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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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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.
Identifikasi Kesalahan Penulisan Kata (Typographical Error) pada Dokumen Berbahasa Indonesia Menggunakan Metode N-gram dan Levenshtein Distance Arina Indana Fahma; Imam Cholissodin; Rizal Setya Perdana
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

Text is one of communication and information media in human life. The crucial thing in text writing is a mistake in word writing called typographical error. The error occurs while using the keyboard on computer or on smartphone. Typographical error on a text can lead to something unpredictable for some people. Based on that reason, a system is needed to identify typographical error in a text and also make the correction of the error word. N-gram and Levenshtein Distance method can be used for correcting typographical error in the text. For detecting how many word candidates of typographical error, Levenshtein Distance can be implemented. Because the word candidates are unsorted, N-gram method is using to sort those word candidates based on the value of cosine similarity. In this research, the reason N-gram method using N=2 is to separated each two characters of identified typographical error and its word candidates.The value of cosine similarity calculated by tf-idf when the process of N-gram was done. The result of test scenario, the best value of precision is 0.97 from insertion type and the best value of recall is 1 from substitution type.
Optimasi Komposisi Makanan Diet bagi Penderita Hipertensi menggunakan Algoritme Genetika Muhammad Shafaat; Imam Cholissodin; Edy Santoso
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

Hypertensive is one of the main causes of mortality and morbidity in Indonesia. as the result that, the clinical problems of the disease that is interventions which at various levels of health facilities are commonly done. For people with hypertension should be arranging their food menu to avoid and confine foods that can increase blood pressure. Therefore, it needed a diet to control the blood sugar levels in hypertensive patients by regulating the composition of the diet. One of techniques that is used to manage regulate the composition of diet foods for hypertensive patients used by genetic algorithm approach. The genetic algorithm process uses the representation of the integer with the length of chromosome 105, each gene of the population is the food number in each group and each index with multiples 15 represents of the day, The crossover method that is used the extended intermediate crossover, while the mutation method that is used reciprocal exchange mutation, and the selection method with elitsm selection. The optimal parameter results obtained on the test population number is 80 with the fitness value 1100.495433, the number of generations is 300 with the fitness value 1190.022286, and the combination of cr and mr is 0.1 and 0.9 with the fitness value 1150.466927. The results of the solution given in the form of food menu recommendations for few days for morning, noon, and night time and with minimal cost.
Optimasi Daftar Bahan Makanan Untuk Pasien Rawat Jalan dan Keluarga Menggunakan Algoritme Genetika Istiana Rachmi; Imam Cholissodin; Marji Marji
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

The consumption of Indonesian society tend to be less healthy which resulted in various diseases. High cholesterol disease and hypertension have a high proportion rate. Both of diseases can be treat with hospitalization and outpatient. Outpatient costs are cheaper than hospitalization. But to regulate the consumption patterns of the patient's food is still difficult because of lack of knowledge. Techniques that can be used to by using genetic algorithms. The data used in this case were 137 foodstuffs grouped into sources of carbohydrates, animal protein, vegetable protein, vegetables, fruits, grease, milk and sugar. In the process of genetic algorithm using representation of integer permutation based on food index with chromosome length 168, crossover method with extended intermediate, mutation method with exchange mutation, and selection method with elitism selection. After conducting the test, the optimum parameters produced are the population size of 80 individuals, the value of cr = 0.3 and mr = 0.7 and generation 100. The final result is food for breakfast, lunch and night for seven days with nutritional content Which suits the nutritional needs of all family members, varied foodstuffs and budget-appropriate costs.
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%.
Optimasi Fungsi Keanggotaan Fuzzy Dua Tahap menggunakan Algoritme Genetika untuk Penentuan Bakat dan Tingkat Persentase Kecerdasan Anak Khairiyyah Nur Aisyah; Imam Cholissodin; Candra Dewi
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

Every child has unequal talents and abilities. But not all parents can recognize about the talent that is actually owned by their child. Many parents are misjudge about the potential related to their child. As a result, many children do a subject which not appropriate with the passion they had and can not develop in their profession because of the minimum passion to it. With a system that can determine the talent and intelligence, it is expected that there is a good synergy between teachers and parents to provide an appropriate guidance accordance to the ability owned by them. The processes did on this research consists of 2-stages fuzzy.. The first stage is the determination of talent with Fuzzy Logic and the second stage is determining the percentage of child's intelligence level with Fuzzy Inference System Tsukamoto. The membership function of both will be optimized using Genetic Algorithm to get more optimal result. The accuracy obtained after the optimization with Genetic Algorithm is 87.91%, 27.08% better than without using optimization with an accuracy of 60.83%. The best fitness value was variation of chromosome with 7 genes, population size 100, number of generation is 70, and combination cr=0,8 and mr=0,2.
Implementasi Metode Analytic Hierarchy Process - Weighted Product Untuk Rekomendasi Hunian Ideal (Studi Kasus: Kota Malang) Rizaldy Aditya Nugraha; Indriati Indriati; Imam Cholissodin
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

