Article Per Year (5 Year)
p-Index From 2020 - 2025
4.747
P-Index
This Author published in this journals
All Journal Jurnal POINTER Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Nurul Hidayat
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

Published : 163 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 163 Documents
Search

 1   2   3   4   5 
Image Resizing Menggunakan Algoritma Seam Carving dengan Menggabungkan Dynamic Programming dan Stochastic Path Adhie Indi Arsyanto; Edy Santoso; Nurul Hidayat
Jurnal POINTER Vol 2, No 2 (2011): Jurnal Pointer - Ilmu Komputer
Publisher : Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

ABSTRAK Pada April 2007, Ariel Shamir dan Shai Avidan menemukan dan mempublikasikan algoritma seam carving. Kelebihan dari algoritma ini adalah pada saat ukuran sebuah citra diubah, dimana perubahan ukuran citra tersebut akan mengubah perbandingan panjang dan lebar. Seam carving dapat menjaga agar objek utama dalam citra tetap utuh, baik dengan atau tanpa bantuan user. Masalah yang timbul adalah operator pada makalah terdahulu menggunakan gradient magnitude dan histogram of oriented gradients dimana hanya 2 piksel yang paling berperan dalam menentukan sebuah tepi. Kedua operator ini sangat sensitif terhadap adanya gangguan pada citra (noise), karena hanya sedikit jumlah piksel yang dilibatkan untuk memperhitungkan gradien (Milan, 1993). Selain itu, menurut Hector Yee (2007) penggunaan algoritma dynamic programming seringkali menimbulkan artifact (pembentukan/perubahan objek). Penggunaan metode stochastic path dengan membuat 10.000 seam secara acak dinilai Hector Yee dapat memberikan hasil yang lebih baik (Hector. 2007). Namun, dengan metode tersebut ukuran citra akan mempengaruhi kualitas hasil resizing. Hal ini dikarenakan jumlah seam yang dibuat akan tetap meskipun ukuran citra bervariasi. Oleh karena itu dalam makalah ini akan dilakukan modifikasi dari algoritma seam carving dengan cara menggabungkan algoritma dynamic pr
Komputasi Frekuensi Kebersamaan Data Berdasarkan Klaster Pembentuknya Marji -; Edy Santoso; Nurul Hidayat
Jurnal POINTER Vol 2, No 2 (2011): Jurnal Pointer - Ilmu Komputer
Publisher : Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

ABSTRAK Salah satu cara untuk mengetahui kemiripan rekord data adalah dengan klastering. Pada metode klastering, dengan jumlah klaster yang sama, antara metode yang satu dengan yang lain kemungkinan menghasilkan struktur klaster yang berbeda. Dengan adanya perbedaan struktur tersebut dimungkinkan dua buah rekord data dengan suatu metode klaster berada dalam suatu klaster, tetapi dengan metode yang lain berada pada klaster yang berbeda. Pada penelitian ini dikembangkan suatu algoritma yang dapat digunakan untuk mengetahui frekuensi rekord data berada dalam satu klaster. Metode klaster yang digunakan adalah k-means, kohonen, fuzzy cmean dan fuzzy substractive. Berdasarkan hasil klastering keempat metode tersebut, dikembangkan algoritma yang dapat digunakan untuk mengetahui frekuensi rekord data bersamaan dalam satu kluster. Data yang digunakan adalah data gen jamur yang dapat didownload pada alamat http://cmgm.stanford.edu/pbrown/  sporulation/ additional/   Kata kunci: klastering, k-means, kohonen, fuzzy cmean, fuzzy substractive ABSTRACT Clustering is a one of  the way to know similarity  among data records.  Sometime, different methods give a different cluster structure , although in  the same sum  of cluster.  So that, by using different methods,  it is possible 2 data  at the different structure.  For exampale , by using kmean, data -1 and data-2 in the same cluster, but by  kohonen, data-1 and data-2 in the  different cluster. In this researh, we developt algorithm that can be used to calculate frequency of data record at the same cluster.  The methods, we are used are kmean, kohonen, fuzzy cmean and fuzzy substractive. Based on those methods, we developt  algorithm that can be used to know frequency of data record at the same cluster. Data used in this research is fungi gen, that can be download at http://cmgm.stanford.edu/pbrown/ sporulation/ additional/   Keywords: clustering, kmean,kohonen, fuzzy cmean, fuzzy substractive
Penerapan Algoritma Genetik Dua Populasi Pada Kasus Transportasi Dua Tahap (Pada Studi Kasus Distribusi Susu Fermentasi Pada Perusahaan XYZ di Pulau Jawa) Kusuma Ari Prabowo; Achmad Ridok; Nurul Hidayat
Jurnal POINTER Vol 2, No 2 (2011): Jurnal Pointer - Ilmu Komputer
Publisher : Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

