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Nurul Hidayat
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Klasifikasi Pendonor Darah Menggunakan Metode Support Vector Machine (SVM) Pada Dataset RFMTC Erwin Bagus Nugroho; Muhammad Tanzil Furqon; Nurul Hidayat
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

Blood donation is a process of taking blood from a person voluntarily to blood transfusions for patients in need. Blood from donors can't be used after 42 days. The only way to meet the demand for blood bags are having regular blood donations from a healthy donor. In Indonesia 2013, there is 2,476,389cc shortage of blood bags, where the ideal blood availability is 2.5% of the population. These problems required a system that can predict the behavior of donors in order to anticipate the shortage of blood bags. Regency, Frequency, Monetary, Time, Churn Probability (RFMTC) is a modification of the RFM method modified that used to predict the blood donor behavior to donate or not to donate bloods. The method for classifying the behavior of donors in this research are Support Vector Machine (SVM) method. Data that was used in this research is 748 which is divided into training data and test data. The accuracy result got best accuracy based on 50%: 50% data ratio, using linear kernel and parameter value λ (lambda) = 2, Gamma (γ), = 0.5, Epsilon (ε) = 0.005, and C (complexity) = 20. The result of SVM method accuracy on blood donor classification is 72.64%.
Sistem Pendukung Keputusan Penentuan Penerima Bantuan Keluarga Miskin Menggunakan Metode Analytical Hierarchy Process - Technique For Order Of Preference By Similarity To Ideal Solution(AHP-TOPSIS) Akbar Aditya Maulana; Nurul Hidayat; Suprapto Suprapto
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

Economic growth is one of the major factors in which a contry can be said to be growing. Various ways undertook by the the Indonesian government to improve economic growth in indonesia, on of which is to suppress poverty in the territory of indonesia. Indonesia region that has a considerable povery level in East Java province, district of Situbondo regency Distric Mlandingan. Many ways are done by the government Situbondo to cope with poverty, especially by providing funds intended for the poor. However, the provison of funds is less appropriate target because there are still critizens who are categorized as capable, who are considered capable should not deserve help. For that need a decision suport system, to assist the Situbondo government to provide recommendations for candidates for help. By using AHP-TOPSIS method that will be applieds to an androids based application with 6 criterian that serve as a reference to get accuracy. Then by the TOPSIS method used to search from the preference for rank. In this research, a test is done to know the value of accuracy in TOPSIS method, and the result of accuracy with a value raching 80% by using TOPSIS method.
Sistem Pakar Diagnosis Penyakit Tanaman Cengkeh Menggunakan Metode Naive Bayes (Studi kasus Kecamatan Wonosalam, Jombang) Andrianto Setiawan; Nurul Hidayat; Ratih Kartika Dewi
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

Clove plants are classified into plantation crops or industries that are widely grown in Wonosalam. But not all clove plantations belong to the local people, but the owners are residents from outside the region. This causes the plant is less well groomed cloves and eventually attacked by disease. One method to diagnose clove plant disease can be done with Naive Bayes. Clove plant disease diagnosis expert system using Naive Bayes method can make it easier to detect diseases that attack the cloves based on the symptoms that arise. The Naive Bayes method is implemented on an expert system inference engine in order to make inferences based on existing knowledge on the knowledge base. Results obtained after a system accuracy test of 93% indicating that the method of Naive Bayes is suitable for clove plant disease cases.
Penentuan Kelayakan Kandang Sapi Menggunakan Analytic Hierarcy Process-Weighted (AHP-WP) [Studi Kasus UPT Pembibitan Ternak Dan Hijauan Makanan Ternak Singosari] Firnanda Al Islama Achyunda Putra; Nurul Hidayat; Tri Afirianto
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

