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All Journal Journal of Environmental Engineering and Sustainable Technology Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer JOURNAL OF APPLIED BUSINESS ADMINISTRATION Indonesian Journal of Electrical Engineering and Computer Science
Muhammad Tanzil Furqon
Fakultas Ilmu Komputer , Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Mechanical Engineering Social Sciences

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Identifikasi Diagnosis Gangguan Autisme Pada Anak Menggunakan Metode Modified K-Nearest Neighbor (MKNN) Jojor Jennifer BR Sianipar; Muhammad Tanzil Furqon; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 9 (2017): September 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Autism is a neurological disorder that shows significant result as a lack of ability to form social relationships, normal communication, and behavior in children. This symptoms generally appear before children reach the age of 3 years. It is not classified as a psychiatric disease because autism is a disorder that occurs malfunction of children's brain and it is manifested on children's behaviour. Some research states that autism causes as the neurodevelopmental disorder that causes abnormalities in children's brain structure. Different experts mentioned that autism in children caused by the kind of food they consumed or they living environment that contain many harmful substances that shows in children's behaviour. Therefore, the system for the identification of autism disorders in children will be create to help identifies autism disorder by using the method of Modified K-Nearest Neighbor (MKNN). It is one of classification method based on the appearance of largest classes in data training. There are 14 symptoms from 4 aspects that are used as parameters in the development of the system. The output of the system is showing whether a child is autistic individuals or not. Based on the testing that has been done on the system that using Modified K-Nearest Neighbor (MKNN), maximum accuracy shows 100% accuracy while minimum accuracy is 92%. Based on those results, the uses of Modified K-Nearest Neighbor (MKNN) method can be implemented in our daily life.
Implementasi Metode Fuzzy Subtractive Clustering Untuk Pengelompokan Data Potensi Kebakaran Hutan/Lahan Vianti Mala Anggraeni Kusuma; Muhammad Tanzil Furqon; Lailil Muflikhah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 9 (2017): September 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Abstract Forest is the habitat for all kinds of animals and plants, forests have a very big function to maintain the balance of nature, as the supplier of the oxygen requirement for living on earth, and the natural resources that provide a variety of materials for human needs. But at this moment the existence of forest diminishing due to illegal logging by humans or by forest fires are becoming more frequent. Forest fires this gives very bad impact, extinction of some species of plants and animals, the smoke is detrimental to health even low and so forth. So to be able to help deal with the issue made a system that can manage data hotspots (hotspots) with Fuzzy subtractive clustering. Parameter data used in the development of the system: brightness temperature and FRP (Fire Radiative Power). The result of clustering which illustrates the potential of forest fires, which are grouped in the high potential and low potential. The test results showed the best coefficient silhouette value of 0.45 and the results of the cluster is formed by two clusters using radius values ​​0.2, accept ratio 0.5, reject ratio 0.15. The results of the analysis in the determination of the potential for forest fires result is a high potential with an average brightness value of 335.727⁰K, FRP 57.248 and average confidence 83.47%. While medium potential with an average brightness value of 318.934⁰K, FRP 23.330 and average confidence 58.08%. Keywords: Clustering, Hotspot, Fuzzy subtractive clustering, Silhouette Coefficient
Sistem Pendukung Keputusan untuk Rekomendasi Wirausaha Menggunakan Metode AHP-TOPSIS (Studi Kasus Kab. Probolinggo) Ghulam Mahmudi Al Azis; Imam Cholissodin; Muhammad Tanzil Furqon
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 11 (2017): November 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Along with the growing number of Indonesian population, also raises the competition in looking for work. The limited job vacancy impacts the increasing number of unemployed every year. Until February 2016, the labor force in Indonesia reached 127 million people with an overall unemployment rate of 5.5% or 7 million people. To overcome this increasing number of unemployment, needed step solution that is in the form of decision support for entrepreneurship. Decision support systems can be used to recommend an entrepreneur for unemployment or everyone. AHP method and TOPSIS method is one of the methods of decision support system that can be combined with calculating the weight of criterion using AHP method then continued by calculating the value of preference for ranking from entrepreneurial alternative using TOPSIS method. The AHP-TOPSIS method will recommend the results of 3 entrepreneurs with the highest preference value. In accordance with the test results, that these application can help to recommend entrepreneurs in helping decisions support for user to choose an entrepreneur.