ABSTRAK Algoritma genetik adalah suatu metode algoritma optimalisasi dan pencarian yang didasarkan pada prinsip genetika dan seleksi natural (Haupt. 2004). Pada penelitian ini, akan dibangun sebuah aplikasi optimasi pencarian rute pada transportasi dua tahap yang diterapkan pada studi kasus distribusi produk susu fermentasi pada perusahaan XYZ menggunakan algoritma genetik dua populasi. Algoritma genetik dua populasi, adalah suatu algoritma genetik yang membentuk dua populasi sebagai populasinya. Populasi tersebut dibagi dalam populasi elit dan umum, dimana individu yang terdapat pada populasi elit adalah suatu individu dengan nilai fitness tertinggi dan individu pada populasi umum dengan nilai fitness yang lebih rendah (Martikainen dan Ovaska, 2006). Seperti pada proses genetika, algoritma genetik memiliki operator genetik yang digunakan dalam proses regenetik.  Pada penelitian ini digunakan metode roulette wheel pada proses select parent nya, metode weight mapping cross over (WMX) untuk  proses cross over, dan swap mutation untuk proses mutasinya. Untuk mengukur sejauh mana pengaruh populasi elit terhadap fitness yang dihasilkan dilakukan uji perbandingan rata-rata hasil fitness pada 10 kali percobaan antara algoritma dua populasi dengan algoritma berpopulasi tunggal. Hasil ujicoba dan evaluasi menunjukkan bahwa metode algoritma genetik dengan dua populasi menghasilkan fitness 12 % lebih baik dari metode algoritma genetik berpopulasi tunggal.   ABSTRACT Genetic algorithm is an optimization method and search algorithms that are based on the principles of genetics and natural selection (Haupt. 2004). In this research we built a search optimization applications in the transportation routes applicable to the two-stage case study of the distribution of fermented milk products at XYZ company uses genetic algorithms two-populations. Two-population genetic algorithm, is a genetic algorithm that forms two populations as a population. The population is divided into elite and the general population, where individuals contained in the elite population is an individual with highest fitness value and individuals in the general population with lower fitness value (Martikainen and Ovaska, 2006). As in the genetic processes, genetic algorithms have the genetic operators used in the re-genetic  process. In this research, we use roulette wheel method for select parent process and weight mapping crossover (WMX) method for cross over process, then for mutation process we use swap mutation method. To measure the extent of the influence of the elite population of the fitness test yielded an average ratio of fitness results from 10 trials between two populations algorithm with single population algorithm. Testing and evaluation results show that the genetic algorithm method with two populations yield 12% better fitness than the single population genetic algorithm method.   Kata kunci : Algoritma genetic, genetic algorithm, dua populasi, two population, transportasi dua tahap, two step transportation.  
Sistem Optimasi Rute Tempat Wisata Kuliner Di Malang Menggunakan Algoritma Bee Colony Muhammad Arif Hermawan; Nurul Hidayat; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 3 (2017): Maret 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1200.115 KB)

