Claim Missing Document
Check
Articles

Optimasi Komposisi Pakan Ternak Ayam Petelur Menggunakan Algoritme Genetika Siti Fatimah Al Uswah; Budi Darma Setiawan; Dian Eka Ratnawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (611.631 KB)

Abstract

Raising laying hens are considered a promising opportunity in Indonesia because the demand for eggs in the country continues to increase in line with the increasing human lifestyle and need for animal protein. Based on data from the ministry of agriculture in 2017 there is an increase in chicken egg consumption during the year 1987-2017 of 3.57% per year with an average consumption of 6.63 kg / kap / th in 2017. On the other hand, raising laying hens is costly especially when it comes to livestock feed, which can cost farmers 60% -70% of production costs. One way to reduce the cost of purchasing feed is by optimizing the feed composition, with purpose of achieving an optimal feed composition that also meets the nutritional needs, all obtained with as minimal cost as possible. The optimization method used in this research is Genetic Algorithm with permutation representation, single-point crossover, reciprocal exchange mutation, and elitism selection. This study used 50 feed data material of laying chicken and its nutritional content. From the results of the tests, the population parameters obtained with the highest fitness value in the population of 500 and 800 with the average fitness value of 2.573591, the optimal generation of 100 generations with an average fitness value of 2.479726 and a combination of probability of crossover 0.5 and the probability of mutation 0.3 with the average fitness value 2.58459. The final result is the composition of laying chicken feed that meets the nutritional needs with minimal cost.
Optimasi Penjadwalan Ujian Semester Menggunakan Algoritme Genetika (Studi Kasus: STMIK Kadiri) Mayang Arinda Yudantiar; Budi Darma Setiawan; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (217.995 KB)

Abstract

Scheduling is an important issue in the implementation of activities, so that absence of such activities will not run smoothly. One example of scheduling is the scheduling of semester exam is performed on a STMIK Kadiri. Scheduling tests done still manually (conventional) so it may take longer computation. This is because the difficulty of putting slots schedule to avoid clashing occurs and there are lots of class but the test room which can be used a bit. So it needs optimization scheduling that is able to minimize conflicting schedules and activities the test can run well. Genetic algorithm is one of the most common optimization methods is used to solve the problems of scheduling. The data used in this study using the test schedule data will be represented in chromosomes, in the form of code exam schedule. Crossover method used is onecut point while mutase method using reciporal exchange mutation and elitism selection method and roulette wheel. The optimal parameter values ​​obtained based on the test result are population size 60, generation size as much as 850, with cr and mr value is 0,5 and 0,5. So the fitness value that is gained is 0.000574..
Algoritma Genetika Untuk Optimasi Fuzzy Time Series Dalam Memprediksi Debit Air (Studi Kasus: PDAM Indramayu) Mohamad Alfi Fauzan; Budi Darma Setiawan; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (286.72 KB)

Abstract

The availability of water in the country of Indonesia reaches 694 billion m3 per year, where the amount is a potential that can be utilized but only about 23% is utilized. With the increasing number of people needing clean water but low water debit distribution, the concept of forecasting or prediction is needed as one of the inputs in making decisions to increase the flow of water to be distributed. To solve these problems in this study fuzzy time series methods are optimized with genetic algorithms in predicting the distribution of water discharge. Genetic algorithm is used to optimize sub intervals in fuzzy time series. Based on the results of the test, the accuracy of the prediction results obtained using the Average Forecasting Error Rate (AFER) method obtained the percentage error rate of 15.33% which included in the good qualifications.
Peramalan Harga Cabai Menggunakan Metode High Order Fuzzy Times Series Multifactors Ridho Agung Gumelar; Budi Darma Setiawan; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (357.021 KB)

Abstract

The daily needs of Indonesian people can not be separated from agricultural commodities such as chili, onion, garlic, tomatoes and others. Some of these agricultural commodities have sharp price fluctuations, such as chili. When the supply of chilli in the market decreases, the price can be soar higher than the normal price. Conversely, when the supply of chili is excessive, the price will be fall well below the normal price. This is influenced by various factors such as the harvest season, the amount of production, the amount of public consumption, the area of the harvest area and others. Therefore we need a method to estimate the price off chili so that it can be used to support decision-making related to price issues. Forecasting is one solution to be able to estimate the price movement of chili commodities. The method used to forecast the price of chili is High Order Fuzzy Times Series Multifactors. In this method the formation of subinterva is done by using Fuzzy C-means. For calculate forecasting error results in this research using Mean Square Error (MSE). Based on the results of the test, the value of training data and orders used in forecasting does not guarantee a low error rate. The results of forecasting the price of chili using the method of High Order Fuzzy Times Series Multifactors get the best MSE results of 20,374.19.
Optimasi Komposisi Makanan Untuk Keluarga Penderita Diabetes Melitus Menggunakan Algoritme Genetika Azmi Makarima Yattaqillah; Imam Cholissodin; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (978.314 KB)