Implementasi Metode Improved K-Means untuk Mengelompokkan Titik Panas Bumi Al-Mar'atush Shoolihah; Muhammad Tanzil Furqon; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 11 (2017): November 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Disaster is an incident or a series of incidents that threaten and disturb people's lives and livelihoods caused by both natural and / or non-natural factors. One of the disasters that happen is fire. Fire is a flame that occur either in small or large size, burning in an unexpected area and difficult to control. Therefore, early prevention is needed. one of the way is with geothermal point which is detected by the satellite. It is used as the indicator of land and forest fires in a region, so that the more geothermal point exist, the more potential for landfill incidents in a region. Hence, it is necessary to implement a system that can cluster the geothermal point data that has the potential in causing fire with farious status such as high, middle, and low potential. Improved K-Means is one of the most popular clustering methods and it can be used for geothermal point grouping. This algorithm performs clustering process based on the maximum distance as the cluster center and the cluster center distance will be calculated with the other data to be grouped. The calculation is done continuously until the data clustering does not change. That case is proven in this research where the evaluation result that uses silhouette coefficient give the highest point of 0.908000874 for the value of cluster 2 and the amount of data 700.
Optimasi Fungsi Keanggotaan Fuzzy Tsukamoto menggunakan Algoritma Genetika untuk Diagnosis Autisme pada Anak Indra Eka Mandriana; Candra Dewi; Muhammad Tanzil Furqon
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 11 (2017): November 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Autism is a developmental disorder that cause children to experience social disruption in certain areas, such as communications, social interaction, emotional and behavioral symptoms that is difficult to be identified. According to research in autism, the number of children who suffered from autism is estimated to grow every year around the world, including in Indonesia. This research implement Fuzzy Tsukamoto method to optimized genetic algorithm in order to diagnose autism in children, by optimizing the constraints on all fuzzy variables.Chromosome representation that is used in this research is real code genetic algorithm which every chromosome will initialize the limitations on all fuzzy variables. Method that is used to the process of crossover is extended intermediate crossover and random mutation for mutation process while selection method used elitism selection. Based on the results, the system obtained the most optimal parameters on a method of CARS in a population of 50, 200 generations, as well as the combination of Cr = 0.8 and Mr = 0.1 with the fitness of 1, while on the CHAT population method 10, 100 generations, as well as the combination of Cr = 0.9 and Mr = 0.1 with fitness by 1
Aplikasi Perencanaan Wisata di Malang Raya dengan Algoritma Greedy Akhmad Eriq Ghozali; Budi Darma Setiawan; Muhammad Tanzil Furqon
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 12 (2017): Desember 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Malang raya is one of regions which becomes the main objective place to visit because it has many tourism places. The thing which has to be noticed is determining the tourism schedule, every tourist must choose the shortest distance and time to be able to reach that destination because they can save the time. To reach that destination, it is used greedy algorithm with knapsack problem to assist the optimation process against searching the shortest traveling time and how many tourism places which can be visited from the possessed time. Time allocation which is possessed by the user to tour is used as an integrity in calculating this application, while the traveling time at each tourism locations which are also used as an integrity is time data which is gotten from google maps. With thats data, the application with greedy algorithm will calculate the most optimal location to be visited with the time which belongs to the user. According to the result of testing application with ten sample of problem cases gets accuracy result 90% from two models of greedy algorithm calculation in searching location which can be visited by the allocation time which is owned. While the result of optimal tour accuracy that is visited is 0% from the first model of calculation and 80% from the second calculation.
Rekonstruksi 3 Dimensi dari Video menggunakan Metode Structure-From-Motion (Studi Kasus: Wilayah Pertambangan Batubara) Rimba Anditya Kurniawan; Fatwa Ramdani; Muhammad Tanzil Furqon
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 12 (2017): Desember 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Indonesia is a country that have a massive natural resources for producing coal. With total 466.307.241 ton in 2012, Indonesia archive third place world level as the most producer coal. For manage coal mining sites, management process very needed. The mine management process can be done with 3-dimensional point clouds reconstruction using the Structure-of-Motion Method (SfM). To build structure from overlapping of many images by using photogrammetry techniques use SfM algorithm. When acquisition image data, sometimes get a failure of automatic camera trigger and lack of density between images. This study uses video data from UAVs flown over mining areas to record all mining activities. Video data predicted can reduce errors during image capture and increase the overlap value between successive images and increase the number of cloud points. The output on the software is tested using the Simple Regression method. This study shows that input video data with 1 minute duration and 90% overlap value can produce 2910 point cloud. The Simple Regression test result an F value of 12,408. It shows that the greater value of overlap, can produce a lot number of points cloud.
