setyawan Tony Faqih Prayogi Tusiarti Handayani Tusty Nadia Maghfira Uke Rahma Hidayah Uswatun Hasanah Utaminingrum, Fitri Vergy Ayu Kusumadewi Veronica Kristina Br Simamora Vinesia Yolanda Vivilia Putri Agustin Vivin Vidia Nurdiansyah Wahyu Bimantara Wanda Athira Luqyana Wicky Prabowo Juliastoro Windy Adira Istiqhfarani Yessica Inggir Febiola Yoseansi Mantharora Siahaan Yudha Ananda Kresna Yudo Juni Hardiko Yuita Arum Sari Yunico Ardian Pradana Yusuf Afandi Zanna Annisa Nur Azizah Fareza