Abstract

Indonesia ranks 6th in the number of people with diabetes mellitus in the world. Of the 10.3 million Indonesians who have diabetes only 36.3 percent are diagnosed. As a result, many people do not have the right diet. The family of people with diabetes mellitus means a family with at least one member suffering from diabetes mellitus. This family is one of the factors that can increase the risk of suffering from diabetes mellitus by two to six times. Unhealthy lifestyles are also a cause of diabetes mellitus which makes diabetes a disease that can be prevented by consuming the right food starting from daily food in the family. Things that need to be considered in the right diet is to determine the composition of the right food, namely how to optimize nutrition in foods consumed by people with diabetes mellitus. Genetic algorithms that have reliability in producing optimal output, can be utilized in the preparation of daily food composition. In this study used integer chromosome representation, extended intermediate crossover method, reciprocal exchange mutation method, and elitism selection method. The best solution is obtained using max generation of 709 generation; population size of 250 individual; crossover rate of 0,4; and mutation rate of 0,6. The results of the global analysis show the calorie content of the food composition of the system meets expert tolerance standards and on average system can save costs by 27,27%.
Implementasi Metode Exponential Smoothing Untuk Prediksi Bobot Kargo Bulanan Di Bandara Internasional I Gusti Ngurah Rai Amaliah Gusfadilah; Budi Darma Setiawan; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (632.202 KB)

Abstract

Goods are important objects to meet people's needs and sometimes the procurement of goods can be done by transferring goods. Transfer of goods can use shipping via air transportation. However, the weight of the cargo indirectly can affect the speed of delivery. So that it demands the airport to always improve the provision of adequate facilities to meet the needs of cargo weight. To be able to meet these demands a mature prediction is needed. The prediction of cargo weight aims to determine cargo weight data in the future by using cargo weight data in the past. The prediction method used in this study uses the Exponential Smoothing method. Exponential Smoothing is a method that continually perfects predictive results by smoothing past values ​​of a data sequence by decreasing time. In this study comparing 3 Exponential Smoothing methods including Single Exponential Smoothing, Double Exponential Smoothing, and Triple Exponential Smoothing, where the method is used to generate predictive values ​​and then evaluate the results of predictions using the Mean Absolute Percentage Error (MAPE). The smallest MAPE is found in the Triple Exponential Smoothing method spanning 5 years with parameter values ​​α = 0.9, β = 0.1, and γ = 0.1 of 13.563. Based on the MAPE values ​​that have been obtained between 10 and 20, the Triple Exponential Smoothing method is included in the good criteria.
Prediksi Tingkat Pemahaman Siswa Dalam Materi Pelajaran Bahasa Indonesia Menggunakan Naive Bayes Dengan Seleksi Fitur Information Gain Siti Utami Fhylayli; Budi Darma Setiawan; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (388.297 KB)

Abstract

Indonesian Language Subjects are generally regarded as easy lessons and do not need to be studied by students and society. Based on this, various learning problems arose involving instructors, Indonesian language subjects, students who received lessons, teaching methods, facilities, ways to obtain, and the objectives of Indonesian language learning (Moeljono, 1989). The difference between each student in different learning differences. This causes the teacher to have limitations in measuring the level of understanding of students. Then a system is needed to predict the level of understanding of students. This prediction uses the classification method with the Naive Bayes algorithm. The class that will be used in this study is that students understand, are quite understanding and lack understanding. In this study, the authors used the Information Gain (IG) feature selection. The selected feature will be processed with the Naive Bayes classification algorithm, then the accuracy will be seen if it is not maximized, then the previous feature selection process will be done again to get the desired verification. From the tests that have been conducted, the results obtained which have a Gain value of more than 0.2 have the largest rating, reaching 90%. The features chosen from 17 included features of family members, residence status, mother's work, caregivers, family support, joining extracurricular activities, repeating lessons at home, length of study at home, reading at home, reading time at home.
Implementasi Metode Time Invariant Fuzzy Time Series Untuk Memprediksi Jumlah Keberangkatan Penumpang Pelayaran Dalam Negeri Di Pelabuhan Tanjung Priok Dwi Damara Kartikasari; Budi Darma Setiawan; Mochammad Ali Fauzi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (354.251 KB)

