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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) SITEKIN: Jurnal Sains, Teknologi dan Industri Journal of Environmental Engineering and Sustainable Technology Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal POINTER JURNAL PENGABDIAN KEPADA MASYARAKAT Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer SISFO Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) JAST : Jurnal Aplikasi Sains dan Teknologi Indonesian Journal of Electrical Engineering and Computer Science Tri Dharma Mandiri: Diseminasi dan Hilirisasi Riset Kepada Masyarakat (Jurnal Pengabdian Kepada Masyarakat) Kohesi: Jurnal Sains dan Teknologi Journal of Information System and Application Development
Lailil Muflikhah
Fakultas Ilmu Komputer, Universita Brawijaya, Malang, Indonesia
Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Public Health Social Sciences Other

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Klasifikasi Risiko Hipertensi Menggunakan Metode Neighbor Weighted K-Nearest Neighbor (NWKNN) Bayu Laksana Yudha; Lailil Muflikhah; Randy Cahya Wihandika
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

Hypertension or called high blood pressure caused high risk of death in Indonesia. This could trigger sustainable effect to other diseases such as heart attack and kidney failure. According to WHO, as many as 30% of Indonesians are sufferers hypertension, Indonesian Hypertension Doctor Association also said that 76% of cases of hypertension can not diagnosed earlier and therefore hypertension is called a silent killer. The way to handling hypertension earlier is by early detection of hypertension in form of Early Alertness System (SKD). In this research will classified risk of hypertension based on medical record using Neighbor Weigted K-Nearest Neighbor (NWKNN) classification method. This method is the development of the KNN method. In NWKNN there is a weighting process in each class of hypertension risk. In this study, the classification of hypertension into 4 risks that is Normal, Pre Hypertension, Stage 1 and Stage 2. The results of this research shows that the NWKNN method is able to classify the hypertension risk well when tested on 100 training data, 25 testing data, K score=10, and E score=4 with accuracy result that reached 88%.
Penerapan Metode Average-Based Fuzzy Time Series Untuk Prediksi Konsumsi Energi Listrik Indonesia Yulian Ekananta; Lailil Muflikhah; Candra Dewi
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

With the ever-increasing amount of demand for consumption, for now the concept of forecasting is increasingly necessary as an important input to take planning and control decisions. Referring to the prediction activity, one of the techniques contained in the activity is the fuzzy time series technique. Fuzzy time series is an algorithm used for prediction. Prediction using this fuzzy time series works to store data in the past then generate new value in the show in the future. The resulting output is the result of the prediction. The advantage of time series method is not to require assumptions compared to other prediction methods. The method of fuzzy time series process is not too complicated so it is easy to develop. There are many types of methods using fuzzy time series in its development, one of them is the average-based fuzzy time series. This method is an average-based fuzzy time series method that is able to determine the effective interval length, so as to provide predictive results with a good degree of accuracy. In its implementation, this research applies method of average-based fuzzy time series for prediction of electric energi consumption. The data of electric energi consumption is chosen because it has the right characteristic that is included in the trend data class. In the test section performed using test while using the traning data as much as the total amount of data 43 produces AFER 9.24. While using the MAPE 14,27%. These results include good criteria.
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.
Klasifikasi Kualitas Susu Sapi Menggunakan Metode Support Vector Machine (SVM) Puspita Sari; Lailil Muflikhah; Randy Cahya Wihandika
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

Cow milk has a lot of animal protein and have benefit for children and whoever in process for grow up. Cow milk contains good essential amino acids. Malang Animal Health Laboratory as the unit executor in east java Animal Husbandry Department do a test in kesmavet for efforts to secure milk as a farm product with appropriate testing in suitable with the Indonesian National Standard (SNI). The classification of cow milk quality is still using organoleptic (smell, taste, color) that are linguistic, so that variable and parameter are uncertain and become themain obstacle of expert in determining good milk quality. To resolve this issue, this can be done with schizophrenia classification using support vector machine (SVM) algorithm, which SVM performace is more suitable than other classification methods. In this study there are 269 data that is divided into two data that is data training and data testing with three classification result, that is low, medium, and hight. The result in this paper get the best acuracy based ratio data 50%:50%, with Kernel RBF and λ (lambda) = 0,001, C (complexity) = 0,01, γ (gamma) =0,00001, maximum iteration = 30 and σ kernel RBF= 2. The average result of accuracy using SVM method in cow milk quality classification was 92.82% and highest accuracy was 94.02%.
