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All Journal Jurnal Bisnis dan Manajemen Journal of Innovation and Applied Technology Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal POINTER Jurnal Pengabdian Kepada Masyarakat (Indonesian Journal of Community Engagement) Sinkron : Jurnal dan Penelitian Teknik Informatika Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Seminar Nasional Teknologi Informasi Komunikasi dan Industri DIKEMAS (Jurnal Pengabdian Kepada Masyarakat) JPKMI (Jurnal Pengabdian Kepada Masyarakat Indonesia) Jurnal Sistem Informasi, Teknologi Informasi, dan Edukasi Sistem Informasi (JUST-SI) Bulletin of Social Informatics Theory and Application
Bayu Rahayudi
Fakultas Ilmu Komputer - Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Public Health Social Sciences

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Penerapan Algoritme Support Vector Machine (SVM) Pada Pengklasifikasian Penyakit Kucing Jumerlyanti Mase; Muhammad Tanzil Furqon; Bayu Rahayudi
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

Kucing merupakan hewan peliharaan yang sering ditemukan di masyarakat. Pemeliharaan kucing memerlukan perhatian yang besar agar kucing tidak terserang penyakit yang dapat membahayakan kucing, pemiliknya ataupun orang yang melakukan interaksi langsung dengan kucing tersebut. Penyakit pada kucing biasanya disebabkan oleh virus, bakteri atau jamur. Kemiripan gejala yang muncul pada penyakit kucing membuat masyarakat umum sulit mendeteksi penyakit yang menyerang kucing tersebut. Sehingga dibutuhkan sistem yang dapat membantu pengklasifikasian terhadap gejala penyakit yang timbul pada kucing untuk mendiagnosis penyakitnya dengan tepat. Sistem yang digunakan untuk pengklasifikasian penyakit kucing ini mengunakan algoritme Support Vector Machine (SVM) dengan menerapkan strategi One-Against-All untuk permasalahan multi class. Penelitian ini menggunakan 220 data dengan 9 hasil klasifikasi yaitu Scabies, Gastritis, Helminthiasis, Rhinitis, Dermatitis, Dermaphytosis, Otitis, Enteritis dan kucing sehat. Hasil akurasi yang dihasilkan oleh sistem ini dengan menggunakan perbandingan rasio data 90% : 10% dan kernel RBF adalah 80,2%. Dengan hasil akurasi yang baik, maka penelitian ini dapat diterapkan untuk membantu melakukan pengklasifikasian penyakit kucing dengan menggunakan algoritme Support Vector Machine (SVM).
Implementasi Algoritma Support Vector Machine (SVM) Untuk Penentuan Seleksi Atlet Pencak Silat Eni Hartika Harahap; Lailil Muflikhah; Bayu Rahayudi
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

Pencak Silat is a traditional martial art originating from Indonesia. Along with an evolution of the time pencak silat is not only used to protect and defend themselves from opponents, but also show in a contest. Determination of the final result in selection that still counts the manual becomes main obstacle of the jury when one of the parties can't accept defeat while competing. To overcome these problems required a classification system that is able to classify enrolment acceptance of the pencak silat athletes had eligible pass the support vector machine (SVM) method by the SVM classifying the data into two classes. The data used in this research is 110 whitch is divided into training data and test data with 2 classes of acceptance of selection is pass and not pass. The best accuracy result in this research based on experiment ratio of data 70% : 30%, using kernel Polynomial Degree d = 2 and parameter value λ (lamda) = 0,1, γ (gamma) = 0,0001, ε (Epsilon) = 0.000001, C (Complexity) = 0.00001 and Itermax = 250. Kernel use in this research value of Polynomial Degree 2. The average result of accuracy using SVM method in the classification enrolment of the Pencak Silat athletes is 69,09 %.
