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Sistem Diagnosis Penyakit Kelamin Pada Pria Menggunakan Metode Forward Chaining Dan Dempster-Shafer Kukuh Bhaskara; Nurul Hidayat; Lailil Muflikhah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

According to the World Health Organization (WHO), more than 1 million sexually transmitted infections (STIs) occur every day. In one year there were an estimated 357 million new cases of sexually transmitted infections (STIs) worldwide. Sexually transmitted infections are all infections both bacteria, viruses, and fungi that are transmitted from one individual to another through sexual activity or through genital organs. For example, a newborn baby can contract gonorrhea from his mother as a result of passing through the vagina infected with N. Gonorrhoeae. According to WHO, more than 30 types of bacteria, viruses and parasites have been identified that can cause sexually transmitted diseases. 8 of these 30 species are known to have the greatest risk of causing sexually transmitted diseases. The purpose of this study was to implement the Forward Chaining and Dempster-Shafer method and testing the accuracy of the Forward Chaining and Dempster-Shafer method in identifying venereal disease in men. The results of the study shows that the accuracy of the expert system based on 35 data tested is 94.2% indicating that this expert system can function properly, namely the diagnosis of the system in accordance with expert diagnosis.
Penentuan Varietas Padi Unggul yang Akan Ditanam Berdasarkan Potensi Hasil Menggunakan Metode Analytic Hierarchy Process-Weighted Product (AHP-WP) Tunggul Prastyo Sriatmoko; Nurul Hidayat; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The increasing population in Indonesia every year, which results in increased demand for food in Indonesia. While the increase in production of the country's agricultural production is still lacking, resulting in the government doing imports to meet food needs. Therefore, an effort is needed to improve better production, especially in rice, which is the staple food of the Indonesian population, one way to increase production is by planting seeds of superior varieties of rice. However, many criteria need to be considered in choosing which rice varieties are suitable to choose from in making choices. From these problems, there are several methods that can be implemented in solving problems with a system that is able to provide advice on the type of rice planted using the Analytic Hierarchy Process (AHP) method to give weights and the Weighted Product (WP) method is used to calculate alternative ranks and take values the highest as a final recommendation. In the testing phase with an accuracy method comparing the results of recommendations from the system compared to recommendations from experts, the resulting accuracy rate is 90.19607843%, so that it can be concluded that the AHP and WP methods can be used in recommending superior types of rice because they have high accuracy values above 90% nearing perfect from expert data.
Diagnosis Penyakit Tanaman Cabai Menggunakan Metode Modified K-Nearest Neighbor (MKNN) (Studi Kasus: BPTP Karang Ploso Malang) Hadi Dwi Abdullah Hamid; Nurul Hidayat; Ratih Kartika Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Red chili is one of the most important vegetables in Indonesia, whether it is as a commodity that is consumed domestically and as an export commodity. As vegetables, beside red chili has a high nutritional value, it also has a high economic value. However, the productivity of national red chilli is still very low at 7.34 tons / ha, whereas the actual yield can potentially reach 12 tons / ha. In a planting period, chili can be harvested several times. If the season and the treatment is very good, chili can be harvested 15-17 times but generally, it can be harvested only 10-12 times. The low productivity of chili can be caused by a variety of factors, including poor quality of chili seeds, decreasing soil fertility, bad implementation of cultivation techniques, plant pest and disease problems. In order to handle this, technology is needed by applying one of the classification methods, namely Modified K-Nearest Neighbor (MKNN). Modified K-Nearest Neighbor (MKNN) is the development of the KNN method that has been designed to overcome the weaknesses of the distance between data and weight in the KNN. The method analysis is based on 18 symptoms of the disease with the process of calculating euclidean distance, calculating the validity and calculation of wighted voting which result in the determination of the classification class based on the specified K value. The test results showed that when using the value K = 5 produces an accuracy of 94%, then K = 8 produces an accuracy of 92%, K = 11 produces an accuracy of 88% and testing K = 14 produces an accuracy of 88%. Based on the results obtained, the Modified K-Nearest Neighbor (MKNN) method showed good accuracy for classifying chili disease.