Implementasi Metode Fuzzy Analytic Hierarchy Process (F-AHP) Dalam Penentuan Peminatan di MAN 2 Kota Serang Muhammad Fajri; Rekyan Regarsari Mardhi Putri; Lailil Muflikhah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 5 (2018): Mei 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Specialization programs are introduced as an effort to better lead students based on their talents, interests, and academic abilities. There are four groups of specialization in Madrasah Aliyah Negeri 2 Kota Serang, namely IPA, IPS, Language, and Religion. The specialization of IPA is for students who have a tendency in the science of certainty. IPS specialization is for students with social science tendencies. Language specialization is for students who have a tendency to speak the language. And religious interest is for students who have religious inclination. In the determination of student interest, MAN 2 Kota Serang uses five aspects of specialization such as the value of acceptance of new learners (PPDB), the value of national examination, the value of report cards, the results of psychological tests, and ask students. But in the determination of specialization there is no standardization of weighting in every aspect of specialization so that the results obtained are not maximal. Fuzzy Analytical Hierarchy Process (F-AHP) is able to overcome the weaknesses in criteria that have more subjective properties on the AHP method. Fuzzy logic itself is a logic that has a value of disguise between two values. In this study, the resulting accuracy is 76.67% with 30 test data for the determination of specialization in MAN 2 Kota Serang.
Penentuan Pemenang Tender Menggunakan Kombinasi K-Neareast Neighbor dan Cosine Similarity (Studi Kasus PT. Unichem Candi Indonesia) Surya Dermawan; Edy Santoso; Lailil Muflikhah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 5 (2018): Mei 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In decision of determination of auction in PT. Unichem Candi Indonesia is still manual. Due to this lack of knowledge in decision making. Data mining is also referred to as a series of processes to explore the added value of knowledge that has so far not been known manually from a data set. One of the technology that can be used for information system of tender winner determination is K-NN and cosine similarity which this technology become efficient and effective when applied to problem in PT. Unichem Candi Indonesia. The K-NN algorithm is a method that uses a supervised algorithm, where. The K value is the amount of nearest training data to the test data. From the test results the effect of the value of k obtained accuracy of 73% where the highest value, ie k = 2. Testing with the amount of trainee data and test data are balanced will affect the amount of accuracy that will be obtained. Based on the test results with the amount of training data and test data obtained an accuracy value of 83% where the highest value, ie k = 4. Keywords: Data Mining , k-nn Algorithm, Cosine Similarity.
Pemilihan Tim Bulutangkis Menggunakan Metode Fuzzy Tsukamoto dan AHP-SAW Randi Pratama Nugraha; Rekyan Regasari Mardi Putri; Lailil Muflikhah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 6 (2018): Juni 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Badminton Activity Unit Universitas Brawijaya is a unit that accommodates students who have interest and talent of badminton sport. It also has to hold selection for badminton athletes who enter through the scholarship path. Those athletes who pass the selection will be the candidates with the athletes in the unit into a team as the representatives of Universitas Brawijaya in certain competition. In selecting process, the candidates need to pass variety of criteria of qualificationt, they are the power of punch, physical stability, movement agility, speed, offense, defense, and readiness. Selection will be conducted using Fuzzy tsukamoto and AHP-SAW method. The Fuzzy Tsukamoto method is used to calculate the number of exercises a player should follow, then the number of these exercises will be used to get the player's readiness score. While the AHP-SAW method is used to determine the weight of each category of matches and the player's rank. The player who has the highest ranking will be selected to be the player candidate in the team. After implementation and testing, the result of single men category correlation is 0.839753, single women is 0.75736, men's double is 0.99079, female double is 0.98921, male tiriple is 0.99886, and triple women is 0.989426. From these results it can be concluded that the results of program and coach decisions are in line and have a positive correlation value and very strong.