Abstract

The number of culinary attractions in Malang that can be reached makes it difficult for culinary lovers to find the optimum route, in terms of distance, time, and cost to travel from one place to another. One of the factor that influence people's when they did culinary tour is the transportation fees. A thing that is very relate with transportation is the distance. Many culinary lovers feel like they have wasting their time to get to the place they want because they choose the wrong routes. Since Malang has so many culinary attractions, it takes optimization in searching the optimum route from starting point to the destination point. The bee colony algorithm was chosen because the algorithm is considered to have the ability to exit local minimum and can be efficiently used for optimization. Bee colony algorithm also can solve the problem of Traveling Salesman Problem better than other algorithm which is also based on group intelligence. At the experiment we can conclude that bee colony algorithm has converged in the search for the best solution that can be seen from the fitness resulted. One of the best have been convergence in bee colony at 20 of 50 bee colony amounts. In addition the convergence can also be seen on the number of iterations at 20 of the maximum number of iterations 50.
Pemodelan Sistem Pakar Diagnosis Penyakit Tanaman Apel Manalagi Dengan Metode Backward Chaining Menggunakan Certainty Factor Muhammad Burhannudin; Suprapto Suprapto; Nurul Hidayat
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 5 (2017): Mei 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (798.178 KB)

Abstract

Kota Batu is one Agropolitan city located in East Java province with huge potential for development in agriculture. Apple is a fruit plant that can live well in the highlands. This plant in Indonesia since 1934. As other fruit crops, apples are also susceptible to the disease. Maintaining plants from disease is also an attempt to preserve the environment. One form of such vandalism is negligence of farmers in preserving plants from disease. Making this system an attempt to perform human roles. This system is expected to help farmers, in particular, to be able to identify precisely the apple crop diseases and appropriate. So can meminimalisi impact. This application is developed using PHP programming language and MySQL database. Both are a combination of the most popular in the manufacture of web-based applications. While the inference method used is Backward chaining which is based on the tracking of data or facts then led to the conclusion in the form of conclusions pests or diseases that attack the apple crop. Tests performed by comparing the suitability of the output with the diagnosis expert system. And of the 30 test cases the data obtained accuracy rate modeling expert system testing using methods Certainty Factor on apple crop disease diagnosis system amounted to 93.3%. With the accuracy of the results indicate that the system is able to replace the role of experts.
Sistem Pendukung Keputusan Budidaya Tanaman Cabai Berdasarkan Prediksi Curah Hujan Hilal Imtiyaz; Barlian Henryranu Prasetio; Nurul Hidayat
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 9 (2017): September 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (818.47 KB)

Abstract

Abstract Chili is one of holticultura product wich is needed every day by Indonesian people. They use chili for spice in cooking. Chili supply not any time to meet demand. It causes price increases in accordance with the law of demand and supply. The surge in prices because of limited supplies occur every year. One of the problems that cause unavailability of supply throughout of year is chili crop failure cause chili cultivation is not good. pepper cultivation planning must consider the rainfall so that water for plants is available. Chili plants would not grow well if the plants lack of of water or if the water is too much. It will disturb chili growth, fertilization and crop becomes susceptible to pests. The main source off plants irrigation is rain. Knowledge of rainfall in the future will help farmers in cultivating planning. This research will discuss about decision support systems of chilli cultivation based on the rainfall prediction using simple linear regression method. Regression method used to predict the rainfall with modeling rainfall data in previous years. Based on the data the rainfall forecasts, system will recomanded best ways of pepper cultivation. Results of rainfall prediction using simple linear regression method has the accuracy rate of 91.6% which inluantial to the good of chili cultivation. Keywords: Decision Support Systems, Chili, Simple Linear Regression, Rainfall.
Pemodelan Sistem Pakar Diagnosis Penyakit pada Sistem Endokrin Manusia dengan Metode Dempster-Shafer Didin Wahyu Utomo; Suprapto Suprapto; Nurul Hidayat
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 9 (2017): September 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (986.953 KB)

