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All Journal Journal of Environmental Engineering and Sustainable Technology JURNAL PENGABDIAN KEPADA MASYARAKAT Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Indonesian Journal of Electrical Engineering and Computer Science Community Empowerment Jurnal Sistem Informasi, Teknologi Informasi, dan Edukasi Sistem Informasi (JUST-SI)
Indriati Indriati
Fakultas Ilmu Komputer, Universita Brawijaya, Malang, Indonesia
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Mechanical Engineering Public Health Social Sciences

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Implementasi Named Entity Recognition Pada Factoid Question Answering System Untuk Cerita Rakyat Indonesia Yulia Kurniawati; Indriati Indriati; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 9 (2018): September 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Regional legend or folklore is a story that developed among the various cultures of Indonesia that have been down and down inherited. Folklore is a story of the past that is believed to be the true event, usually the folktale is the origin of a place. The lack of an attractive means of introducing folklore is one of the reasons for the lack of interest of Indonesian folklore. In addition, the level of understanding of children who are still less than adults cause them to easily forget the story of the people when they are less understood to the story of the people of Indonesia. This study aims to facilitate the children in understanding the story. Therefore, the researcher makes question answering system by using Named Entity Recognition method. The classification of named entity in this research using naive bayes method. In this research used four named entity to recognize the next word will be candidate for answers such as product, person, location and none. Where none is an entity. In addition, the type of question that can be asked on the question answering system is Factoid Question is a question that the answer is a short and solid fact not a description. The data used are five folk stories of Indonesia obtained from the internet and the classification of Named Entity has a precision value of 34.22%, the accuracy of NE classification of 64.65% and recall 13.13% while for question answering accuracy system obtained accuracy of 16.7%.
Analisis Sentimen Review Aplikasi Mobile Dengan Menggunakan Metode Modified K Nearest Neighbour (MK-NN) Ahmad Nur Royyan; Indriati Indriati; Lailil Muflikhah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 10 (2018): Oktober 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Mobile Applications is a program that runs on mobile devices like Handphone. Especially Smartphone that can accommodate many a program which certainly serves to facilitate users in undergoing their activities. Mobile Banking is required by its users to make transactions that can be done at the ATM. With this application, users do not need to come to the ATM to make transfers or check balances at ATMs. Because it can be done through the Smartphone he has. This is an opportunity for application developers to create Mobile Banking applications that user needs. In the development of this application, They are need the input from users for applications developed in accordance with the needs of its users. Therefore, it takes a method that is able to sort out the sentiments (comments) from the user. Whether the sentiment is included in positive or negative sentiments. In this study, the author used Modified K Nearest Neighbors (MKNN) as the method used to sort the sentiments. The highest accuracy value obtained is 76% for the value of K = 11 with 400 dataset. For 200 training dataset, the highest accuracy is 69% (K=3). And 70% for 300 training dataset and K=3.
Penerapan Algoritme Fuzzy K-Nearest Neighbor (FK-NN) Pada Pengklasifikasian Penyakit Kejiwaan Skizofrenia Tania Oka Sianturi; Muhammad Tanzil Furqon; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 10 (2018): Oktober 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

One of the psychiatric diseases that affects many Indonesians is schizophrenia. Schizophrenia causes a person to sustain delusions, hallucinations, chaotic thoughts, and behavioral changes. According to Riset Kesehatan Dasar (Riskesdas) in 2013, prevalence of schizophrenia is 1.7% per 1000 people or about 400,000 people. For very wide territory of Indonesia with total population around 237 million, the number of psychologists or psychiatrists about 616 people is still very small. With this limitation, a system that can be used to assist paramedics in diagnosing and classifying psychiatric illnesses of schizophrenia. In this study applied fuzzy K-nearest neighbor algorithm to diagnose and classify psychiatric illness of schizophrenia. Types of schizophrenia used in this study are paranoid schizophrenia, hebephrenic schizophrenia, catatonic schizophrenia, undifferentiated schizophrenia, and simple schizophrenia. The classification process consists of three processes are the fuzzy initialization process, the K-nearest neighbor algorithm process, and the fuzzy K-nearest neighbor algorithm process. The testing consists of the effect of K value and the effect of K-Fold. Based on the test results on the K value, obtained the highest accuracy of 38.33% at K=5. The effect of K-Fold test results obtained the highest average accuracy of 34.17% at K-Fold= 10.