The cow shed is a place to live a day cow. The better quality and materials of the cow cow will certainly make the cow better for its development. Therefore, it is important that a decent cow shed plays an important role also on cow health. Today many people do not meet the correct criteria for cow breeding. As a result many cows that died suddenly due to less healthy cages. Therefore, the authors chose this topic because according to the interviews UPTD that this application will help local farmers, especially malangraya region and generally to the community at large. AHP or also called Analytic Hierarcy Process is a decision support model developed by Thomas L. Saaty. This decision support model will describe complex multi-factor or multi-criteria problems into a hierarchy. Variables needed in this study are the criteria for the determinants of the feasibility of the cage as many as 5 criteria. WP or also called Weighted Product acts as a ranking against the weighting that has been done by AHP. So get the results of farmers breeding rank from the lowest to highest rank. This study resulted in an accuracy of 77.3%.
Sistem Diagnosis Penyakit Hewan Pada Anjing Dengan Menggunakan Metode Naive Bayes Alfian Himawan; Nurul Hidayat; Mahardeka Tri Ananta
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

Human pets, dog is a social creature that can interact with each other or humans so that not a few people prefer dogs as pets. However, dogs can also have an infectious disease that can be bad for humans, the presence of an expert would be helpful in terms of solving the diseases that attack dogs by means of identifying the symptoms that plagued and conclude what disease. Naive Bayes method is a method used to predict probabilities. While Bayes classification is the classification of statistics that can predict the probability of a class member. For a more simple Bayes classification known as naive Bayesian Classifier can be assumed that the effect of an attribute value is a class given is free of other attributes. The required variable in this study is clinical symptoms in dogs. The results of this research testing showed the accuracy of the system are 90%.
Identifikasi Penyakit Pada Kambing Menggunakan Metode Fuzzy K-Nearest Neighbor (F-KNN) Basuki Rahmat Rialdi; Nurul Hidayat; Suprapto Suprapto
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

Goat (Capra Aegragus Hircus) is one of the animals raised by humans. However, goat cattle business will experience constraints when the goats are infected with the disease. In addition to causing harm, the disease can also reduce public interest to goat breeding. So the system was made to identify the disease in goat farms, so the breeder could know the type of disease that attacked and handled it appropriately. The method used is k-nearest neighbor and fuzzy. The first step of this method includes trainer data that contains symptoms of the disease. Then the classification uses k-nearest neighbor. After the implementation and testing, obtained the highest accuracy of 96% at K which is worth 9. From these results can be concluded that the results of the system and experts are aligned and have positive accuracy
Sistem Pakar Deteksi Dini Penyakit Stroke Menggunakan Metode Naive Bayes-Certainty Factor Renaldy Senna Hutama; Nurul Hidayat; Edy Santoso
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

Stroke became one of the diseases that have a high mortality rate in Indonesia and also in the world. It can be dangerous if it is not handled quickly because of a sudden disruption of blood that supplies the brain and if not handled quickly can cause permanent disability or death. In Indonesia, stroke disease in recent years has increased, but the government still has no solution in solving the disease problem. Though the process of handling stroke disease takes sufficient time in detection, if not handled quickly can lead to disability or even death. With the existence of these problems then required a system that can accelerate and simplify the detection of risk to reduce the number of people suffering from stroke. The method used in the detection process is Naive Bayes-Certainty Factor. The Naive Bayes method is used to look for an opportunity to appear from the risk of stroke. For certainty factor method is used to find the value of his belief. This system is built with android based with Java programming language. For the test is done by doing a comparison of detection results from experts with the results of detection conducted by the system where from 25 test data obtained obtained accuracy of 84%.
Implementasi Algoritme Modified K-Nearest Neighbor (MK-NN) Untuk Diagnosis Penyakit Anjing Luh Putu Novita Budiarti; Nurul Hidayat; Tri Afirianto
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

Dog is one of the most favorite pets. Interacting with dogs has its benefit such as lowering stress levels and leading the owners to have a more active lifestyle. However, the dog's health itself should be taken care of. Dog who suffers from a disease can infect other pets or even humans, so veterinarian help is needed. Things will be difficult if the owners realize that their dogs are sick outside of working hours because there is not much veterinary clinic that open for 24 hours. So the owners should be capable of giving immediate response to their dogs. Therefore, a system is needed to help this problem using Modified K-Nearest Neighbor (MK-NN) algorithm, to help the owner getting their dog diagnosed and giving immediate response. The system is implemented using Java programming language. There are 10 types of the diseases with 46 clinical symptoms. Based on the accuracy test, the maximum average of accuracy obtained is 96.6% with k=2.
Implementasi Metode Dempster-Shafer Untuk Mendeteksi Penyakit Pada Anjing Muhammad Zainuri Aziz; Nurul Hidayat; Satrio Hadi Wijoyo
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

