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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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Analisis Sentimen Masyarakat terhadap Uji Coba LRT Jakarta Menggunakan Improved K-Nearest Neighbor dan Information Gain Mahendra Okza Pradhana; Indriati Indriati; Sigit Adinugroho
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 6 (2020): Juni 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Current transportation development system has giving easiness for society to moving from place to another places. One of quite new public transportation is Light Rail Transit (LRT). LRT or light railroad have an opportunity to held public trial access for free just by registering yourself in LRT Jakarta website. For improving and maximize LRT Jakarta services, they have social media account where people may give feedback and assessment. One of way that could be done is by sentiment analysis to find out whether the society likes the services provided by LRT Jakarta. This study is using the Improved KNN as a classification method to determine people sentiment coupled with Information Gain to select features used during the classification process. The process of sentiment analysis includes data collection, text preprocessing that produces clean data, then weighting the terms with tf idf followed by feature selection using Information Gain. The next step is classification with Improved KNN using the features of the previous selection. The data used are primary data sourced from three social media namely Youtube, Twitter and Facebook. The results of this study are the best f-measure obtained when k = 11 using a 100% threshold or the whole term used that is equal to 85.51% with an average computational time calculated from 5-fold of 0.4647 minutes.
Pengenalan Jenis Kelamin dan Rentang Umur berdasarkan Suara menggunakan Metode Backpropagation Neural Network Avisena Abdillah Alwi; Putra Pandu Adikara; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 7 (2020): Juli 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Technology in the field of speech recognition is currently experiencing rapid progress. One technology that utilizes speech recognition is virtual assistants such as Google Assistant, Cortana, and Alexa. In order to improve the quality of communication between virtual assistants and humans, virtual assistants need to know who their communication opponents are. One way is by knowing the gender and age. Recognition of gender and age range based on voice is one part of speech recognition. Audio cannot be directly classified, therefore there is a need for feature or feature extraction, feature extraction that can be used include Mel-Spectogram, Mel Frequency Cepstral Coefficients (MFCC), and Chroma- Short-Time Fourier Transform. Artificial neural network architecture is able to classify it, one of the methods is Backpropagation. From the tests conducted by gender classification and age range with a dataset from Mozilla Common Voice, the accuracy is less good, that is 0.18357. From the test results it is necessary to do additional testing, namely testing the dataset. When testing the dataset for gender classification alone, the accuracy of classification with the Mozilla Common Voice dataset is 0.62504, while the accuracy of the classification with the dataset from Free ST American English Corpus gets 0.9349. From the tests conducted it was concluded that the use of the Mozilla Common Voice dataset was less recommended for gender and / or age recognition.
Analisis Sentimen pada Ulasan Pengguna MRT Jakarta Menggunakan Metode Neighbor-Weighted K-Nearest Neighbor dengan Seleksi Fitur Information Gain Firda Oktaviani Putri; Indriati Indriati; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 7 (2020): Juli 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The existence of the MRT Jakarta is expected to reduce the number of private transportation uses, which causes the congestion rate in the Jakarta area to continue to increase. Reviews from MRT Jakarta users help MRT Jakarta in improving its services, because good service quality can attract people to use MRT as public transportation for traveling. However, at this time, MRT Jakarta's official social media accounts had not yet found a feature to sort reviews between positive and negative reviews. If this is done manually it will take time, therefore it is necessary to carry out an automation process in the selection of these reviews. This automation process is known as sentiment analysis. In this study, the sentiment analysis system uses a combination of the Neighbor-Weighted K-Nearest Neighbor (NWKNN) classification method with the Information Gain feature selection. Tests conducted in this study using 5-Fold Cross Validation. The test results reach the optimal point at the 5th Fold, when the k value = 100, the exponent value = 2, and the threshold value for feature selection = 100% (without feature selection and without using stopword removal), with values of precision, recall, f- measure, and accuracy is 1; 0.94; 0.97; and 0.97.
Penerapan Algoritma Decision Tree C4.5 Untuk Deteksi Fraud Pada Kartu Kredit dengan Oversampling Synthetic Minority Technique (SMOTE) Ludgerus Darell Perwara; Fitra Abdurrachman Bachtiar; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 8 (2020): Agustus 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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In today's technological developments, credit cards are seen as an easy and practical way of making transactions, because apart from being easy to use transactions with credit cards only require a few requirements. However, the increasing use of credit cards has resulted in criminal acts that harm both customers and banks. Data mining is seen as the right method to solve this problem, so this research will use the Decision Tree C4.5 method to detect fraud in credit card transactions. Because the occurrence of fraud on every transaction is rare and there are more normal transactions, this study will also add to the SMOTE oversampling method that can create synthetic fraud data with the aim of balancing class. The results of this study produce an accuracy value of 78%, a precision value of 89.65%, a recall value of 85.71% and an f-measure of 87.64% with an N value of 500% in SMOTE and a depth value of the Decision Tree C4. 5 = 15. So, it can be concluded that the implementation of Decision Tree C4.5 in the case of detecting fraud in credit card transactions is best done by oversampling SMOTE.
Temu Kembali Informasi Berita Berbahasa Indonesia menggunakan Metode BM25F Puteri Aulia Indrasti; Indriati Indriati; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 9 (2020): September 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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The development of digital technology has a positive impact on information media such as news. Online news sites have become one of the most trusted source of information for conducting news searches. Finding news information online enables users to search directly in the search column of a news site. Online news has a structure or fields such as title, content, and additional tags. However, this will cause problems if many users searches are following the structure other than the title and content of the news which should have a more appropriate portion. Indonesian news information retrieval system is needed to solve this problem. Using methods that can solve the problem of structured documents. BM25F method is a ranking method that can consider the structure or field in a document. Tests carried out on BM25F free parameters get the best results at boost title = 5, content = 1, bc = 0,75, and k1 = 1,2. And the BM25F ranking test using precision @ k and r-precision in 600 news documents for 12 queries obtained the best average precision @ k = 0,95 when k = 5 and the best r-precision value = 1.
