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All Journal International Journal of Electrical and Computer Engineering Jurnal Ilmu Komputer dan Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Register: Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Misykat: Jurnal Ilmu-ilmu Al-QurÆan, Hadist, Syariah dan Tarbiyah Systemic: Information System and Informatics Journal Indonesian Journal of Electrical Engineering and Computer Science Jurnal Sistem Informasi, Teknologi Informasi, dan Edukasi Sistem Informasi (JUST-SI) Kertha Widya : Jurnal Hukum
M. Ali Fauzi
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Social Sciences Other

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Analisis Sentimen Terhadap Tayangan Televisi Berdasarkan Opini Masyarakat pada Media Sosial Twitter menggunakan Metode K-Nearest Neighbor dan Pembobotan Jumlah Retweet Winda Estu Nurjanah; Rizal Setya Perdana; Mochammad Ali Fauzi
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

Twitter is a social media that attracts many internet users as a media for communication and getting information. The information covered on Twitter in the form of questions, opinions or comments, whether it is positive or negative. Sentiment analysis is a part of research from Text Mining that conducted the classification process on text documents. K-Nearest Neighbor was used as method of this research, by adding the quality of retweet (non-textual). The result of textual quality of the K-Nearest Neighbor classification and the non-textual quality from the sum of retweets would be combined using certain constants (α and β) to generate positive and negative sentiments. The data was used in the form of public opinion on the television show on twitter showed 400. From the test results of accuracy using non-textual quality obtained 82.50%, using 60% non-textual quality, and use the combination of both was 83.33% with the score k=3 and the exact multiplication constant α=0,8 and β=0.2.
Named Entity Recognition Menggunakan Hidden Markov Model dan Algoritma Viterbi pada Teks Tanaman Obat Agung Setiyoaji; Lailil Muflikhah; Mochammad Ali Fauzi
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

Media to convey information can be through television, radio, social media, and website. Website is a work of someone located in a domain that contains information. The development of websites more and more information is not unstoppable so that the problem arises difficult to find information in accordance with the needs of Internet users, so that the required classification and extraction of information for information on the website. Named Entity Recognition which derives from the extraction of information, NER aims to facilitate the search for information by naming entities on each word in a text. In this research will be done the introduction of four entities namely the NAME, PLACE, SUBSTANCE, and FUNCTION of the text on medicinal plants. The algorithm used Hidden Markov Model (HMM) and Viterbi algorithm. Overall entity recognition count the lowest value with f-measure 0.41, and the highest with f-measure 0.72.
Penentuan Kelayakan Lokasi Wifi.Id Corner Dengan AHP-PSO (Studi Kasus: Telkom Kota Kediri) Ulfa Lina Wulandari; Dian Eka Ratnawati; Mochammad Ali Fauzi
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

Wifi.id Corner (wico) is a public facility of innovation from Telkom in the form of a place that provides internet access with high speed up to 100 Mbps. Currently, the determination of the location of Wifi.id Corner Telkom Kediri is done based on the consideration of the parties and managers of Wireless Broadband Division (DWB). So often have difficulty in determining the feasibility of installation location Wifi.id Corner from several proposed locations. This is due to the difficulty to determine the feasibility of location and which location can provide maximum benefits for the community and for Telkom Kediri. In determining the feasibility of Wifi.id Corner location there are 4 criteria by the company. There are the availability of network, users crowded, location type and density of Wifi.id Corner around the location. To solve this problem used Analytic Hierarchy Process (AHP) and Particle Swarm Optimization (PSO) methods. PSO is used to optimize the value of comparison matrix weight in AHP. The length of the used dimension is 6. Where each dimension value represents the comparative value of each criteria in the comparison matrix. In this research used 50 data location of Wifi.id Corner Telkom Kediri. From the test results obtained by the average fitness value of 0,94 with parameters of threshold value of 0,018, size of particles is 250 and number of iteration is 10 so that the obtained accuracy is 94%.
