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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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Diagnosis Penyakit Hati Menggunakan Metode Naive Bayes Dan Certainty Factor Rhyzoma Grannata Rafsanjani; Nurul Hidayat; Ratih Kartika Dewi
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

Liver disease or liver disease is a disease caused by various factors that damage the liver, such as viruses and alcohol use. Obesity is also associated with liver damage. Over time, liver damage can cause serious effects, the presence of experts will be very helpful in dealing with liver disease problems by identifying the symptoms experienced and infer what type of liver disease is attacking and provide information to deal with the problem. The Naive Bayes method is a method used to predict probabilities. While Certainty Factor is a method that can help experts who diagnose something uncertain. Variables needed in this study are symptoms of liver disease and liver disease type. Based on the results of testing and analysis of the results of this study, it can be taken some conclusions that Method Naive Bayes and certainty factor can be used for the diagnosis of liver disease. The Naive Bayes method and certainty factor resulted in an accuracy of 88%.
Implementasi Naive Bayes Dengan Certainty Factor Untuk Diagnosis Penyakit Anjing Desy Setya Rositasari; Nurul Hidayat; Fitra A. Bachtiar
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

The interest of Indonesians in having dog as pets is high. Dogs become favorite pets because dogs have funny and adorable habits. In addition, taking care of dogs is quite easy. Prevention and detection of diseases that infect dogs is necessary, so the infected dogs can be taken care of immediately to prevent transmission of the disease to other dogs and to human. Diagnosing the diseases could be a bit difficult sometimes because some diseases have similar symptoms. Another problem is that there are not many veterinary clinics that open for 24 hours so it would be difficult for dog owners if they found out that their dog was sick outside of the clinics' working hours. The system of dog diseases diagnosis is made to assist veterinarians in diagnosing dog diseases, in addition the system is expected to assist the community in making an initial diagnosis of their dogs. This system is Android-based and applies the method of Naive Bayes and Certainty Factor. The Naive Bayes method is used to classify dog diseases based on the usual pattern of symptoms, while the Certainty Factor method is used to determine the value of certainty of classification results from the Naive Bayes method. Based on the accuracy test that was done for five times, the average accuracy value obtained was 97.2%.
Sistem Diagnosis Penyakit Penglihatan Kabur Pada Mata Menggunakan Metode AHP-SAW Mochammad Faizal Satria Rahman; Nurul Hidayat; Ratih Kartika Dewi
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

Blurred vision sickness is an eye-attacking disease which has a high rate of cases in Indonesia. The disease is also difficult to detect visually. In many cases, this disease is detected when the symptom is already severe. Patients with this disease are usually not aware of blurred vision symptom. Therefore it needs expert diagnosis to understand this disease. On the other hand, limited number of eye experts in Indonesia is also problem which has to be addressed. Those problems can be solved by establishing an expert system of blurred vision diagnosis. Expert systems are part of artificial intelligence which contains expert knowledge and experience incorporated into a particular area of knowledge to solve specific problems. Method of Analytic Hierarchy Process-Simple Additive Weighting (AHP-SAW) is kind of method which applied to overcome the problem of identifying criterion with measuring data qualitatively and quantitatively. Based on the test data which used in this study, system succeed to diagnosis of blurred vision sickness with 87% of accuracy.
Identifikasi Hama Dan Penyakit Pada Tanaman Sedap Malam Menggunakan Metode K-Nearest Neighbor Ikhlasul Amal Faj'r; Nurul Hidayat; Donald Sihombing
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

Tuberose (Polianthes Tuberose) is one of the ornamental plants that comes from the family Agavaceae which has many benefits. But in the cultivation found several obstacles, including pests and diseases that are very influential on growth and flower production. To facilitate farmers to identify pests and diseases, then needed a system, one of the methods that can be used is k-nearest neighbor. After the implementation and testing, the results obtained with the highest accuracy of 94%. Thus, it can be concluded that k-nearest neighbor algorithm on pest and plant flower diseases identification system can be applied well so that it is very beneficial for tuberose flower farmers.
Sistem Diagnosis Penyakit Tanaman Melon Menggunakan Metode Dempster-Shafer Dwi Prasetyo; 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

Melon plant is a kind of plant that potentially attacked by plant disease. The lack of farmer knowledge in this field for controlling and maintaining the disease can affect the melon fruit productivity and contribute to plant damage. Therefore, the melon production would not achieve the expected target. In addition, another important problem is the higher number of symptom which resulted in difficulties to diagnose the melon plant disease. Basically, the farmer could discuss with the expert in plant pathologist field to control and try to solve this problem. However, this solution still has some limitation. It caused by restriction of the number of expert, long distance away, and it will take more longer time to analyze. The result show that, a system which was developed by using Dempster-Shafer method based on 24 data of melon plant symptom has reached success rate 87,5%. This value was obtained from 21 of 24 experiment data and it assumed as correct data. It was occurred because data that obtained was significantly different from the other data. It could be occurred because of the symptom density have similar weight in different types of disease.
Implementasi Metode Promethee untuk Diagnosis Penyakit Parasit pada Kambing (Studi Kasus : UPTD. Pembibitan Ternak dan Hijauan Makanan Ternak Kec. Singosari Malang) Ade Wicaksono; 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

