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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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Klasifikasi Multilabel Menggunakan Metode Fuzzy Similarity K-Nearest Neighbor Untuk Rekomendasi Pencarian Artikel Online Wahyuni Lubis; Yuita Arum Sari; Mochammad Ali Fauzi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The article is someone's opinion of the paper that addresses a specific problem that is actual and sometimes controversial to inform, influence, persuade, and entertain the reader. Rapid technological developments led to the large number of articles written online. Each article has a different label online, and allows each article has more than one label. The number of online articles that exist on the internet every day growing which makes the reader's difficulty in finding the desired information. The proper classification can improve the quality of information retrieval. A method of Fuzzy K-Nearest Neighbor Similarity is a method that combines the multilabel classification method of Fuzzy Similarity Measure and MLKNN. Previous research on method FSKNN has better speed in doing computing k nearest neighbors and better performance of the method MLKNN. The steps undertaken in this research is conducting a text preprocessing, document clustering, weighting, classification and search process. On the research of the optimal values obtained this F1 and BEP amounted to 0.933 and 0.937 at k = 1 and alpha = 0.5. On the recommendation of the search articles online using the method FSKNN obtained the highest precision value of 0.5 and 0.8 recall. From the results of F1 and the BEP obtained, indicating that the method FSKNN was kind enough to do a multilabel classification articles online.
Evolution Strategies Untuk Optimasi Pembentukan Fungsi Regresi Linier Dalam Menentukan Kebutuhan Volume Air Penyiraman Tanah Robertus Santoso Aji Putro; Nurul Hidayat; Mochammad Ali Fauzi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Seed Laboratory BPTP East Java is one of provincial government work units that was appointed as the technical implementer to conduct a study in seed growth. Currently this facility is developing automatic watering device based on soil humidity sensor, but the device cannot predict the volume of water needed in order to keep the soil moisture. With the help of humidity sensor on device and expert's knowledge, the observations dataset of soil moisture to the waters volume requirement are obtained. This study was conducted to implements linear regression method so that the device can perform predictions based on dataset patterns as an equation. The accuracy of prediction results with this method is measured by the coefficient of determination. The coefficient of determination can be decreasing due to the arising of observation outliers because Inaccuracy of observation results. The solution from this study is using evolution strategies with information criteria as comparison for detecting observation outliers to eliminated. After eliminating 6 observations outliers were detected by evolution strategiess in this study, shows increase in the coefficient of determination from 0.9673 to 0.9935
Klasifikasi Teks Bahasa Indonesia Pada Dokumen Pengaduan SAMBAT Online Menggunakan Metode Naive Bayes dan Kombinasi Seleksi Fitur Hilmy Khairi Idris; Mochammad Ali Fauzi; Indriati Indriati
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

SAMBAT Online is a form of e-Government realization in Malang City. SAMBAT Online or The Integrated Online Community Application System is a platform of a website provided by the Malang City Government to receive complaints, criticisms, suggestions, or questions to the government. Each incoming report will be grouped manually by the SAMBAT Online system manager. Grouping is based on The Regional Work Unit (SKPD) which is handled manually. Therefore, a classification system was built to save time in the process of grouping reports to SKPD using the Naive Bayes method and the Combination of Feature Selection between Chi-Square and Information Gain. In the tests conducted, the system succeeded in providing better accuracy results when using feature selection than without using feature selection with an accuracy value of 83.33%. Furthermore, when a feature selection combination is performed, the results of the accuracy obtained are the same as the results without a combination of 83.33%. So, the combination of selection has not been able to provide better results.
Klasifikasi Ujaran Kebencian pada Twitter Menggunakan Metode Naive Bayes Berbasis N-Gram Dengan Seleksi Fitur Information Gain Muhammad Hakiem; Mochammad Ali Fauzi; Indriati Indriati
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