Analisis Sentimen Pada Ulasan "Lazada" Berbahasa Indonesia Menggunakan K-Nearest Neighbor (K-NN) Dengan Perbaikan Kata Menggunakan Jaro Winkler Distance Yane Marita Febrianti; Indriati Indriati; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 10 (2018): Oktober 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The development of an information technology currently carries a considerable impact against the pattern of life one on purchasing power. The current purchasing power are more likely to shop online because it's considered easier. But, how does a consumer know if the items to be purchased good or otherwise. Therefore it appears there is a review or comment on any goods sold. Review on items bring considerable influence against the purchasing power of consumers to know the quality of the goods, does not be surprised if a review into one of the main goals being viewed by consumers after the price. However, not all reviews provided the consumers can be understood by other consumers due to use the word is abbreviated, it use modern languages, in typing letters, the researcher proposes the creation of a system Analysis of Sentiment on the Reviews “Lazada” Berbahasa Indonesia Using the K-Nearest Neighbor (K-NN) and Repair Word Using Jaro Winkler Distance. Testing based on the value of precission, recall, and accuracy at each analysis sentiment without repair word, or with repair word. The test result with good accuracy value is present on the analysis sentiment with repair word is 76 %, with value of precission 0,76, and recall 1.
Pengelompokan Artikel Berbahasa Indonesia Dengan Menggunakan Reduksi Fitur Information Gain Thresholding Dan K-Means Novia Agusvina; Indriati Indriati; Nurudin Santoso
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 10 (2018): Oktober 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The increasing number of articles spread on the internet site, making it difficult for users to find the desired article. One of the online article service providers is Kompas.com. To face the competition among mass media industry, Kompas.com step is to provide features that facilitate the user, such as features related article recommendations. However, in its application Kompas.com is still less than the maximum so it remains inferior to other online mass media. In this study, researchers implemented a method of reducing the features of Information Gain Thresholding and K-Means to create a group of related articles. The purpose of this study is to improve the system related articles from Kompas.com. In implementing the use of java language. In the early stages of preprocessing to reduce the disturbance in the data, then the feature reduction is done to reduce the features used for faster process, then weighted as the basis for calculating the distance between documents, after finding the distance of the initial distance or centroid, grouping can be done. The results show that the clustering of articles using Information Gain Threshold and K-Means is good enough, has criteria of silhouette coefficient of 0.9595 and a purity measure of 0.75 with 3 clusters and 0.04 threshold limit, this conclude that it gives better purity compared to without feature reduction.
Implementasi Metode Improved K-Means untuk Mengelompokkan Dokumen Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Muhammad Abdurasyid; Indriati Indriati; Rizal Setya Perdana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 10 (2018): Oktober 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Journal of Information Technology and Computer Science Development (J-PTIIK) is a scientific journal in the field of computer that contains scientific writings of research results FILKOM Brawijaya University students that published periodically. J-PTIIK is a journal document that has journal topics that are in the field of information technology and computer science. At this time J-PTIIK is clustered by volume archive and published journal number. To facilitate the identification of journal topics contained in J-PTIIK, J-PTIIK documents can be clustered based on similarity of topics contained in J-PTIIK. J-PTIIK documents clustering is made using improved k-means method. The improved k-means method is the unsupervised clustering techniques with the initial centroid determination obtained by combining the optimization method of distance and density. Document pre-processing and formation of vector space model to perform term weighting is done first before clustering the J-PTIIK documents. Based on the evaluation results, J-PTIIK documents clustering obtained an optimal silhouette coefficient by 0.026574 at k = 19 and α = 0.50. Optimal purity test results obtained by 0.738197 at k = 23 and α = 0.50. The research result shows that the use of improved k-means method has better silhouette coefficient than k-means method, with average value of silhouette coefficient at improved k-means method by 0.016457654 and k-means method by 0.011820563.
Klasifikasi Spam Pada Twitter Menggunakan Metode Improved K-Nearest Neighbor Dea Zakia Nathania; Indriati Indriati; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 10 (2018): Oktober 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Twitter is a service application that is popular because it can be used to interact and communicate in everyday life. A lot of various new types of automation software increases to disseminate information immediately. Twitter does not strictly check the automation tweet, therefore there is no prevention of the use of bot on a regular basis. Low restriction of the use of automation services on Twitter led to the emergence of market Spam-as-a-Service consisting of counterfeiting program, abridgement ad-based on service and sales account. Each of these services allows spammers to do the spam deployment process by using automation tweet services. So it is necessary to do a research on the classification of the tweet to know the type of category is included in the category of spam or not spam. Spam classification process begins with the preprocessing consists of several stages, namely; cleansing, case folding, tokenization, filtering and stemming. The next step are process of term weighting, until the process of classification using Improved K-Nearest Neighbor method. The results obtained on the basis of implementation and testing research of the classification of Spam on Twitter produces an average Precision of 0.8946, Recall of 0.9405, F-Measure of 0.9155 and results accuracy of 89.57%. Where is the number of documents, a comparison or balance the proportion of training data and the determination of k-values that are used too well or whether the process of classification of the document.