Pengenalan Entitas Bernama untuk Identifikasi Transaksi Akuntansi Menggunakan Hidden Markov Model Rika Raudhotul Rizqiyah; Lailil Muflikhah; Mochammad Ali Fauzi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 7 (2018): Juli 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Accounting is a task which has an important role in supporting economic continuity, due to the recording of any business process that occurred was done in accounting. However, the recording of financial transactions in accounting for identification into journal is still done manually, so that required classification and extraction of information contained in the accounting transaction text to make it easier. Named Entity Recognition (NER) is the first step needed to perform information extraction. To solve this problem, named entity recognition done for identification of accounting transaction. In this research used method of Hidden Markov Model (HMM), because HMM can resolve labeling task and and known robustly in performing named entity recognition. The main process in this named entity recognition is divided into modeling process using Hidden Markov Model and decoding process using Viterbi Algorithm. In this research will be recognize 12 entities namely DATE, TITLE, PER, TRANS, EXP_MON, TYP_COMP, FIRST_ORG, SECOND_ORG, EXP_DATE, NO_DATE, MONTH and YEAR. Overall entity recognition with addition Laplace Smoothing and Regular Expression techniques produce a value of average precision, recall and f-measure consecutive 81.75%, 87.88%, and 82.39%.
Pemodelan Sistem Pakar Deteksi Dini Resiko Penularan HIV/AIDS Menggunakan Metode Dempster-Shafer Marine Putri Dewi Yuliana; Lailil Muflikhah; Rizal Setya Perdana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Human Immunodeficiency Virus (HIV) is a disease that attacks the body immune and until now still not found a drug that can cure it. People with HIV are often regarded as a disgrace that can cause psychological pressure on patients and families around him. It is this kind of thing which can then lead to the process of AIDS happening faster. Lack of information and ignorance of the spread of this virus resulted in increasing HIV patients. Fear will be regarded as a sufferer and do not want his privacy disturbed, most people are reluctant to ask this specialist about HIV. Therefore the need for a system that can be used as a support activity solving a problem. The knowledge to be represented in the expert system is full of uncertainty and disguise. One way to overcome the problem of uncertainty can be done by using Dempster Shafer method. The result obtained from 28 existing data has an accuracy of 78%. This indicate the system can be used in the expert system for early detection of HIV/AIDS.
Sistem Pakar Diagnosis Penyakit Pada Kambing Menggunakan Metode Dempster Shafer Agus Ardiansyah; Lailil Muflikhah; Suprapto Suprapto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Disease in goat cattle is an important thing to be considered, because it can cause losses for breeders can even cause the death of goat. Examination disease periodically are necessary to keep goats from disease. The investigation disease goats cannot be done by any person as between types of disease with this shows a tendency to having uncertainty. This makes it difficult for farmers to do early treatment and do not know what to do without an expert/veterinarian. Based on these problems, the authors create an expert system capable of diagnosing disease in goats as is usually done by an expert/veterinarian. This expert system uses the Dempster Shafer method. The Dempster Shafer method is a mathematical theory of evidence. The theory can provide a way of combining evidence from multiple sources and bringing in or providing a level of trust (represented by a trust function) which takes from all available evidence. Based on the results of the tests conducted on 32 test cases, obtained the average result of precision of 93%, 96% recall, and accuracy for f-measure of 94%