Implementasi Learning Vector Quantization (LVQ) untuk Klasifikasi Kualitas Air Sungai Rifwan Hamidi; Muhammad Tanzil Furqon; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 12 (2017): Desember 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Water is a one of the natural resources which is very important and necessary for the activity and survival of living things, as humans, animals and plants. River is one of the source from various alternative sources of water available for processing. But nowadays as growth of population grows, industrial growth, economic development and rising standard of living cause degradation of quality of water itself. Pollution of river occurs when in the water there are various substances or conditions that can reduce water quality standards that have been determined, so it can't be used for certain needs. Therefore, there is an effort to maintain the quality, quantity and continuity of river water by monitoring and measuring the quality of water. Previously, river water quality and measurement was measured using manual methods such as Water Pollution Index (IP), Water Quality Index (WQI) and STORET with high time and cost constraints. So that another method is needed to speed up the calculation process effectively and efficiently using Learning Vector Quantization (LVQ) method which can classify data into 4 water quality class of river based on 7 input parameters. The LVQ implementation process for river water classification begins with the dataset division, data training, data testing and classification that will result in a class of good, mild, moderate and heavy contaminated classes. The best average accuracy result is 81,13% using alpha 0,1, decrement alpha 0,4, comparison of training data and testing data 100: 35 from 135 total dataset, maximum epoch 10 and minimum epoch 0,001.
Peramalan Permintaan Daging Sapi Nasional Menggunakan Metode Multifactors High Order Fuzzy Time Series Model Taufan Nugraha; Muhammad Tanzil Furqon; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 12 (2017): Desember 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Beef is a commodity whose demand level is always high because it is a livestock product that has nutritional value to obtain protein requirement for society. Increase in beef demand in Indonesia has not been matched by beef production, in terms of both quality and quantity. Beef demand is influenced by beef production, beef consumption, and income levels. In anticipation of the increasing demand for beef, it is necessary to forecast to estimate future demand for beef. To make the forecasting there are various methods used, one of them is the method of multifactors high order fuzzy time series model. The method is a method of forecasting that uses antecedent factor and more than one order, which is considered better than using only one antecedent factor (Lin & Yang, 2009). This research obtained the average forecasting error rate (AFER) of 6.648381805287571% which shows that the smaller error value means the level of accuracy.
Prediksi Kebutuhan Air PDAM Kota Malang Menggunakan Metode Fuzzy Time Series Dengan Algoritma Genetika Khaira Istiqara; Muhammad Tanzil Furqon; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Water is one of the basic needs of living things derived from natural resources. The Government provides a regional water company called Perusahaan Daerah Air Minum (PDAM) to fullfil the clean water needs of the people of Indonesia, one of which is located in Malang. PDAM water needs prediction system serves to predict the water needs of the people of Malang, so water needs will be guaranteed in the future. Variable used is PDAM water usage data from 2008-2013. Genetic algorithms are used to optimize the subset of universe in fuzzy time series. Search solution uses real-coded chromosome representation, then processed with genetic operator (crossover, mutation and selection). Method of genetic operator used is one-cut-point crossover, uniform mutation and elitism selection. The result of testing genetic algorithm parameter values, obtained the optimal population size is 360, the length of chromosome is 60, the best combination of crossover rate and mutation rate are 0.4 and 0.2, and the number of optimal generation is 550. Based on the best genetic algorithm parameter value, obtained the prediction result with the error value (MAPE) is 2.266776%. These results showed a good predictive ability with low error values.