Penerapan Algoritme Modified K-Nearest Neighbour Pada Pengklasifikasian Penyakit Kejiwaan Skizofrenia Anjelika Hutapea; Muhammad Tanzil Furqon; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 10 (2018): Oktober 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Schizophrenia is a disease that has a soul crack or a splitting of personality. Problems of mental disorder almost in all countries in the world. Schizophrenia has 5 types: Paranoid, Hebephrenic, Catatonic, Unspecified and Simplex.The similarity of symptoms causes the paramedic difficulty to determine the class of Schizophrenia. Therefore, a system that aims to Schizophrenia classification by applying one of the classification method Modified K-Nearest Neighbor (MKNN). The system will perform the step by calculating the distance of assymetric binary, the calculation of the validity value and weight voting value in order to get the final result that will be used to determine the classification based on the value of K that has been determined. The testing of this system consist of testing the effect of K value and testing the influence of K-Fold value. The result of testing the effect of K value gives the greatest accuracy equal to 37,045% at K=7 and K-Fold=10. The result of testing the effect of K-Fold value gives the greatest accuracy of 28,4462% at K-Fold=5.
Implementasi Association Rule Mining Untuk Menentukan Menu Paket Makanan Dengan Algoritma FIN Menggunakan Nodesets (Studi Kasus R.M. Lesehan Nova Sragen) Riski Nova Saputra; Muhammad Tanzil Furqon; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 10 (2018): Oktober 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Restaurant of Lesehan Nova Sragen has a variety of menu items are quite a lot of 116 food menu items and 44 drink menu items. Due to the high variations of menu items makes consumers take longer to select order menu items. Author provides solutions to restaurant's owner to create a menu package based on consumer history in selecting menu items. So as to improve restaurant service to consumers. To create package menu author using FIN algorithm. Fin algorithm is used to perform mining frequent itemset to sales transaction data. Fin algorithm is implemented on automatic package menu builder system. Based on test results, minimum value of support = 11 has resulted in proportional package menu variation ,and has been representative with consumer choice. Variation number of resulting package menu is 6 variations of package menu.
Implementasi Fuzzy K-Nearest Neighbour (FK-NN) Untuk Pemilihan Keminatan Mahasiswa Teknik Informatika (Studi Kasus : Program Studi Teknik Informatika Fakultas Ilmu Komputer Universitas Brawijaya) Dhony Lastiko Widyastomo; Indriati Indriati; Rizal Setya Perdana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 11 (2018): November 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Concentration selection is one of few steps for a students to finish their studies. Informatics programee have 4 concentration consist of Artificial Inteligent(AI), Software Engineering (SE), Network and Game. Unfortunately because the limited and many internal problems from the students causing some problem for the concetration selection. To solve the problem of selection, a system who can give a classification is needed to give the solution. A classification for concentracion selection uses fuzzy k-nearest neighbor for its method. The method works with calculate the number of K value to Process the classification of 4 study concentration and resulting the recomendation class of concentration class based on the student data. Based on the research of study using 200 data of the students of Informatics engineering, from 2011 to 2013, the biggest accuracy was produced by K value=3 and have 87,5% accuracy. While the lowest precentages of accuracy was produced by K value=10 with the averages of 67,5% accuracy.