Hate speech is one of the topics that often discussed in information technology. Hate speech has been usually used by the people that don't like or hate with someone or a group. People stated their hate speech with post it in social media. One of the most used social media to spread the hate speech is Twitter. Hate speech identification is needed to decrease the spread of hate speech. The method used in this research is Naive Bayes based on N-gram and feature selection Information Gain. N-gram features that used in this research are Unigram, Bigram, and combination unigram-bigram. 250 data are used in this research with hate speech label and 250 data with non hate speech label and have 80% proportion for data training and 20% for data testing. The best accuracy results in this research come from Unigram feature and without feature selection Information Gain. The best accuracy result is 84%, precision value 92%, recall value 79,31%, and f-measure value 85,18%. Based on the results obtained it can be concluded that to classify hate speech in Twitter using Naive Bayes has the best result with Unigram feature and without using feature selection Information Gain.
Implementasi Metode Time Invariant Fuzzy Time Series Untuk Memprediksi Jumlah Keberangkatan Penumpang Pelayaran Dalam Negeri Di Pelabuhan Tanjung Priok Dwi Damara Kartikasari; Budi Darma Setiawan; Mochammad Ali Fauzi
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

Maritime transportation is considered to have an important contribution in advancing the national economy in Indonesia, considering that 75% of Indonesia's territory is in the ocean. Maritime transportation has also become an alternative of transportation between islands recently. Moreover with the increase in the number of vehicles on land from year to year resulting in congestion on the highway, of course this will further increase public interest in making maritime transportation an alternative to their transportation. But in every cruise, the number of passengers always decreases or increases. The uncertainty of the number of passengers must be predictable, so that further policies can be made from the port to anticipate the number of passengers in the future, in order to increase economic benefits in the sea transportation sector. The method used to make predictions in this research is Time Invariant Fuzzy Time Series with the data used is the number of cruise passenger departures at Tanjung Priok Port in the period January 2006 to December 2015. Based on the results of the test, the smallest of Mean Average Percentage Error (MAPE) is 17.39% using the number of fuzzy sets = 5; training data = 108, 96, 84, and testing data = 12.
Klasifikasi Berat Badan Lahir Rendah (BBLR) Pada Bayi Dengan Metode Learning Vector Quantization (LVQ) Suryani Agustin; Budi Darma Setiawan; Mochammad Ali Fauzi
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

Low Birth Weight (LBW) is the condition as a birth weight of a baby less than 2500 grams or 2.5 kg.. LBW is a factor of infant mortality in Indonesia. The prevention and treatment of pregnant women when they know they will give birth to babies with LBW are very necessary, in order to minimize the death during the birth process. Therefore, it is expected that the existence of a low birth weight classification system in infant can help to identify the condition of the baby in pregnant women before the baby is born. This research use the Learning Vector Quantization (LVQ) method with 96 data and 6 features, there are age, education, parity, birth interval, hemoglobin and nutritional status. Those who will classify into two classes first is case class, which means the baby is born with LBW and the control class means that the baby is born without LBW. Based on the results of testing, the system produces an average accuracy is 60.5% using optimal parameters for learning rate 0.1, learning rate decrement 0.1 and maximum epoch is 5. In the k-fold cross validation testing the best accuracy value is 58.3% and the average accuracy is 46.85%.
Penentuan Seleksi Atlet Taekwondo Menggunakan Algoritme Support Vector Machine (SVM) Uswatun Hasanah; Imam Cholissodin; Mochammad Ali Fauzi
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