Co-Authors A. Bachtiar , Fitra Abdurrachman Bachtiar, Fitra Achmad Jafar Al Kadafi, Achmad Jafar Addin Sahirah, Rafifa Adinugroho, Sigit Agung Setiyoaji Agus Ardiansyah Agus Wahyu Widodo Agus Wahyu Widodo, Agus Wahyu Ahmad Nur Royyan Ahmad Wildan Attabi' Akbar Grahadhuita Al Kautsar, Prima Daffa Aldi Bagus Sasmita Aldino Caturrahmanto Anis Zubair, Anis Annisaa Amalia Safitri Aqmal Maulana Tisno Nuryawan Ardiza Dwi Septian Arief Andy Soebroto Ashidiq, Muhammad Fihan Aulia Herdhyanti Bachtiar, Harsya Baharudin B. Baharum Baihaqi, Galih Restu Bajsair, Fath' Hani Sarli Bayu Laksana Yudha Bayu Rahayudi Bening Herwijayanti Bintang, Tulistyana Irfany Brillian Ghulam Ash Shidiq Budi Darma Setiawan Candra Dewi Candra Dewi Daneswara Jauhari Daneswara Jauhari, Daneswara Darma Setiawan, Budi Darmawan, Riski Daud, Nathan Dewi, Buana Dhimas Wida Syahputra Dian Eka Ratnawati Dimas Joko Hariyanto Dimas Joko Haryanto Duwi Purnama Sidik Edy Santoso Edy Santoso Eni Hartika Harahap Eva Agustina Ompusunggu Faris Dinar Wahyu Gunawan Fatimah Az-Zahra, Adinda Feri Eko Herman Fitra Abdurrachman Bachtiar Fitrotuzzakiyah, Shafira Puspa Gessia Faradiksi Putri HANA RATNAWATI Hanggar Wahyu Agi Prayogo Haris, Asmuni Haryanto, Dimas Joko Hinandy Nur Anisa Hoar, Wilhelmina Sonya Ichsan Achmad Fauzi Iftinan, Salsa Nabila Imam Cholissodin Imam Cholissodin Imam Cholissodin Imam Cholissodin Indriati Indriati Indriati Indriati Issa Arwani Kautsar, Ahmad Izzan Khairunnisa, Alifah Ksatria Bhuana Kukuh Bhaskara Kukuh Haryobismoko Kurnianingtyas, Diva Laily Putri Rizby Luqyana, Wanda Athira Luthfi Afrizal Ardhani M. Ali Fauzi M. Tanzil Furqon, M. Tanzil Marine Putri Dewi Yuliana Marji . Marji Marji Maulana, Muhammad Taufik Maulidiya, Afifulail Maya Nur Muh Arif Rahman Muh Hamim Fajar Muh. Arif Rahman Muhammad Abduh Muhammad Fajri Muhammad Ferian Rizky Akbari Muhammad Rafif Al Aziz MUHAMMAD SYAFIQ Muhammad Tanzil Furqon Muhammad Wafiq Mukhrodi, Dillah Lyra Nashi Widodo Nisa, Lisa N. Novanto Yudistira Nurfansepta, Amira Ghina Nurhidayati Desiani Nurul Dyah Mentari Nurul Hidayat Nurul Hidayat Olivia Bonita Puji Indah Lestari Puspita Sari Putra Pandu Adikara Putri, Rania Aprilia Dwi Setya Rachmad Indrianto Rachmatika, Isnayni Sugma Rafifah Nawawi, Danisha Ramadhan, Galang Gilang Randi Pratama Nugraha Randy Cahya Wihandika Ratih Kartika Dewi Rekyan Regarsari Mardhi Putri Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Rendi Cahya Wihandika Rheza Raditya Andrianto Ria Ine Pristiyanti Rika Raudhotul Rizqiyah Riski Darmawan Riyanarto Sarno Rizal Setya Perdana Rizal Setya Perdana Robbiyatul Munawarah Rowan Rowan Rusydi Hanan, Muhammad Satrio Hadi Wijoyo Setiana, Maya Setya Perdana, Rizal Shalsadilla, Shafatyra Reditha Sholeh, Mahrus Sukma, Lintang Cahyaning Supraptoa Supraptoa Surya Dermawan Susanto, Dominicus Christian Bagus Sutrisna, Naufal Putra Sutrisno Sutrisno Sutrisno, Sutrisno Syafruddin Agustian Putra Syarif Hidayatulloh Tahtri Nadia Utami Tibyani Tibyani Tirana Noor Fatyanosa, Tirana Noor Tri Fadilah, Ghina Utaminingrum, Fitri Vianti Mala Anggraeni Kusuma Vidya Capristyan Pamungkas Wahyu Rizki Ferdiansyah Wardana, Dzaky Ahmadin Berkah Warut, Gregorius Batara De Wibowo, Dhimas Bagus Bimasena Wijaya, Nicholas Yobel Leonardo Tampubolon Yogi Suwandy Yulian Ekananta Yunita, W. Lisa Zakiyyah, Rizka Husnun Zanna Annisa Nur Azizah Fareza