Co-Authors Abdul Azis Adjie Sumanjaya Abel Filemon Haganta Kaban Achmad Arwan Achmad Burhannudin Achmad Ridok Ade Wahyu Muntizar Adella Ayu Paramitha Adinugroho, Sigit Afif Musyayyidin Aghata Agung Dwi Kusuma Wibowo Agus Wahyu Widodo Ahmad Afif Supianto Ahmad Fauzan Rahman Ahmad Nur Royyan Aisyah Awalina Alaikal Fajri Nur Alfian Alfita Nuriza Alvin Naufal Wahid Anak Agung Bagus Arisetiawan Andhika Satria Pria Anugerah Andre Rino Prasetyo Anggara Priambodo Jhohansyah Anjelika Hutapea Annisa Selma Zakia Ardhimas Ilham Bagus Pranata Arief Andy Soebroto Arifin Kurniawan Arinda Ayu Puspitasari Arthur Julio Risa Ashshiddiqi Arya Perdana Avisena Abdillah Alwi Ayu Tifany Novarina Bagus Abdan Aziz Fahriansyah Bayu Rahayudi Benita Salsabila Berlian Bidari Ratna Sari B Beta Deniarrahman Hakim Billy Sabilal Binti Najibah Agus Ratri Binti Robiyatul Musanah Brian Andrianto Budi Darma Setiawan Candra Ardiansyah Candra Dewi Chandra Ayu Anindya Putri Choirul Anam Daneswara Jauhari Dea Zakia Nathania Deny Stevefanus Chandra Deri Hendra Binawan Desy Andriani Desy Wulandari Dewi Syafira Dhaifa Farah Zhafira Dhony Lastiko Widyastomo Diajeng Ninda Armianti Dian Eka Ratnawati Dina Dahniawati Dinda Adilfi Wirahmi Durrotul Fakhiroh Dwi Suci Ariska Yanti Dyah Ayu Wulandari Edo Ergi Prayogo Edy Santoso Eka Putri Nirwandani Enggar Septrinas Erma Rafliza Fajar Pradana Faradila Puspa Wardani Fardan Ainul Yaqiin Febriana Ranta Lidya Febrina Sarito Sinaga Fera Fanesya Ferdi Alvianda Feri Angga Saputra Firda Oktaviani Putri Firda Priatmayanti Firhad Rinaldi Saputra Fitra Abdurrachman Bachtiar Frans Agum Gumelar Galuh Fadillah Grandis Ghiffary Rizal Hamdhani Guedho Augnifico Mahardika Hilmy Khairi Idris I Made Budi Surya Darma Imam Cholissodin Indah Mutia Ayudita Indriya Dewi Onantya Inosensius Karelo Hesay Jeffrey Junior Tedjasulaksana Jeowandha Ria Wiyani Joda Pahlawan Romadhona Tanjung Junda Alfiah Zulqornain Katherine Ivana Ruslim Khaira Istiqara Khalisma Frinta Kornelius Putra Aditama Ksatria Bhuana Lailil Muflikhah Liana Shanty Wato Wele Keaan Liana Shinta Dewi Liana Shinta Dewi Linda Pratiwi Ludgerus Darell Perwara Lusiyana Adetia Isadi Luthfi Mahendra M. Aasya Aldin Islamy M. Ali Fauzi Mahdarani Dwi Laxmi Mahendra Okza Pradhana Mardji Mardji Marinda Ika Dewi Sakariana Marji Marji Mentari Adiza Putri Nasution Merry Gricelya Nababan Moch Bima Prakoso Mochamad Havid Albar Purnomo Mohamad Alfi Fauzan Mohammad Birky Auliya Akbar Mohammad Fahmi Ilmi Mohammad Imron Maulana Muhammad Abdurasyid Muhammad Fauzan Ziqroh Muhammad Hakiem Muhammad Mauludin Rohman Muhammad Reza Ravi Muhammad Tanzil Furqon Muhammad Yudho Ardianto Nadya Oktavia Rahardiani Nana Nofiana Nanda Ajeng Kartini Nanda Cahyo Wirawan Ni Made Gita Dwi Purnamasari Ni Made Gita Dwi Purnamasari Nihru Nafi' Dzikrulloh Nirmala Fa'izah Saraswati Novanto Yudistira Novia Agusvina Nur Intan Savitri Bromastuty Nurdifa Febrianti Nurina Savanti Widya Gotami Nurudin Santoso Nurul Hidayat Nurul Muslimah Pengkuh Aditya Prana Prais Sarah Kayaningtias Pratitha Vidya Sakta Puteri Aulia Indrasti Putra Pandu Adikara Putri Rahma Iriani Putu Amelia Vennanda Widyaswari Putu Rama Bena Putra Rachmad Ridlo Baihaqi Rahma Chairunnisa Rahmat Arbi Wicaksono Rakhman Halim Satrio Randy Cahya Wihandika Ratih Karika Dewi Ratna Tri Utami Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Rien Difitria Rifki Akbar Siregar Rilinka Rilinka Riska Dewi Nurfarida Riski Nova Saputra Riyant Fajar Riza Cahyani Rizal Aditya Nugroho Rizal Setya Perdana Rizaldy Aditya Nugraha Rizky Haqmanullah Pambudi Rizky Nur Ariyanti Sabrina Hanifah Salsabila Rahma Yustihan Sigit Adinugroho Sinta Kusuma Wardani Siti Robbana Sutrisno Sutrisno Swandy Raja Manaek Pakpahan Tania Malik Iryana Tania Oka Sianturi Tasya Agiyola Thio Marta Elisa Yuridis Butar Butar Titus Christian Vera Rusmalawati Wayan Firdaus Mahmudy Yane Marita Febrianti Yobel Leonardo Tampubolon Yudha Ananda Kresna Yudha Irwan Syahputra Yudha Prasetya Anza Yuita Arum Sari Yulia Kurniawati Zahra Swastika Putri