Martial arts is an art that in use for defense or defense, protecting one's self when subjected to danger. Taekwondo is a martial art that originated in Korea that uses the hands and feet with the rules and ethics of discipline. Public physical exercise in a prepare taekwondoin i.e. MTH, 300 meter run, run back and forth 6 meters, side kick, back kick, front kick, Crescent kick, block, punch, horses, jump rope, push ups, sit ups, pull ups, backing up, triple hops. The purpose of this research can apply the algorithm support vector machine in determining the selection athlete taekwondo. On this research uses data sets that 116 has 16 parameters. Then the data is divided into training data and test data which used the method with a K-Fold Cross Validation, with k = 10. The result of the implementation of the algorithm of support vector machine for determination of taekwondo athletes in the classification selection qualify and do not qualify for the best accuracy results obtained with the parameters used, namely a comparison ratio data = 90%: 10%, a parameter λ ( lamda) = 10, the parameter γ (gamma) = 0.001, the parameter C (constant) = 1, parameter ϵ (epsilon) = 0.001 maximum iterations, 30. So the average accuracy is obtained that is 100%.
Sistem Temu Kembali Informasi Pasal-Pasal KUHP Menggunakan Metode Cosine Similarity dan Pembobotan Inverse Book Frequency Billy Sabilal; Mochammad Ali Fauzi; Indriati Indriati
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

Indonesia law based on the Kitab Undang-undang Hukum Pidana (KUHP) is a matter that must be obeyed as a people or related in their field, such as the police, judges or people associated with the trial. Kitab Undang-undang Hukum Pidana contains 569 pasal in the book that will be very inefficient and practical if you have to take it and also if you want to find related articles that have to open pages one by one manually. Based on these conditions the application developed an application using the cosine similarity method and weighting inverse book frequency. Cosine similarity method is used to calculate the similarity or proximity of article documents to queries. Weighting inverse book frequency weighting terms that consider the distribution of book collections. The value of each term is assumed to have a proportion opposite to the number of books containing that term. The performance of the system is indicated by the results of testing on each variation of 10 queries by dividing 3 1-word queries, 3 2-word queries, 3 3-word queries and 1 4-word queries tested, with performance precision values of 0.5273, recall 1, f.measure 0.6063 while the best precision@k results in the third rank of 0.6498.
Implementasi Metode Naive Bayes - Weighted Product Untuk Diagnosa Penyakit Ikan Kerapu Annam Rosyadi; Edy Santoso; Mochammad Ali Fauzi
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

Grouper (Epinephelus sp.) Is a fish that lives in seawater that has high economic value, so it is consumed by many Indonesians because of its delicious taste. However, during grouper cultivation, there are problems that arise, namely the existence of diseases that can cause death. Usually in the grouper, there are many diseases that originate from bacteria, parasites, viruses, and other sources, namely lack of nutrition and decreasing water quality in ponds. So that the existence of this system can provide information to pond farmers about the types of diseases in groupers and handling that can be given. In this system using the naive bayes - weighted product method. The Naive Bayes method serves to search for probability values for each symptom in the disease. The weighted product method serves to draw conclusions on the diagnosis of grouper disease using alternative values of S and V criteria. There are 6 diseases and 16 symptoms in groupers in this system. Accuracy testing using a lot of data as much as 100 test data obtained an accuracy value of 94%.
Analisis Sentimen Pemilihan Presiden 2019 pada Twitter menggunakan Metode Maximum Entropy Alvandi Fadhil Sabily; Putra Pandu Adikara; Mochammad Ali Fauzi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In this modern era, communication can be done through various media, one of which is through online media, namely Twitter. Twitter is one of the social media that functions to exchange information and also express an opinion on something. Twitter posts that discuss presidential elections are the objects used in this study. To find out whether a sentiment has a positive or negative value, a sentiment analysis is needed as in this study. To analyze a sentiment, a method that can classify sentiments is needed, Maximum Entropy is the method used in this study with the evaluation method used is Confusion Matrix which will then calculate the value of Macro and Micro averaging from the evaluation value produced. The evaluation results carried out in this study resulted in quite high Macro accuracy values ​​of 89.16% with precision and recall values ​​of 100% and 89.16% and also F-measure values ​​of 94.27%. Testing is done by testing 120 tweets and training data used as many as 300 tweets.
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