Analisis Optimasi Multiple Travelling Salesman Problem Time Window Pada Algoritme Genetika Terhadap Pemilihan Rute Pengiriman Barang J&T Express Surabaya Eko Wahyu Hidayat; Agus Wahyu Widodo; Bayu Rahayudi
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

J&T Express is a company engaged in the service of shipping the goods. The process of delivery of the goods on the J&T Express speed levels very seriously, because it has to be timely in serving all the customers with the maximum time duration of 1x24 hours to 2x24 hours. Delivery of the goods on the field do not always meet the target because some non technical issues. One of the reasons is the level of congestion in some cities that make the delivery of goods is hampered. This research has the objective to create a system that is able to find a line with a low level of congestion and are able to find routes with the fastest travel time that you visit our sales more than one, that problem is called with Multiple Travelling Salesman Problem Time Window (MTSP-TW). Genetic algorithms is one method that can be used to solve the problem of MTSP-TW, so it can search through the route with a fastest journey time. The test results on the analysis of the selection of shipping routes shows that the crossover one cut point with mutation insertion produces a fitness better combination than other reproduction, and the results of the selection of the route of the system generates a time faster than the route choice company.
Klasifikasi Kualitas Susu Sapi Menggunakan Algoritme Support Vector Machine (SVM) (Studi Kasus: Perbandingan Fungsi Kernel Linier dan RBF Gaussian) Arif Indra Kurnia; Muhammad Tanzil Furqon; 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

Cow milk has a lot of animal protein and have benefit for children and whoever in process for grow up. Cow milk contains good essential amino acids. Malang Animal Health Laboratory as the unit executor in east java Animal Husbandry Department do a test in kesmavet for efforts to secure milk as a farm product with appropriate testing in suitable with the Indonesian National Standard (SNI). The classification of cow milk quality is still using organoleptic (smell, taste, color) that are linguistic, so that variable and parameter are uncertain and become themain obstacle of expert in determining good milk quality. To resolve this issue, this can be done with schizophrenia classification using support vector machine (SVM) algorithm, which SVM performace is more suitable than other classification methods. In this study there are 269 data that is divided into two data that is data training and data testing with three classification result, that is low, medium, and hight. The result in this paper get the best acuracy based K-Fold Cross Validation as much 10 fold, with Kernel RBF and Kernel Linear with value λ (lambda) = 0,0001, C (complexity) = 1, γ (gamma) =0,0001, maximum iteration = 30 and σ kernel RBF= 10. The highest accuracy using SVM method in cow milk quality classification use Kernel RBF was 96% and the highest accuracy use Kernel Linear was 62%.
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.
Optimasi Penjadwalan Mata Pelajaran pada Kurikulum 2013 dengan menggunakan Hibridisasi Algoritme Genetika dan Simulated Annealing (Studi Kasus: SMA Negeri 6 Surabaya) Priscillia Vinda Gunawan; Imam Cholissodin; 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

Scheduling is one of the computational problems that is not easily solved. For solving it must be prepared systematically, by maximizing resources and time available effectively and efficiently. Scheduling problems can occur in various fields, including education. SMA Negeri 6 Surabaya is one of the high schools in Surabaya that has problems finding the right time slot with a limited number of teachers and there are some constraints that must be met in the scheduling of subjects. One method that can be used in the scheduling of subjects is to use genetic algorithm hybridization and simulated annealing (GA-SA) because GA has the weakness of early convergence and possibly stuck in local optimum, then SA is given as a solution to cover the weakness of GA and able to survive on a local optimum. The algorithm hybridization process is done with the first step in GA using chromosome representation of integer numbers, one-cut point crossover, reciprocal exchange mutation, and elitism selection. In the second step, a simulated annealing process is done using neighborhood move. The results given are scheduling the subjects by meeting the existing constraints. Based on the research, the optimum parameters are the number of generation 270, the population 90, the combination of cr and mr are 0.3 and 0.7 with the average fitness value of 0.999000.
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%.