Dogs are one of the most popular pets in the world. Dogs are easily attacked by disease. When the dogs are attacked by disease it will certainly cause certain symptoms. People who keep dogs mostly do not know the various diseases experienced by the dog. Implementation that can know the various diseases of dogs from the data of the symptoms experienced by the dog can be done, so that dog owners and veterinarians can be more easily to know the illness they suffered. In this application applied Dempster-Shafer method because this method was known from one of the same symptoms can be known more than one disease that exists. With this method also can overcome the problems. The accuracy of this system is 85.53% which means the system can run well because the result of the system closely matches the actual field facts.
Diagnosis Penyakit Kambing Menggunakan Metode Dempster-Shafer Fibriliandani Nur Pratama; Nurul Hidayat; Suprapto Suprapto
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

In meeting the needs of meat and milk in the country, developing goat Ranch has a good prospect because it also has opportunities as export commodities. However there are several factors which impede the goat breeders to find out what diseases are attacking their goat, i.e. the limitation of the time owned breeder, very expensive and the latter is at least a vet in remote areas. Information received from a veterinarian only in accordance with the conditions of the goats at the time. If there are other symptoms the next day then we must go back to the vet for consultation again. The theory of the Dempster-Shaffer is one method that is able to accommodate the uncertainty in the classification of multispectral. This theory is used to combine separate pieces of information to calculation the chances of an event. The required variable in this study is clinical symptoms on goats. The test results of this research show the system accuracy of 89%.
Co-Authors Achmad Affan Suprayogi Nugraha Achmad Dwi Noviyanto Achmad Igaz Falatehan Achmad Ridok Achmad Syarifudin Ade Wicaksono Adhie Indi Arsyanto Adhitya Pratama Wijayakusuma Adhiyatma Mugiprakoso Aditya Purwa Pangestu Agus Wahyu Widodo Ahmad Afif Supianto Ahmad Fuyudi Wijaya Akbar Aditya Maulana Akhmad Syururi Akhmad Wahyu Redhani Aldion Cahya Imanda Alfan Nazala Putra Alfian Himawan Alfita Nuriza Ali Syahrawardi Andi Amaliyah Maryama Andika Eka Putra Andrianto Setiawan Arief Andy Soebroto Arifandi Wahyu Widianto Arik Khusnul Khotimah Asep Ardi Herdiyanto Askia Sani Atha Milzam Ayudiya Pramisti Regitha Bambang Gunadi Barlian Henryranu Prasetio Basuki Rahmat Rialdi Bayu Febrian Putera Ammal Bayu Kusuma Pradana Bayu Rahayudi Benedict Abednego Hasibuan Bhima Arya Tristya Haryu Niswara Bryan Pratama Jocom Budi Darma Setiawan Caesaredi Rama Raharya Chandra Tio Pasaribu Christian Herlando Indra Jaya Dayu Aprellia Dwi Putri Denis Ahmad Ryfai Desy Setya Rositasari Dhatu Kertayuga Dhimas Tungga Satya Dicky Manda Putra Sidharta Didin Wahyu Utomo Dito Rizki Pramudeka Dizka Maryam Febri Shanti Dona