Abstract

The endocrine system is a gland system that acts on the human body whose secretedness called as hormones. Hormones are chemicals which carried within the bloodstream to tissues and organs and then stimulate hormones to perform certain actions. Hormones work directly into the blood without going through the ductus. Endocrine disease is very dangerous and can even lead to death if it were not treated immediately. In the BPJS system that implemented by the Indonesian government, general practitioners serve as the main gateway in diagnosing the disease or determining whether to be referred to a specialist. In the case of endocrine disease patients, it is very dangerous if not treated early, whereas referral process to a specialist or hospital takes a long time due to many patients who come. The purpose of this modelling system is one way done that aims to provide early help for patients with endocrine diseases. This application is developed by using PHP programming language using CodeIgniter framework and MySQL database. The process of calculating the diagnosis of disease using the Dempster-Shafer method. Testing is done by comparing the conformity of results between the diagnosis of the system and the results of expert diagnosis. Based on 35 tested data, obtained 91.428% test accuracy level indicating that modeling expert system diagnosis of endocrine disease with dempster-shafer method can well functioned
Sistem Pendukung Keputusan Untuk Pemilihan Penanaman Varietas Unggul Padi Menggunakan Metode AHP dan TOPSIS Muhamad Rendra Husein Roisdiansyah; Agus Wahyu Widodo; Nurul Hidayat
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 10 (2017): Oktober 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (684.077 KB)

Abstract

According to the data from Indonesian Center for Rice Research, until today there is already 48 varieties of inpari, 19 varieties of hipa, 11 varieties of inpago, and 9 varieties if inpara that has been relased and there is a possibility that this ammount will increase each year. This amount does not include the high yielding varieties that are still cultivated to date such as ciherang, IR 64, Cibogo, IPB 3S, and others. The excessive ammount of varieties of rice crops along with their own criteria can cause problems, how do farmers choose the right varieties to maintain their crops maximally.There is a solution for this problem that is using a Decision Support System (DSS). In this research, the system is created by combining 2 DSS methods, that is Analytic Hierachy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Those methods was chosen because it is considered to produce a more accurate decisions and more objective than using one method alone. The AHP method will generate the weight of criteria that can also be used in the weighting process in the TOPSIS method. The Input from the system created is divided into 2. In the AHP using pairwise comparison table data from the criteria of superior varieties, the TOPSIS method uses data description of varieties that become the alternatives. The results of the system made shown as a ranking of alternatives from best to worst. System testing is done by matching the results of the system with the results of the experts, based on testing conducted, obtained the results of accuracy at 83.33%.
Rekomendasi Pemilihan Properti Kota Malang Menggunakan Metode AHP-SAW Syafruddin Agustian Putra; Nurul Hidayat; Lailil Muflikhah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 10 (2017): Oktober 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1140.991 KB)

Abstract

The increasing of population number in Malang City triggered property developers to answer people's needs by developing and supplying assorted facilities of property. Many criterias should be considered by prospective buyers in selecting a property, for example: price, number of bedrooms, bathrooms, garages, building area, and land area. The numerous considerations referring to some specific criteria lead prospective buyers to take a difficult decision. Regarding to this problem, there are several methods able to resolve the complicacy of buyers in taking decision, which are performing combination of Multi Criteria Decision Making (MCDM) method by using Analytic Hierarchy Process (AHP) as a way to calculate weight of each determined criterion, and Simple Additive Weighting (SAW) as a method used in ranking the criteria. In functional test, the result of 100% represents that the system runs very well as designed. And from the accuracy test, the result is 80.80%. In sum, the AHP-SAW method combination is compatible to be used in selecting property in Malang City
Implementasi Algoritma Modified K-Nearest Neighbor (MKNN) untuk Klasifikasi Penyakit Demam Fakihatin Wafiyah; Nurul Hidayat; Rizal Setya Perdana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 10 (2017): Oktober 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1192.322 KB)

Abstract

Fever is an early indicator for some diseases such as dengue fever, typhoid and malaria accompanied by similar symptoms, including muscle pain, indigestion, tongue condition and enlargement of the liver and spleen. Similar symptoms of each disease cause difficulties in getting anamnese (temporary diagnosis) so that patients get the inadequate initial treatment. Handling the problem, technology is needed to obtain a temporary diagnosis by applying one of the classification method of Modified K-Nearest Neighbor (MKNN). The method studied the pattern of previous examination data based on 15 symptoms of disease with eucledian distance calculation process, calculation of validity value and weighted voting calculation that the end result is used for class classification determination based on predetermined value of K. Testing of the value of K get the accuracy of 88.55%. The average value of accuracy obtained from testing of variation in the amount of training data is 92.42%. Testing the influence of the composition of train data get the average value of accuracy of 87.89%. Testing the influence of the composition of train data and test data get the average value of accuracy of 96.35%
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