Abstract

Maritime transportation is considered to have an important contribution in advancing the national economy in Indonesia, considering that 75% of Indonesia's territory is in the ocean. Maritime transportation has also become an alternative of transportation between islands recently. Moreover with the increase in the number of vehicles on land from year to year resulting in congestion on the highway, of course this will further increase public interest in making maritime transportation an alternative to their transportation. But in every cruise, the number of passengers always decreases or increases. The uncertainty of the number of passengers must be predictable, so that further policies can be made from the port to anticipate the number of passengers in the future, in order to increase economic benefits in the sea transportation sector. The method used to make predictions in this research is Time Invariant Fuzzy Time Series with the data used is the number of cruise passenger departures at Tanjung Priok Port in the period January 2006 to December 2015. Based on the results of the test, the smallest of Mean Average Percentage Error (MAPE) is 17.39% using the number of fuzzy sets = 5; training data = 108, 96, 84, and testing data = 12.
Penerapan Metode Fuzzy Tsukamoto untuk Menentukan Harga Sewa Hotel (Studi Kasus: Gili Amor Boutique Resort, Dusun Gili Trawangan, Nusa Tenggara Barat) Rudito Pujiarso Nugroho; Budi Darma Setiawan; M. Tanzil Furqon
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1089.969 KB)

Abstract

Gili Trawangan is a place that is popular in the lndonesian and foreign traveler. ln the hospitality industry in Gili Trawangan they have 3 seasons, namely; low season, high season, and peak season. Gili Amor Boutique Resort is one of the hotels located on Gili Trawangan that has problem to determining the hotel rental price because they only estimates the hotel price to be rented based on the current season. Based on the problem, Fuzzy Tsukamoto was chosen because it has a monotone logic on each rules, which is each consequence of lF-THEN rules must be represented by a fuzzy set with a monotonus membership function. Fuzzy logic is use to solve periods in an linguistically or variabels that contain uncertainties rather than the numbers. The Tsukamoto Method has 3 stages, namely; fuzzification, fuzzy inference system, and defuzzification. Fuzzification functions to change the crisp value to fuzzy value. Fuzzy inference system are conclusions based on fuzzy rules. Defuzzification is the process of turning fuzzy output into a crisp value using weighted average concept. ln this research, the rules will be searched automatically by the system based on the data that has been inputted. The data that has been inputted will be added “event” to distinguish holidays, significant price, and etc. The result of this research obtained an error using MAPE amounting to 28.41% for data test with Studio type of rooms and 27.85% for data test with Premiere type of rooms.
Klasifikasi Pola Sidik Bibir Untuk Menentukan Jenis Kelamin Manusia Dengan Metode Gray Level Co-Occurrence Matrix Dan Support Vector Machine Eka Novita Shandra; Budi Darma Setiawan; Yuita Arum Sari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (515.702 KB)