Co-Authors Abas Saritua Gultom Abu Wildan Mucholladin Achmad Arwan Achmad Ridok Adinda Chilliya Basuki Adinugroho, Sigit Agus Wahyu Widodo Ahmad Afif Supianto Akhmad Eriq Ghozali Al-Mar'atush Shoolihah Aldion Cahya Imanda Amalia Luhung Andini Agustina Anindya Celena Khansa Kirana Anjelika Hutapea Annisya Aprilia Prasanti Annisya Aprilia Prasanti Ardisa Tamara Putri Arief Andy Soebroto Arif Indra Kurnia Arina Rufaida Arinda Rachman Arjun Nurdiansyah Arya Perdana Arynda Kusuma Dewi Aryo Pinandito Aryu Hanifah Aji Asfie Nurjanah Audi Nuermey Hanafi Ayu Anggrestianingsih Barik Kresna Amijaya Bayu Rahayudi Bayu Rahayudi Bossarito Putro Brillian Ghulam Ash Shidiq Budi Darma Setiawan Candra Dewi Cusen Mosabeth Daniel Alex Saroha Simamora David Bernhard Defanto Hanif Yoranda Dendry Zeta Maliha Destin Eva Dila Purnama Sari Desy Andriani Diajeng Sekar Seruni Dian Eka Ratnawati Dwi Yana Wijaya Dyan Dyanmita Putri Dyang Falila Pramesti Dzar Romaita Edy Santoso Eko Ari Setijono Marhendraputro Eky Cahya Pratama Elan Putra Madani Erwin Bagus Nugroho Evilia Nur Harsanti Fadhilla Puji Cahyani Fahmi Achmad Fauzi Fajar Pradana Fatwa Ramdani, Fatwa Fernando Parulian Saputra Fikar Cevi Anggian Firdaus Rahman Fitra Abdurrachman Bachtiar Gabriel Mulyawan Ghulam Mahmudi Al Azis Guntur Syafiqi Adidarmawan Hangga Eka Febrianto Hanifa Maulani Ramadhan Hanifah Khoirunnisak Hugo Ghally Imanaka Humam Aziz Romdhoni I Gusti Ngurah Ersania Susena Imam Cholissodin Iman Harie Nawanto Imaning Dyah Larasati Inas Hakimah Kurniasih Indra Eka Mandriana Indri Monika Parapat Indriana Candra Dewi Indriati Indriati Inggang Perwangsa Nuralam Issa Arwani Jojor Jennifer BR Sianipar Julita Gandasari Ariana Jumerlyanti Mase Kevin Nadio Dwi Putra Khaira Istiqara Laila Diana Khulyati Lailil Muflikhah Listiya Surtiningsih Luthfi Faisal Rafiq M. Ali Fauzi Mahardhika Hendra Bagaskara Mahendra Data Maria Sartika Tambun Marji Marji Masayu Vidya Rosyidah Mochamad Ali Fahmi Muh. Arif Rahman Muhamad Fahrur Rozi Muhammad Aghni Nur Lazuardy Muhammad Iqbal Mustofa Muhammad Rafif Al Aziz Muhammad Riduan Indra Hariwijaya Muhammad Wafiq Naufal Sakagraha Kuspinta Nindy Deka Nivani Novanto Yudistira Nur Kholida Afkarina Nurdifa Febrianti Nurudin Santoso Nurul Hidayat Nurul Hidayat Nurul Ihsani Fadilah Ofi Eka Novyanti Oky Krisdiantoro Pangestuti, Edriana Pricielya Alviyonita Priyambadha, Bayu Putra Pandu Adikara Putri Indhira Utami Paudi R Moh Andriawan Adikara Raden Rafika Anugrahning Putri Raditya Rinandyaswara Raditya Rinandyaswara Rahman Syarif Randy Cahya Wihandika Ratna Ayu Wijayanti Restia Dwi Oktavianing Tyas Ridho Ghiffary Muhammad Rifaldi Raya Rifwan Hamidi Rimba Anditya Kurniawan Riski Nova Saputra Riza Rizqiana Perdana Putri Rizal Setya Perdana Robbiyatul Munawarah Romlah Tantiati Satrio Hadi Wijoyo Setyoko Yudho Baskoro Silvia Aprilla Sutrisno Sutrisno Tania Oka Sianturi Taufan Nugraha Teri Kincowati Tryse Rezza Biantong Ulva Febriana Vandi Cahya Rachmandika Vania Nuraini Latifah Vera Rusmalawati Vianti Mala Anggraeni Kusuma Weni Agustina Wildan Afif Abidullah Wildan Ziaulhaq Wildan Ziaulhaq Wilis Biro Syamhuri Yuita Arum Sari Yuita Arum Sari