Optimasi Pemetaan Tugas Mengajar Dosen Menggunakan Memetic Algorithm Okvio Akbar Karuniawan; Nurul Hidayat; Marji Marji
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Submission of information relating to teaching and learning activities is very important, one of the first things to consider is scheduling. At Faculty of Computer Science (FILKOM) Brawijaya University, the assignment process is still manually designed where it requires some substantial time, therefore it needed a right optimization methods in dealing with this case. This assignment problem can be solved by a population-based heuristic methods, Memetic Algorithm (MA) which has been applied in various fields such as scheduling and assignments. The data used in this study is the data division of lecturers teaching tasks as a priority of lecturer's teaching interests to a course. From the obtained data, it determined constraints such a lecturer's teaching priority, the maximum and minimum amount of credits, and the number of course that can be taken to calculate fitness value for each particles. Through the obtained results, it had parameter tested to find the effect of tested parameters on the resulted fitness values. From MA parameters test results, it obtained the best population number as 100, best iteration number as 100, and combination of parameter cr and mr as 0,8 and 0.2 with resulted fitness value as 87830. From the results of system, The fitness value of the test is optimal solution of generation 100 because the stop conditioning memetic algorithm is a maximum iteration. But the results do not guarantee if the value of Cr is getting smaller and the greater the value of Mr will produce better fitness.
Rekomendasi Prioritas Perbaikan Jalan Dengan Metode AHP-SAW-TOPSIS (Studi Kasus: Dinas Pekerjaan Umum dan Penataan Ruang Kota Malang) Ayudiya Pramisti Regitha; Nurul Hidayat; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

One of the most important public facilities is roadway as it helps in distributing and delivering various human needs. There are 3776 roadways in Malang, and the total accumulation of its length is 1.221.193 kilometers. Based on the data in 2017, 15% of are damaged. However, the allocation of APBN is very limited, about 3-4%, causing limitation in repairing those damaged roads in the time span of one year. Moreover, that allocation is not enough and so it creates difficulties for the staff of PU Bina Marga to decide the priorities in repairing the damaged roadways as all of them need to be fixed. The solution offered for this problem by creating a program/system that can analyze and make a quick decision about the list of priority in repairing damaged roads which called Sistem Rekomendasi Prioritas Perbaikan Jalan. Criterias used in the decision making of this program are the length of the road, the width of the road, the condition, the acces to certain road, the classification of the road based on its function and the route of public transportation. This system uses MADM Method which consists of AHP, SAW and TOPSIS Method. This research testing has resulted 57,14% .
Rekomendasi Perbaikan Rumah Tidak Layak Huni Menggunakan Metode TOPSIS Studi Kasus Badan Keswadayaan Masyarakat Di Kelurahan Bekasi Jaya Muhammad Fakhri Mubarak; Nurul Hidayat; Marji Marji
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 4 (2019): April 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Houses that are habitable, clean and have good infrastructure are the hopes of every human being. Conversely, non-habitable homes can cause discomfort for residents, and can also be a source of disease that should be avoided by residents. To avoid this, residents of the house must spend not a little money to improve the infrastructure for their place of residence. The problem is that there are still families who do not have excessive financial resources to repair their homes, which makes them have to survive in places that are not suitable for habitation. To overcome this, the governments of each region prepared a variety of programs to help disadvantaged communities, one of which was responsible to the Badan Keswadayaan Masyarakat. Unfortunately, these funds cannot be given to all applicants for repairing unfit for housing. Due to the imbalance in the number of applicants for repairs to improper housing, with funds owned by the Community Self-Help Agency. So the Badan Keswadayaan Masyarakat needs a system that is used to help provide recommendations for homes that are preferred to be repaired. The application of the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method will be used to get home improvement recommendations that will be repaired. This system uses data as much as 50 data which form the basis of calculations and 8 home recommendation data which become test data. The application of the TOPSIS method in determining recommendations for repairing uninhabitable homes uses several factors, namely: the status of the house, the walls of the house, the floor of the house, the roof of the house and family income. From this study, it was obtained an accuracy of 75% obtained from testing of decision-making data in the Community Empowerment Agency and ranking using the TOPSIS method.