Adittia Donald Sihombing Donald Sihombing Dwi Prasetyo Edi Siswanto Edy Santoso Eka Hery Wijaya Elan Putra Madani Elna Diaz Pradini Eric Aji Panji Kurniawan Erwan Wahyu Andrianto Erwin Bagus Nugroho Fahmiyanto Ekajaya Fakihatin Wafiyah Faris Abdi El Hakim Fariz Andri Bakhtiar Fibriliandani Nur Pratama Fikar Cevi Anggian Firmansyah Arif Maulana Fitra Abdurrachman Bachtiar Galih Putra Suwandi Ganda Adi Khotarto Greviko Bayu Kristi Gustian Ri'pi Hadi Dwi Abdullah Hamid Haryuni Siahaan Healtho Brilian Argario Hema Prasetya Antar Nusa Herlina Devi Sirait Heru Nurwarsito Hilal Imtiyaz I Gede Adi Brahman Nugraha Icha Gusti Vidiastanta Ichwanda Hamdhani Idham Triatmaja Ikhlasul Amal Faj'r Imam Cholissodin Indriati Indriati Irfan Aprison Irvan Windy Prastyo Isnaini Isnaini Januar Dwi Amanda Jiwandani Andromeda Kholif Beryl Gibran Komang Candra Brata Krisna Andryan Syahputra Effendi Krisna Wahyu Aji Kusuma Kukuh Bhaskara Kusuma Ari Prabowo Lailil Muflikhah Lisa Septian Putri Luh Putu Novita Budiarti Luqman Hakim Harum Lutfi Fanani M. Ali Fauzi Mahardeka Tri Ananta Mahdi Fiqia Hafis Marji Marji Maskiswo Addi Puspito Maulana Aditya Rahman Meriza Nadhira Atika Surya Meutya Choirunnisa Moch Cholil Mahfud Moch. Cholil Mahfud Moch. Cholil Mahfud Mochammad Faizal Satria Rahman Mochammad Taufiqi Effendi Mohamad Yusuf Arrahman Muhamad Altof Muhamad Rendra Husein Roisdiansyah Muhammad Anang Mufid Muhammad Arif Hermawan Muhammad Atabik Usman Muhammad Burhannudin Muhammad Denny Chrisna Pujangga Muhammad Fakhri Mubarak Muhammad Hasbi Wa Kafa Muhammad Kurniawan Khamdani Muhammad Regian Siregar Muhammad Resna Muhammad Rouzikin Annur Muhammad Tanzil Furqon Muhammad Vidi Mycharoka Muhammad Zainuri Aziz Mustofa Robbani Niftah Fatiha Armin Ninda Silvia Tri Cahyani Novianto Donna Prayoga Nurudin Santoso Oktavianis Kartikasari Okvio Akbar Karuniawan Priscillia Pravina Putri Sugihartono Putra Pandu Adikara Putra, Firnanda Al Islama Achyunda Putut Abrianto Rachmad Faqih Santoso Rahmat Arbi Wicaksono Ramadhan Anindya Guna Aniwara Randy Cahya Wihandika Ratih Kartika Dewi Raymond Gunito Farandy Junior Rekyan Regarsari Mardhi Putri Renaldy Senna Hutama Reynaldi Firman Tersianto Reyvaldo Aditya Pradana Reza Andria Siregar Reza Rahardian Rhayhana Putri Justitia Rhiezky Arniansya Rhyzoma Grannata Rafsanjani Ricky Marten Sahalatua Tumangger Rihandiko Hari Romadhona Rio Arifando Risda Nur Ainum Risqi Auliatin Nisyah Risqi Nur Ifansyah Rizal Setya Perdana Rizaldy Amsyar Rizki Wulyono Propana Sodiq Robertus Santoso Aji Putro Salam Maulana Sandy Ikhsan Armita Satrio Hadi Wijoyo Siti Febrianti Ramadhani Supraptoa Supraptoa Sutrisno Sutrisno Syafruddin Agustian Putra Syailendra Orthega Syndu Pramanda Galuh Widestra Tibyani Tibyani Tri Afirianto Trio Pamujo Wicaksono Tunggul Prastyo Sriatmoko Vicky Robi Wirayudha Wahyu Dwiky Rahmadan Wildan Gita Akbari Wildansyah Maulana Rahmat William Muris Parsaoran Nainggolan Yamlikho Karma Yayuk Wiwin Nur Fitriya Yori Tri Cuswantoro Yudo Juni Hardiko Yusril Iszha Eginata Yusuf Ferdiansyah Yusuf Nurcahyo Zaiful Bahar