Optimasi Susunan Gizi Makanan Bagi Pasien Rawat Jalan Penyakit Jantung Menggunakan Real Coded Genetic Algorithm (RCGA) Ratih Diah Puspitasari; Dian Eka Ratnawati; Mochammad Ali Fauzi
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

Heart is one of the most important organs in the human body. Nowadays, coronary heart disease is one of the diseases that tend to invade a person's heart and dietary arrangements is a must for people who have this kind of disease in order to be healthy like normal people. This research is focused on recommending food nutrition for outpatients who suffers from coronary heart disease that often called diet heart 4. This study, titled optimization arrangement of food nutrition for outpatient using real coded genetic algorithm (rcga), the results that is displayed by the program is patient's data such as age, weight, height and foodstuffs that comply with the needs of the outpatients with the lowest prices of any food. This algorithm consists of an initial population of the initialization stage, the reproduction consisting of crossover and mutation, the calculation of the fitness and selection. The research on using the names of 271 food with nutrient content (source of carbohydrates, a source of protein, vegetable source of protein, vegetables, fruits, snacks, and oil/FAT). From the results of testing, this research obtained optimal parameters of 500 population with average fitness of 12347, 3, 50 generations with average fitness of 11795.8 and the combination of cr = 0 and mr = 0.9. with an average value of fitness 11940.7. The results of the program with the parameter generate an average median difference in actual data - with data from the program of 51.815 or 2.30%.
Klasifikasi Teks Pengaduan Pada Sambat Online Menggunakan Metode N-Gram dan Neighbor Weighted K-Nearest Neighbor (NW-KNN) Annisya Aprilia Prasanti; Mochammad Ali Fauzi; Muhammad Tanzil Furqon
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 2 (2018): Februari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

SAMBAT Online is a concrete application of E-Government in a web-based platform for complaints provided by Dinas Komunikasi dan Informatika Kota Malang (Diskominfo Malang). An incoming complaint text will be categorized into various areas of the SKPD. With that being said, in order to make the job of the super admin easier in organizing and determining an SKPD category, as well to organize a complaint text and improve the time efficacy, a method of text classification is paramount. NW-KNN is an upgraded algorithm of the traditional KNN algorithm. Generally, the closest neighboring distance calculations will use Cosine Similarity with bag of words for feature extraction. Bag of words is a feature extraction that ignores the order of words of a sentence altogether. To improve the algorithm despite the deficiency, this research will use supporting method for feature extraction, which is called as N-Gram. The result in this research indicated that NW-KNN with neighboring value k = 3 and N-Gram with Unigram have the highest f-measure's value with 75.25%.
Penentuan Penerima Bantuan Ternak Menggunakan Algoritma K-Means & Naive Bayes Moh Fadel Asikin; Dian Eka Ratnawati; Mochammad Ali Fauzi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 2 (2018): Februari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Indonesia is a vast country with many islands suitable for the development of livestock business. In reality, the livestock sector has not been able to encourage public and private participation. To overcome these problems, some of the budget of the Ministry of Agriculture is allocated in the form of social assistance expenditures, such as for community empowerment and poverty alleviation in the form of goods to farmer groups. One of the forms of assistance allocated to farmer groups is the provision of livestock. Determination of potential recipients is still not effective and sometimes leads to the giving of livestock assistance is not right on target, so that every expenditure of state money does not provide maximum benefits for the community. In this research, K-Means Naive Bayes (KMNB) method is considered capable of giving accurate classification results on the determination of livestock recipients. The KMNB learning approach is formed by combining clustering and classification techniques. K-Means is used as a pre-classification component to group the same data at an early stage. Furthermore, for the second grouping of data will be classified by category Accepted or not using Naive Bayes. Thus, the data with the wrong group during the first stage will be classified according to the category in the second stage. Based on the test results by comparing the results of grouping on conventional K-Means method it is proven that KMNB gives the highest accuracy of 100% while conventional K-Means has an accuracy of 95.91%
Sistem Temu Kembali Informasi Pasal-Pasal KUHP (Kitab Undang-Undang Hukum Pidana) Berbasis Android Menggunakan Metode Synonym Recognition dan Cosine Similarity Safier Yusuf; Mochammad Ali Fauzi; Komang Candra Brata
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 2 (2018): Februari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Kitab Undang-undang Hukum Pidana (KUHP) is a matter that must be studied and even memorized for people engaged in their field, such as police, law enforcement officials, judges, lawyers or persons associated with the trial. KUHP is a book in which it consists of dozens of chapters and hundreds of chapters with a total of 569 articles, so that with a thick book it will become very inefficient and practical if it must be brought and also if you want to find related chapters that must open the page one by one manual. Based on these conditions in this study developed applications using synonym recognition and cosine similarity methods. Synonym recognition is a technique used to recognize words with different writing but has the same meaning. The cosine similarity method is used to calculate the similarity or closeness of the chapter documents with the query. The performance of the system is indicated by the results of the tests on each threshold variation of 5, 10 and 15, with optimal performance is at threshold 15 which has f.measure value of 0.404.