Implementasi Algoritme Support Vector Machine (SVM) Untuk Klasifikasi Penyakit Dengan Gejala Demam Nurul Ihsani Fadilah; Bayu Rahayudi; Muhammad Tanzil Furqon
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

Infectious disease in humans have one of the general indications, that is Fever. There are three diseases with symptoms of fever that transmission of disease occurs by the media Arthropod-borne disease, such as dengue fever, malaria, and typhoid. The disease has almost the same clinical symptoms, that is difficult to make a diagnosis of the disease suffered by the patient. Because of a large number of patient and a high risk of death in this disease, need a system that can distinguish these three diseases quickly and precisely. To solve the problem, the system is needed to classify the disease with fever symptoms using the Support Vector Machine (SVM) algorithm. This research uses 130 datasets that have 15 parameters. The dataset is divided into train data and test data by using K-Fold Cross Validation method, with k=10. The final result from SVM algorithm implementation for disease classification with symptoms of fever is the accuracy of the system capabilities in classifying dengue fever class, malaria class, and typhoid class. So, the best average value of accuracy in this implementation is 99.23%, using k-fold cross validation, with k=10, division of data ratio=90%:10%, and the parameters used are lamda=0.5, gamma=0.01, C(Complexity)=1, epsilon=0.0001, maximum iteration=20.
Implementasi Gripper Pada End Effector Robot Untuk Memegang Telur Ayam Dengan Sensor FSR (Force Sensitive Resistor) Alfian Reza Pahlevi; Dahnial Syauqy; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Robots with gripper can help users to grab objects in a place that is unattainable to humans. Users also do not need to directly interact with the object directly because the robot can be controlled wirelessly with the help of wifi and Android devices. As a substitute for the senses of taste on human skin is used FSR sensor (Force Sensitive Resistor). This sensor is used to obtain the value of the gripper's closeness when grabbing the object. To overcome the damage of the object, the gripper is implemented can stop automatically by using the threshold value. The threshold used is 552. The value of 552 is obtained from the average result on the 10 data acquisition of sensor values ​​using the FSR sensor with manual experiment. When the value of the sensor obtained through the threshold, then the robot gripper will automatically stop. This is done to prevent damage to the chicken egg object. From the test as much as 10 times on the robot gripper, obtained test results with 100% percentage that the system can stop gripper and chicken egg object is not damaged. From the test results obtained different pressure values ​​on each object. This may be due to layers of chicken egg object is different or the value of the sensor that keeps changing.
Peramalan Status Siaga Banjir Berdasarkan Data Curah Hujan (ARR) dan Tinggi Muka Air (AWLR) Menggunakan Metode Fuzzy Time Series (Studi Kasus: Perum Jasa Tirta I) Arina Rufaida; Muhammad Tanzil Furqon; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Flood is a condition where water flow is higher than normal water level so it flooded the surrounding area. Floodwaves flow from upstream to downstream and interact with increasing water capacity of the estuary. Floods can occur due to high rainfall, overflow from the river, the destruction factor of Watershed (DAS). From that point on, a system that is able to forecast to make it easier to analyze the flood alert status in the future. Regression method used in this research is Fuzzy Time Series. The FTS method is a model usually used to forecast data in sequence. This research has a goal to forecast flood alert in Kambing Station DAS Brantas . The results of the test show the prediction of flood alert on the water level data (AWLR) that is in December 2016 got the error value (RMSE) of 2.89 and rainfall data (ARR) in February 2015 got the error value (RMSE) of 16.0. Both data resulted flood alert forecasting that shows Normal.