The goat is farm animals which have many uses and benefits, besides as a producer of meat, other products can also be utilized in accordance commodities generated by goats. On the practice field for livestock farming goats have many experience problems, one of problem which arises is in term of the endurance of the goat against parasities. Based on case occurs, tha system is built on this reaserch is “Implementation promethee method to diagnose parasities disease on goats (case study: UPTD. Livestock breeding and forage feed of kec. Singosari Malang). The method use to range the disease diagnose on goats employs promethee method; it counts the variable based on Multi Criteria Decision Making (MCDM). The result of the rank is based on the selection of the system. Therefore, the present result shows the similarity with the labor results while the rest does not show the same pattern. The testing of the system uses disease data taken form 50 samples of goats whose rate is divided according to worm group; scabies and myasis. Based on the experiment, the accuracy of the final result is close to 85%.
Penentuan Penerimaan Beasiswa Menggunakan Metode Modified K-Nearest Neighbor Caesaredi Rama Raharya; 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

In determining the acceptance of students scholarship, the officers often face problem selecting student who are eligible for a scholarship that caused by several factors such as the number of students who apply for a scholarship while the quota for students who get scholarships is relatively small, the number of parameters used as a reference in determining the students who are eligible for a scholarship and the officers who are given only a relatively short time in determining the awardee. Therefore implement a classification system is required to this issue for help facilitate the scholarship selection officer. This research was using Modified K-Nearest Neighbor method. Modified Method K-Nearest Neighbor is modified method from K-Nearest Neighbor consists of the process of calculating distance euclidean, calculation of validity value and weight voting calculation. The highest average accuracy results obtained based on the tests and normalization data that have been done is 87.2%.
Implementasi Metode Extreme Learning Machine (ELM) untuk Memprediksikan Penjualan Roti (Studi Kasus : Harum Bakery) Luqman Hakim Harum; Nurul Hidayat; Ratih Kartika Dewi
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

Harum Bakery is a bread store located in Malang Regency area. The number of bread sales in this company is uncertain everyday. It makes the company difficult to predict the sale of breads per day. To avoid loss, this company need a system to predict sales prediction easily. With the prediction of the sale, the writer hope that the company can suppress the losses that may occur and optimizing company's profit. This research use Extreme Learning Machine (ELM) method which is method of Artificial Neural Network(ANN) to predict bread sales at Harum Bakery. The Process of prediction using ELM method is started from data normalization, then training process, testing process, find the error value using Mean Square Error (MSE) method to find the smallest error value with some testing, and data denormalization the ELM method is feedforward method with a single hidden layer which is called Single Hidden Layer Feedforward Neural Network (SLFNs). The main purpose of this method is to improve the weakness of other feedforward artificial neural networks, especially in the learning speed. Based on some tests that have been done, the smallest error rate is 0,01616 for white bread using 7 neurons, 4 features, and 5 months of sales data, the best MSE is 0,02839 for sweet bread using 2 neurons, 5 features, and 4 months of sales data, and 0,00812 for cake bread using 7 neurons, 4 features, and 3 months of sales data.
Diagnosis Penyakit Ikan Koi Menggunakan Metode Naive Bayes Classifier Yudo Juni Hardiko; Nurul Hidayat; Imam Cholissodin
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

Koi fish (Cyprinus carpio) is a type of freshwater ornamental fish that is widely cultivated because it has an attractive body shape and color. Koi morphology is almost similar to other fish species, koi body covered by two layers of skin, the outer skin (epidermis) and the skin (dermis). Epidermis is useful as a protective skin from the outside environment or as protection such as impact, dirt, and pest. Disease attacks and parasitic infections are a common problem faced by fish farmers. Diseases that often attack koi caused by pathogens in the form of bacteria, fungi, or viruses. The pathogens that live in the body of koi is very harmful because it will indirectly affect the color of koi fish. Koi fish diseases generally have some common symptoms that are almost the same as excessive mucus, punctured wounds or lumps on the body of fish and koi fish so menyediri. With so many diseases that have the same symptoms it makes fish farmers difficult to diagnose diseases in koi fish. Many methods can be used to create an system one of them is by using the method of Naive Bayes Classifier. In this system receive input in the form of data koi fish disease symptoms and the data is then processed using the method of Naive Bayes the results of system output in the form of diagnosis of diseases and treatment of disease outcomes that are diagnosed. Based on the accuracy testing of 20 data yields an accuracy of 90%.
Penerapan Metode Analitycal Hierarchy Process-Simple Additive Weighting (AHP-SAW) dalam Penentuan Varietas Padi yang Unggul Dona Adittia; Nurul Hidayat; Fitra Abdurrachman Bachtiar
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

Rice (Oryza sativa L.) is a very important food crop in the world after wheat and corn. During the development of agricultural research appeared several varieties of rice. Variety itself is one important component that has a major contribution in increasing production and income of rice farming. Therefore, it takes a computer system to help farmers decide the varieties that will be planted in accordance with the environmental conditions of planting by considering some aspects of the criteria. In the design using Analytic Hierarchy Process - Simple Additive Weighting in order to give consideration / advice to farmers to determine the superior varieties. The result of this method is the rank of the varieties. Method AHP function to determine the value of the vector of weight of some rise varieties that criteria then made reference in is the rank of the varieties produced by the process SAW. In this research, the test is done by measuring the accuracy level with the result reaching accuracy above 80%. So the system that is created by using the method AHP-SAW can be applied as a supporting decision making in determining superior rice varieties.
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