Optimasi Sisa Bahan Baku Pada Industri Mebel Menggunakan Algoritma Genetika Andika Indra Kusuma; Agus Wahyu Widodo; Mochammad Ali Fauzi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 3 (2018): Maret 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The problem of the utilization of raw materials in the furniture industry is the difficulty of cutting raw materials with the right combination of sizes. To adjust the furniture production requirements, standard-sized raw materials must be cut to fit the needs of the furniture model to be produced. If not done the exact calculation when cutting the raw materials will certainly produce a lot of waste materials unused. The abundance of unused raw materials is what causes the maximum profit can not be achieved so that optimization of the remaining raw materials needs to be done. In this research optimization of the remaining raw materials is done with Genetic AlgorithmCorner Junction (GA+CJ). Stages performed are initial population generation, mutation with Rectangle &Junction Gene Swap Mutation(RJGSM) and Rectangle Rotation Mutation(RRM), evaluation, and selection. The results obtained in the form of chromosome-shaped solution arrangement of pieces of material. The highest fitness is 0.0026 which means consuming 16 pieces of raw material located on generation input parameter as much as 120 generations, mutation rate equal to 0.9, and 60 populations.
Sentiment Analysis Peringkasan Review Film Menggunakan Metode Information Gain dan K-Nearest Neighbor Ria Ine Pristiyanti; Mochammad Ali Fauzi; Lailil Muflikhah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 3 (2018): Maret 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The film reviews contain an opinion from a reviewer to describe a movie. Assessment of the content from the film review can be called by sentiment analysis. Sentiment analysis on movie review is divided into 2 parts, which are positive review and negative review. Grouping of sentiment analysis results can be simplified by the k-nearest neighbor classification method where this method will look for documents that have similarity between one to another document. In general, the movie review data contains very long content required by feature selection or pruning feature to reduce dimensions during classification process. In this case, the method of information gain is used to reduce many features during the classification process. This method will predict the presence or absence of term in a document so the term that frequently appear has low information gain value, however for the term that rarely appear or only appear in one category has high information gain value. The term with high information gain value will be able to be used for classification process. The result for using all of term for classification is 92% accuracy where the accuracy value is better than the feature selection due to the elimination of term having low information gain value.
Peramalan Produksi Gula Menggunakan Metode Jaringan Syaraf Tiruan Backpropagation Pada PG Candi Baru Sidoarjo Adi Sukarno Rachman; Imam Cholissodin; Mochammad Ali Fauzi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 4 (2018): April 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Sugar is a staple that is routinely used by the people of Indonesia. Sugar is often used in the food and beverage industry, food processing and preservation industries. Sugar needs increased supported by the lifestyle of Indonesian people, especially in daily life. PG Candi Baru is a sugar faktory that was built in 1832 and is a sugar-producing company SHS I (Superior Hooft Suiker) or White Crystal I (GKP). Since 2004 PG Candi Baru has greatly improved the company's performance and made changes through technological breakthroughs in the field of on farm and off farm. This research uses Artificial Neural Network backpropagation with network architecture design in the form of 4 input layer neurons, 3 hidden layers, and 1 output layer. Based on testing the maximum number of iterations obtained the lowest MAPE value of 17.85% with the number of iteration 800. And in the test of learning rate obtained the lowest MAPE value of 17.38% with the value of learning rate 0.4. If the maximum iteration value of 800 and the value of learning rate 0.4 will result in MAPE value of 16.98%.