Sistem Diagnosis Penyakit Mata Menggunakan Metode Fuzzy Tsukamoto Galih Putra Suwandi; Nurul Hidayat; Suprapto Suprapto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 4 (2019): April 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Eye is one of the five most important senses which include hearing, smell, taste, and touch. In the eye itself, there are various kinds of diseases. According to the Basic Health Research (Riskendas) on 2013, they collected the data of blindness with the respondents analyzed totaling 224,714,112 people, and experiencing blindness 966,329 people. Blindness is one of several eye diseases such as conjunctivitis, anterior uveitis, cataracts and others. Due to many types of eye diseases, a system is needed to take and apply knowledge from experts. It is Fuzzy Tsukamoto method. This method is chosen because it has more advantages, that have data tolerance and are very flexible, and are intuitive and can provide qualitative. The results of the implementation and testing found 85% accuracy in conjunctivitis, 85% for uveitis anterior, 90% for cataracts and 86.67% for the average accuracy of the three diseases.
Sistem Diagnosis Penyakit Tanaman Mangga Menggunakan Metode Bayesian Network Asep Ardi Herdiyanto; Nurul Hidayat; Ratih Kartika Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 4 (2019): April 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Diagnosis system app for mango disease is an application that aims the farmers community, especially for the mango farmers so that symptoms can be handled early. This system is built based on the problems that occur in the community, namely the difficulty in recognizing pests and diseases of mango plants. Because mango pests and diseases have quite a number of symptoms and there are similarities in symptoms that some diseases have. This is one of the causes of reduced productivity levels of mango plants in Indonesia, recorded from the 2015 Central Bureau of Statistics research that the national harvest decreased by 252 thousand tons with the total number of 2,178 thousand tons in 2015. However, in 2014 there were 2,431 million tons. The Bayesian Network method was chosen in this study because Bayesian Network includes all features in the training data, thus making this method optimal in carrying out the calculation process. This system uses the Android operating system, because Android is quite even and popular in the Indonesian smartphone market until now. The data used in this study were obtained from lecturers at the Faculty of Agriculture, Brawijaya University, Malang. The results of this study indicate that, in testing the accuracy of 32 test data get an accuracy rate of 87.5%.
Sistem Pakar Diagnosis Penyakit Infeksi Saluran Pernapasan Akut (ISPA) Menggunakan Metode Fuzzy Tsukamoto William Muris Parsaoran Nainggolan; Edy Santoso; Nurul Hidayat
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 4 (2019): April 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Acute Respiratory Infection (ARI) is a major cause of morbidity (number of diseases) from various infectious diseases in the world. Bacteria, mycoplasma virus, fungi are a small part of various causes of ARI disease. Based on the severity, ARI disease can also be divided into 2, namely mild ARI and severe ARI. The low level of public information about knowledge about diseases, especially ARI, is an important factor why the mortality rate due to ARI is very high. In addition, sufficient numbers of medical personnel are needed to help communities in certain areas of Indonesia to be able to cope with ARI disease and get to know more widely ARI disease. Therefore, expert systems are expected to be a solution or rapid treatment and in helping diagnose ARI. This study also uses the Tsukamoto fuzzy method in the process of calculation and implementation. The application of fuzzy tsukamoto method of diagnosis of ARI disease, applying input from symptoms of ARI that appear as a reference for the diagnosis of disease. In the system, experts provide 5 symptoms and 2 types of ARI disease. Accuracy testing is done by testing the accuracy of 60 training data obtained from experts and there are 53 of the 60 data that match the results released by the system with expert results. The accuracy value obtained is 88.33%.
Implementasi Metode Bayesian Network untuk Diagnosis Penyakit Telinga Hidung dan Tenggorokan (THT) Mustofa Robbani; Nurul Hidayat; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 4 (2019): April 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Ear nose and throat disease one of the harmful disease, lack of hygiene and the difficulty in keeping the communities to diagnose due to the similarity of symptoms and diseases of the ear nose and throat, in addition to the conditions in the village It is located far from hospitals - major hospitals lead to sluggish handling of the ear nose and throat. Allow the occurrence of the disease is worse so detrimental to society or to patients themselves. Then it takes a software which can help the community or patient so expect that software can help communities to diagnose diseases of the ear nose and throat. Then the software was made using Bayesian Network methods, and to facilitate operation then made software with Android-based operating system. This software has the input based on the symptoms - symptoms of the disease that is selected by the user and is processed by methods of Bayesian Network so as to generate output in the form of disease and suffered from the results of testing the accuracy of data 42 It brings the accuracy of 93.75%.
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