Co-Authors Abdullah Harits Abdurrahim, Ahmad Azmi Abhiram, Muhammad Tegar Achmad Choirur Roziqin Achmad Ridok Adam Hendra Brata Ade Wahyu Muntizar Adi Mashabbi Maksun Adi Maulana Rifa'i Adi, Tri Adinda Putri, Lintang Gladyza Adinugroho, Sigit Aditya Septadaya Aditya, Nathanael Chandra Afif Ridhwan Ageng Wibowo Agus Wahyu Widodo Agus Wahyu Widodo, Agus Wahyu Ahmad Afif Supianto Ahmada Bastomi Wijaya Aldi Bagus Sasmita Aldous Elpizochari Alfarisi, Raihan Alfian Reza Pahlevi Alip Setiawan Allifira Andara Hasna Alvian Akmal Nabhan Amaliah Gusfadilah Andhi Surya Wicaksana Andro Subagio Angga Wahyudi Kurniawan Pratama Anggi Novita Sari Anne Diane Rachmadani Arif Indra Kurnia Arina Rufaida Aristides, Joy Vianoktya Arjun Nurdiansyah Arsan, Danish Alif Arsti Syadzwina Fauziah Audia Refanda Permatasari Ayezha Halidar Putri Irwanda Ayuda Dhira Pramadhari Bachtiar, Harsya Bafagih, Novel Bagas Laksono Bastian Dolly Sapuhtra Basuki, Akbar Lucky Bisma Anassuka Brillian Aristyo Rahadian Buce Trias Hanggara Budi Darma Setiawan Cahyo Gusti Indrayanto Candra Dewi Candra Dewi Chandra, Ardhya Khrisna Christina Sri Ratnaningsih Cindy Cynthia Nurkholis Dahnial Syauqy Daniel Agara Siregar Dany Primanita Kartika Sari Dany Primanita Kartikasari Davia Werdiastu Dedy Surya Pradana Dese Narfa Firmansyah Devi Nazhifa Nur Husnina Dhaifa Farah Zhafira Dhimas Wida Syahputra Dhiva Mustikananda Diamanta, Ananda Dian Eka Ratnawati Dian Ratnawati Dian Sisinggih Dimas Adi Syahbani Achmad Putra Djoko Pramono Djoko Pramono Dloifur Rohman Alghifari Dwi H Sulistyarini Dwija Wisnu Brata Dwija Wisnu Brata Dwija Wisnu Brata Dzulkarnain, Tsania Dzulkarnain, Tsania - Edgar Maulana Thoriq Edy Santoso Eko Wahyu Hidayat Ellita Nuryandhani Ananti Ema Rosalina Eni Hartika Harahap Fadilah Islamawan, Adam Faiz Abiyandani Faizatul Amalia Fajar Pangestu Faradila Puspa Wardani Faris Febrianto Farizky Novanda Pramuditya Fauzia, Sri Febrina Sarito Sinaga Ferina Kusuma Anjani Ferry Jiwandhono Fitria Yesisca Gagas Budi Waluyo Gani Kharisma Wardana Gilang Pratama Gusti Reza Maulana Haidar Azmi Rabbani Hanggara , Buce Trias Hardyan Zalfi Harris Imam Fathoni Haryuni Siahaan Hayunanda, alanela ganagisarama Heryadi Mochamad Ramdani Hidayati, Chofifa Hilmy Ramadhan, Achmad Zhafran Huda Minhajur Rosyidin Husalie, Levin Vinnu Imam Cholisoddin Imam Cholissodin Imam Cholissodin Immanuel Tri Putra Sihaloho Indriati Indriati Indriati Indriati Indriati, Indriati - Intan Sartika Eris Maghfiroh Irany Windhyastiti Irwan Shofwan Issa Arwani Issa Arwani Ivan Agustinus Jasico Da Comoro Aruan Jefri Hendra Prasetyo Jonemaro, Eriq Muhammad Adams Jumerlyanti Mase K., Anggraeni Dwi Kautsar, Ahmad Izzan Kevin Nastatur Chatriavandi Khairul Rizal Krishna Febianda Ksatria, Willyan Eka Kurnianingtyas, Diva Laila Diana Khulyati Lailil Muflikhah Liwenki Jus'ma Olivia