Co-Authors Adi Sukarno Rachman Adinugroho, Sigit Aditya Kresna Bayu Arda Putra Agnes Rossi Trisna Lestari Agung Setiyoaji Agus Wahyu Widodo Agus Zainal Arifin Ahmad Galang Satria Ahmad Wildan Attabi' Akbar, Aldi Fandiya Alvandi Fadhil Sabily Amalia Kusuma Akaresti Andika Indra Kusuma Andro Subagio Anita Sumiati Annam Rosyadi Annisya Aprilia Prasanti Annisya Aprilia Prasanti Anny Yuniarti ari kusyanti Bayu Rahayudi Billy Sabilal Budi Darma Setiawan Budi Kurniawan Chusnah Puteri Damayanti Claudio Fresta Suharno Claudio Fresta Suharno Dahnial Syauqy Desfianti, Ruri Dhimas Anjar Prabowo Dian Eka Ratnawati Dimas Joko Haryanto Dwi Damara Kartikasari dwi taufik hidayat Edy Santoso Eka Dewi Lukmana Sari Elisa Julie Irianti Siahaan Eti Setiawati Fachrul Rozy Saputra Rangkuti Fakhruddin Farid Irfani Fathor Rosi Ferly Gunawan Ferly Gunawan Figgy Rosaliana Fitra Abdurrachman Bachtiar Galih Nuring Bagaskoro Gosario, Sony Hadiyan Hadiyan Hasbi Razzak Hidayat, Hasannudin Hilmy Khairi Idris Hurriyatul Fitriyah I Wayan Sudira Imam Cholissodin Imam Cholissodin Indriati Indriati Irma Pujadayanti Irwin Deriyan Ferdiansyah Ismiarta Aknuranda Isnan . Joda Pahlawan Romadhona Tanjung Komang Candra Brata Lailil Muflikhah Laksono Trisnantoro Liana Shinta Dewi Liana Shinta Dewi Lita Handayani Tampubolon M Yusron Syauqi Dirgantara M. Rizzo Irfan M. Rizzo Irfan Mahdarani Dwi Laxmi Mahendra Data Malahayati, Salsabila Nur Maulana, Muhammad Afif Moch. Yugas Ardiansyah Moh Fadel Asikin Moh Iqbal Yusron Muhammad Fhadli Muhammad Hakiem Muhammad Khaerul Ardi Muhammad Khatib Barokah Muhammad Mishbahul Munir Muhammad Sholeh Hudin Muhammad Tanzil Furqon Nanda Firizki Ananta Ni Made Gita Dwi Purnamasari Ni Made Gita Dwi Purnamasari Nining Nahdiah Satriani Nur Hijriani Ayuning Sari Nurul Dyah Mentari Nurul Dyah Mentari Nurul Hidayat Prananda Antinasari Primantara Hari Trisnawan Putra Pandu Adikara Qiindil, Audry Rachmad Indrianto Rahmat Yani Rakhman Halim Satrio Randy Cahya Wihandika Ratih Diah Puspitasari Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Resti Febriana Ria Ine Pristiyanti Rika Raudhotul Rizqiyah Rizal Maulana Rizal Maulana, Rizal Rizal Setya Perdana Ro'i Fahreza Nur Firmansyah Robertus Santoso Aji Putro Rodhiya, Hanif Robby Rosy Indah Permatasari Safier Yusuf Saiful Bahri Shandy, Ryo Shima Fanissa Silalahi, Gifo Armando Silvia Aprilla Sonny Christiano Gosaria Sudin, Mahmudin Suryani Agustin Sutrisno Sutrisno Thio Marta Elisa Yuridis Butar Butar Tibyani Tibyani Tibyani Tibyani Tri Afirianto Tri Afirianto Ulfa Lina Wulandari Umi Rofiqoh Ummah Karimah, Ummah Uswatun Hasanah Utaminingrum, Fitri Veronica Kristina Br Simamora Vina Adelina Wahyuni Lubis Widhi Yahya Wildan Aulia Rachman Winda Estu Nurjanah Winda Fitri Astiti Yessivha Imanuela Claudy Yuita Arum Sari Yuita Arum Sari Zafran, Muhammad Abyan Zubaidah Al Ubaidah Sakti