Abstract

Identification is one way that can be done to recognize individual characteristics. Identification is needed to find out the clarity of personal identity, for both deceased and living people. In the world of forensic medicine, the role of identification is very important. Like fingerprints, lip prints also have unique characteristics for each individual. Lip prints can be used as a means to identify forensic and non-forensic cases. For nonforensic cases, lip prints can determine the sex of an individual. To help in the process of identifying gender based on lip prints, a classification system is needed that can classify the sex of women and men. The process begins with collecting lip print images which are then preprocessed and extracted texture features using the Gray Leveled Co-ocurrence (GLCM) method. There are 4 features that are used namely ASM, Contrast, Correlation and IDM with angles of 0o, 45o, 90o and 135o. Then the feature value is used by data for the training and testing process using the Support Vector Machine (SVM) method. The training data used in the test is 60 data. The results of this study have not provided a good level of accuracy because the system is only able to provide an accuracy of 51.4% by testing the GLCM parameter, namely distance = 1 and SVM parameters λ (lambda) = 0.5, C (complexity) = 1, constant (gamma) = 0.01, and itermax = 100.
Co-Authors Abdul Fatih Achmad Basuki Achmad Fahlevi Addin Sahirah, Rafifa Adinugroho, Sigit Aditya Chandra Nurhakim Aditya Kresna Bayu Arda Putra Agung Nurjaya Megantara Agus Wahyu Widodo Ahmad Afif Supianto Akhmad Eriq Ghozali Akmal Subakti Wicaksana Alfi Nur Rusydi Almira Syawli, Almira Amaliah Gusfadilah Andhi Surya Wicaksana Andika Harlan Angga Dwi Apria Rifandi Anjasari, Ni Luh Made Beathris Aria Bayu Elfajar Asghany, Yusrian Ashidiq, Muhammad Fihan Azmi Makarima Yattaqillah Baihaqi, Galih Restu Barlian Henryranu Prasetio Bayu Rahayudi Bintang, Tulistyana Irfany Budi Santoso Cahyo Adi Prasojo Candra Dewi Candra Dewi Chelsa Farah Virkhansa Cindy Inka Sari Cinthia Vairra Hudiyanti Civica Moehaimin Dhewanty Deby Chintya Dellia Airyn Delpiero, Rangga Raditya Dewi, Buana Dhan Adhillah Mardhika Dian Eka Ratnawati Diva, Zahra Dwi Anggraeni Kuntjoro Dwi Ari Suryaningrum Dwi Damara Kartikasari Edo Fadila Sirat Eka Novita Shandra Eka Yuni Darmayanti Eti Setiawati Fadhlillah Ikhsan Fajar Nur Rohmat Fauzan Jaya Aziz Fajar Pradana Fanny Aulia Dewi Fattah, Rafi Indra Fatwa Ramdani, Fatwa Febri Ramadhani Fikri Hilman Fitra Abdurrachman Bachtiar Fitria, Tharessa Fitrotuzzakiyah, Shafira Puspa Gandhi Ramadhona Gembong Edhi Setiawan Gilang Ramadhan Hendra Pratama Budianto Husin Muhamad Imam Cholisoddin Imam Cholissodin Imam Cholissodin Imam Cholissodin Indah Larasati Indriati Indriati Indriati Irawati Nurmala Sari Irfan Aprison Irma Lailatul Khoiriyah Irma Nurvianti Irma Ramadanti Fitriyani Ismiarta Aknuranda Issa Arwani Issa Arwani Jobel, Roenrico Karina Widyawati Keintjem, Arthurito Khairunnisa, Alifah Kholifa'ul Khoirin Koko Pradityo Lailil Muflikhah Lathania, Laela Salma M Kevin Pahlevi M. Ali Fauzi M. Raabith Rifqi M. Rikzal Humam Al Kholili M. Tanzil Furqon Mahar Beta Adi Sucipto, Ekmaldzaki Royhan Mahendra Data Mahendra Data Marji Marji Masayu Vidya Rosyidah Maulana, M. Aziz Mayang Arinda Yudantiar Meilia, Vina Mimin Putri Raharyani Mindiasari, Irtiyah Izzaty Miracle Fachrunnisa Almas Moch. Khabibul Karim Mochamad Chandra Saputra Mohamad Alfi Fauzan Muhammad Arif Hermawan Muhammad Dimas Setiawan Sanapiah Muhammad Harish Rahmatullah Muhammad Khaerul Ardi Muhammad Rizkan Arif Muhammad Syaifuddin Zuhri Muhammad Tanzil Furqon Mustofa Robbani Muthia Azzahra Nadia Natasa Tresia Sitorus Nainggolan, Cesilia Natasya Nanda Agung Putra Nashrullah, Nashrullah Nelli Nur Rahma Ni'mah Firsta Cahya Susilo Nihru Nafi' Dzikrulloh Noval Dini Maulana Novanto Yudistira Nur Intan Savitri Bromastuty Nurfansepta, Amira Ghina Nurhana Rahmadani Nurudin Santoso Nurul Hidayat Oky Krisdiantoro Olive Khoirul L.M.A. Panjaitan, Mutiharis Dauber Pindo Bagus Adiatmaja priharsari, diah Purnomo, Welly Putra Pandu Adikara Putra, Octo Perdana Putri, Rania Aprilia Dwi Setya Rachmatika, Isnayni Sugma Radifah Radifah Rafely Chandra Rizkilillah Rahmadi, Anang Bagus Rahmat Faizal Raissa Arniantya Ramadhianti, Fatiha Randy Cahya Wihandika Ratna Candra Ika Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Rekyan Regasari MP, Rekyan Regasari Rendi Cahya Wihandika Retiana Fadma Pertiwi Sinaga Revanza, Muhammad Nugraha Delta Revinda Bertananda Reza Wahyu Wardani Rhobith, Muhammad Ridho Agung Gumelar Rima Diah Wardhani Rinda Wahyuni Rizal Setya Perdana Rizal Setya Perdana Rizki Agung Pambudi Rizky Haqmanullah Pambudi Robih Dini Rosi Afiqo Rudito Pujiarso Nugroho Rudy Usman Azzakky Ryan Mahaputra Krishnanda Sabriansyah Rizkiqa Akbar Santoso, Nurudin Satrio Hadi Wijoyo Shelly Puspa Ardina Sigit Adinugroho Silfiatul Ulumiyah Sintiya, Karena Siti Fatimah Al Uswah Siti Utami Fhylayli Sri Wahyuni Suryani Agustin Sutrisna, Naufal Putra Sutrisno Sutrisno Tahajuda Mandariansah Talitha Raissa Tibyani Tibyani Tri Afirianto Tria Melia Masdiana Safitri Ulfah Mutmainnah Vina Meilia Wayan Firdaus Mahmudy Wildannantha, Jawadi Ahmad Yerry Anggoro Yosendra Evriyantino Yuhand Pramudita, Rezzy Yuita Arum Sari Yuita Arum Sari Yulfa Hadi Wicaksono Zubaidah Al Ubaidah Sakti