M. Ali Fauzi M. Ali Fauzi M. Attala Reza Syahputra Made Tri Ganesha Madjid, Marchenda Fayza Marji Marji Marpaung, Veronika Oktafia Marwa Mudrikatussalamah Maulana Syahril Ramadhan Hardiono Maulana, M. Ighfar Maulidhia, Abrilian Meriza Nadhira Atika Surya Michael Eggi Bastian Mochammad Ilman Asnada Mohammad Aditya Noviansyah Mohammad Setya Adi Fauzi Mohammad Zahrul Muttaqin Muh. Arif Rahman Muhammad Ferian Rizky Akbari Muhammad Hidayat Muhammad Ikhsan Nur Muhammad Jibril Alqarni Muhammad Kevin Sandryan Muhammad Nadzir Muhammad Nurhuda Rusardi Muhammad Razan Nadhif Muhammad Reza Utama Pulungan Muhammad Shidqi Fadlilah Muhammad Syahputra Muhammad Tanzil Furqon Mukhtar Darma Hidayat, Alif Ahmad Muthia Maharani Muzayyani, Muhammad Farid Nadiah Nur Fadillah Ramadhani Najihah, Siti Waheeda Nanang Yudi Setiawan Nanang Yudi Setiawan Nanda Alifiya Santoso Putri Nashihul Ibad Al Amin Niken Hendrakusuma Wardani, Niken Hendrakusuma Nilna Fadhila Ganies Novanto Yudistira Nur M. F. Dinia Nurfadhilah, Rakhmad Giffari Nuril Haq, Muhammad Nurizal Dwi Priandani Nurul Hidayat Nurul Ihsani Fadilah Obed Manuel Silalahi Panjaitan, RE. Miracle Pascad Wijanata, Ida Bagus Prakosa, Wira Zeta Pramudita, Julina Larasati Primayuda, Averil Priscillia Vinda Gunawan Purnomo, Welly Putra Pandu Adikara Putranto, Rezky Donny Putri Ratna Sari Putri, Firda Qhafari, Abi Al Qoid A Fadhlurrahman Rafli, Mohammad Ali Rahinda, Muhammad Abiyyi Ramadhani, T. Zalfa Randy Cahya Wihandika Rani Metivianis Rasif Nidaan Khofia Ahmadah RE. Miracle Panjaitan Reinaldi Guista Pradana Ismail Reiza Adi Cahya Renaldi Muhammad Revan Yosua Cornelius Sianturi Reyhan Dzickrillah Laksmana Reza Aprilliana Fauzi Rheza Raditya Andrianto Rifwan Hamidi Riswan Septriayadi Sianturi Riza Rizqiana Perdana Putri Rizky Ardiawan Rizky Nuansa Nanda Permana Rohimatus Sholihah Roisul Setiawan Roma Akbar Iswara Rudianto Raharjo Safa S Istafada Saifurrijaal, Muchammad Salsabila, Dhea Rani Sandi Dewo Rahmadianto Satrio Agung Wicaksono Sekeon, Yerobal Gustaf Setiana, Maya Setiawan, Roisul Shafira Eka Aulia Putri Slamet Thohari Sofi Hidyah Anggraini Sugeng Santoso Sugiarto S Sugiono Sugiono Sukmawati, Annisa Sultan Saladdin Sultan, Muhammad Attharsyah Firdaus Supraptoa Supraptoa Tanica Rakasiwi Tasya Agiyola Teri Kincowati Tri Astoto Kurniawan Trias Hanggara, Buce Trio Pamujo Wicaksono Ulva Febriana Umar Basher, Nizar Umu Khouroh Vivilia Putri Agustin Wahyu Bimantara Wayan Firdaus Mahmudy Welly Purnomo Welly Purnomo Weni Agustina Wenny Ramadha Putri Wibowo, Dhimas Bagus Bimasena Wicaksono, Satrio A. Widhy Hayuhardhika Nugraha Putra Widhy Hayuhardika Nugraha Putra Widodo, Ibnu Sam Widyadhana, Fawwaz Kumudani Wiku Galindra Wardhana Wisnu Brata, Dwija Yahya, Faiz Yesaya Sergio Vito Putranta Yudi Setiawan, Nanang Yuita Arum Sari Yusuf Afandi Zhafira, Dhaifa Farah