The purpose of this study is to help prospective house buyers in getting the recommendation for an ideal house to be purchased. Prospective house buyers that were looking for a house of their dreams still found it difficult to obtain the appropriate recommendation suitable with their desires. Therefore, this study was conducted to create a decision support system application of ideal house recommendation to facilitate a prospective house buyer in obtaining an ideal house recommendation. The input data used on this system is a weight priority measure for each criteria and sub criteria of the house specified by the prospective house buyer. Then these input data are calculated by using analytic hierarchy process - weighted product method. The analytic hierarchy method is used to obtain the criteria and sub criteria weight which is then used for the calculation of weighted product method. The final result of this system is the rank order of ideal house recommendation. The test performed on this system is done on the pairwise comparison matrices with 80% accuracy.
Peramalan Kenaikan Indeks Harga Konsumen/Inflasi Kota Malang menggunakan Metode Support Vector Regression (SVR) dengan Chaotic Genetic Algorithm-Simulated Annealing (CGASA) Muhammad Maulana Solihin Hidayatullah; Imam Cholissodin; Rizal Setya Perdana
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

Inflation forecasting is complicated. Inflation rate calculated based on the rise in the consumer price index (CPI) is influenced by various factors ranging from volatile prices of various types of goods, rupiah exchange rate, world inflation rate, government policy, fluctuations in the supply of goods and demand. Hybridation algorithm of support vector regression (SVR) with chaotic sequences and genetic algorithms has been successfully applied to improve the accuracy of forecasting in various fields. But it has not been explored the usability of this algorithm in the field of market economy which is forecasting inflation. This journal will analyze the potential of hybridization algorithm that which is chaotic genetic algorithm-simulated annealing algorithm (CGASA) with SVR model to improve the performance of forecasting accuracy. With the chaotic sequence of chaotic sequences, it will be able to avoid premature local optimum and early convergention, especially with the simulated annealing algorithm that increases the search area of ​​the solution. The results of the forecasting test in this study show better accuracy than the previous research which has been studied is the combined ensemble method between autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) algorithm.
Optimasi Penjadwalan Asisten Praktikum pada Laboratorium Pembelajaran Menggunakan Algoritme Genetika (Studi Kasus : Fakultas Ilmu Komputer Universitas Brawijaya) Nadia Natasa Tresia Sitorus; Imam Cholissodin; Budi Darma Setiawan
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

Scheduling is an important thing to be prepared carefully for the sake of an activity doing well.Good and effective scheduling will make the activities work and be well organized. Practicumis a routine activity for the application of materials that have been accepted by students.Practicum can work well if the teaching schedule of the practicum assistant does not collidewith the lecture schedule or their other activities. Genetic algorithm is one of algorithm thatcan complete the teaching schedule of practicum assistant through computation process. Thedata in conducting the research is the data from practicum schedule, practicum assistant andthe schedule of the assistant's willingness. The code of the practicum assistant is representedon the chromosome using the permutation method. The sequence of genes on thechromosomes represents the code of the practicum schedule. The crossover method appliedis one-cut-point, with mutation method using reciprocal exchange, and elitsm selectionmethod. The test result obtained optimal genetic algorithm parameter with total population5000, generation 500, with cr and mr value is 0,9 and 0,1. The output of the system is theteaching schedule of the laboratory teaching assistant.
Optimasi Jumlah Pinjaman Koperasi Menggunakan Fuzzy Tsukamoto Dengan Algoritme Genetika Shelly Puspa Ardina; Imam Cholissodin; Budi Darma Setiawan
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 the majority of cooperatives are still performing calculations lending manually and very rarely utilize the use of computer technology so that in decision making is done less efficient. From the problems encountered, it takes a system that has a relationship with the computer so that it can accelerate and assist the process of making the decision of lending efficiently. The required system is an artificial intelligence system that helps to get the most precisely seen value of the greatest fitness as each of its calculations. The criteria that become the basis for determining the loan amount to the members using the optimized Tsukamoto Fuzzy method using Genetic Algorithm are job status, age, salary and loan duration. The results will be able to show the fitness in each of the calculations that have been optimized by using Genetic Algorithm, so it will get the most appropriate value. The result of system evaluation using Mean Absolute Percentage Error calculation with the example of a case has an error value of 0.661468035 or 1.65% with the resulting fitness value of 0.601877363.
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