Klasifikasi Dokumen Pengaduan Sambat Online menggunakan Metode Multinomial Naive Bayes dan N-Gram Feri Angga Saputra; Indriati Indriati; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 9 (2020): September 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In an effort to utilize technology in public services, the Malang Office of Communication and Information has launched the SAMBAT Online web application (Integrated Questions Society Application System) to accommodate criticism, suggestions, and complaints given by the public. To improve time efficiency and make it easier for admins to classify incoming complaints the text classification method is needed. The Naive Bayes Multinomial method is widely used because this algorithm is very simple and efficient. But the Naive Bayes Multinomial algorithm has the disadvantage of having dependence on the amount of data. To improve these deficiencies researchers used a support method as feature extraction, N-gram. The test results using the Multinomial Naive Bayes method and N-gram show that the unigram n-gram can provide the highest accuracy rate of 88.23% with an average overall accuracy of 80.88% with an f-measure value of 0,8013.
Klasifikasi Pengaduan Pelayanan Dispendukcapil Kota Malang Menggunakan Metode Naive Bayes dan Seleksi Fitur Glasgow-II Choirul Anam; Indriati Indriati; Marji Marji
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 9 (2020): September 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The service of each service will never escape from imperfections including the Population and Civil Registry Service (DISPENDUKCAPIL). Service improvement aims to create a sense of comfort and increase satisfaction and trust towards DISPENDUKCAPIL employees for the residents of Malang City. The categories or types of complaints that often go into DISPENDUKCAPIL are complaints on issues of Identity Card (KTP), Family Card (KK), deed (birth, death, and marriage), moving or coming letters. The categorization of various types of service complaints that have been sent to DISPENDUKCAPIL can be done using classification. Classification of service complaints is done using the Naive Bayes method and the Glasgow-II Feature Selection. The process starts from text preprocessing, term weighting, Feature Selection, Naive Bayes training, and Naive Bayes testing. Based on the results of tests conducted using the Naive Bayes method and the Glasgow-II Feature Selection, values ​​of accuracy, precision, recall were 87.5%, 85.1%, 88.075% and an average accuracy of 81.25%. Whereas by using the Naive Bayes method without the Glasgow-II Feature Selection the accuracy, precision, recall values ​​were 84.375%, 83.1%, 81.5625% and the average accuracy was 79.99%. So, that the use of the Naive Bayes method and the Glasgow-II Feature Selection are able to provide better results.
Klasifikasi Jenis Kelamin Pengguna Twitter dengan menggunakan Metode BM25 dan K-Nearest Neighbor (KNN) Annisa Selma Zakia; Indriati Indriati; Marji Marji
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 10 (2020): Oktober 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Twitter is a microblogging social network where one can write up to 280 characters in one tweet. Indonesia emerged as the fifth largest country in terms of Twitter users. Seeing how many Twitter users in Indonesia can certainly be used by companies in creating new business strategies to serve their customers, but some social account users objection if they have to reveal their identities. These problems can be solved by developing a system for classifying based on tweets from users, this system is certainly useful because it saves time. The system is designed using the BM25 method for calculating similarities between documents and KNN for classifying data. the system used 1000 documents, then the document is tested with K-Fold Cross Validation using K = 10 so that 900 training documents and 100 testing documents are obtained on each K. The next test is about neighbor values, neighbor values used are 1, 3, 5, 7, 10, 20, 30, 40 and 50, the test results show that the optimal neighbor value is k = 3. At k = 3 the value of accuracy, precision, recall and F-Measure of the average Cross Validation 10 fold are 68.6%, 67.63%, 71.52% and 69.34%.
Klasifikasi Severity Bug menggunakan Support Vector Machine dan Oversampling SMOTE-NC Titus Christian; Fitra Abdurrachman Bachtiar; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 13 (2020): Publikasi Khusus Tahun 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Untuk dipublikasikan di Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK)
Klasifikasi Review Produk Kecantikan Pada Aplikasi Sociolla Menggunakan Algoritme Modified K-Nearest Neighbor (MK-NN) dengan Pembobotan BM25 Alfita Nuriza; Indriati Indriati; Nurul Hidayat
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 10 (2020): Oktober 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Beauty products have become one of the many things that cannot be separated from women because of the demands to look beautiful and attractive. These products offer their advantages, there are many beauty products on the market, ranging from skin care and cosmetics from various types and brands. These products have advantages, but not all products suitable for the users needs. This is something that consumers must pay attention to before buying. Other than that, the number of beauty products that are closely related to opinions about certain products in accordance with the parameters given by consumers such as strengths, weaknesses, quality and other parameters, this is what is used as a reference. One electronic trading platform that provides beauty products is Sociolla. Not only sell beauty products, on this platform there are also reviews from consumers. Reading all these reviews in full will take up a lot of time, whereas if you only read a little, the resulting evaluation will be biased. To overcome these problems the classification of the existing review will be classified into 2 classes, namely positive and negative classes. In this study the authors used the Modified K-Nearest Neighbor (MK-NN) algorithm with BM25 as a weighting. The data used were 500 data which were divided into two, positive and negative. From the evaluation results of the test with 5-fold cross validation, the highest average values ​​of accuracy, precision, recall, and f-measure were 51.00%, 50.90%, 52.61%, and 51.70% at the time k = 11.
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