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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 Jaringan Saraf Tiruan Backpropagation untuk Memprediksi Jumlah Penduduk Miskin di Indonesia dengan Optimasi Algoritme Genetika Arthur Julio Risa Ashshiddiqi; Indriati Indriati; Sutrisno Sutrisno
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

Poverty is a common issues encountered by every country, and Indonesia is one of them. The escalation of the poor occurred almost every year. According to Indonesia Statistic Bureau (Badan Pusat Statistik) using population indicator based on their monthly expense below the line of poverty can be categorized as poor people. The increasing amount of the poor can trigger criminality, that is because those individuals will do anything to make ends meet. By predicting the amount of the poor, hopefully the government or any related institution can help decrease poverty and unemployment rate in Indonesia. Artificial neural network backpropagation is one of the method that can be used to make predictions. Weight and bias in backpropagation's training optimized using genetic algorithm to obtain more optimal results. In this artificial neural network backpropagation research method that the weight training optimized using genetic algorithm generate 8.744579% AFER points.
Identifikasi Tweet Cyberbullying pada Aplikasi Twitter menggunakan Metode Support Vector Machine (SVM) dan Information Gain (IG) sebagai Seleksi Fitur Ni Made Gita Dwi Purnamasari; Mochammad Ali Fauzi; Indriati Indriati; Liana Shinta Dewi
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

Cyberbullying is one of the actions that violate the ITE Law where the crime is committed on social media applications such as Twitter. This action is difficult to detect if no one is reporting the tweet. Cyberbullying tweet identification aims to classify tweets that contain bullying. Classification is done using Support Vector Machine method where this method aims to find the dividing hyperplane between negative and positive class. This study is a text classification where more data is used, the more features are produced, therefore this research also uses Information Gain as feature selection to select features that are not relevant to the classification. The process of the system starts from text preprocessing with tokenizing, filtering, stemming and term weighting. Then perform the information gain feature selection by calculating the entropy value of each term. After that perform the classification process based on the terms that have been selected, and the output of the system is identification whether the tweet is bullying or not. The result of using SVM method is accuracy 75%, precision 70.27%, recall 86.66% and f-measure 77.61% on experiment iterMax value = 20, λ = 0.5, γ = 0.001, ε = 0.000001, and C = 1. The best threshold of information gain is 90%, with accuracy 76.66%, precision 72.22%, recall 86.66% and f-measure 78.78%
Peringkasan Teks Otomatis Menggunakan Metode Maximum Marginal Relevance Pada Hasil Pencarian Sistem Temu Kembali Informasi Untuk Artikel Berbahasa Indonesia Nirmala Fa'izah Saraswati; 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

Information retrieval is a system that displays documents according to the query given by user. However, the information retrieval system provide a lot of search results, when we are looking for a desired information is not possible to open one by one documents generated by system. Text Summarization can be done to get an overview of information from a document, so that user get the right documents. One method to summarize text is Maximum Marginal Relevance (MMR). Maximum Marginal Relevance (MMR) is one of the extractive summary methods used to summarize single or multi document documents. MMR summarizes documents by computing the similarity between sentences and sentences, and between sentences and queries. Based on the test results, it obtain best Precision at k in the fifth rank of 0.96 for information retrieval system results. The best test results from an average precision, recall, f-measure and accuracy respectively 0.70, 0.75, 0.70 and 74.17. The used method is good enough to get the relevant documents and obtain summaries based on the title corresponding to the contents of the document.
Sistem Pencarian Jurnal Ilmiah Cross Language dengan Metode Vector Space Model (VSM) Indah Mutia Ayudita; Indriati Indriati; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Scientific journals are periodical publications that contain scientific papers with data and information written in accordance with the rules of scientific writing. Scientific journals used widely as a reference to make a new research or continue the previous research. As the usage is growing, scientific journals also easier to find digitally and available in a digital library such as Science Direct and IEEE, but the searching process is still limited to Monolingual Information Retrieval, in which the search results have the same language as the query inputted, even though the relevant documents also available in other languages. This research is done to observe the result of implementing Cross Language Information Retrieval that can do the searching process in one language for the input and retrieved document in two languages. The final result is 8 out of 10 queries have a higher precision up to 74,5% and recall up to 41,5%. Generally, system can retrieved the relevant documents in average for 84%.
Pemilihan Alternatif Tanaman Obat Terhadap Penyakit Hipertensi Menggunakan Metode Analytical Network Process (ANP) dan Simple Multi Attribute Rating Technique (SMART) Linda Pratiwi; Indriati Indriati; Ahmad Afif Supianto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Medicinal plants contain active substances aims for healing and preventing of various types of diseases. Various types of medicinal plants each has certain criteria which result in difficulty in determining the alternative medicinal plants as the best priority. This research aims to select alternative medicinal plants which have nutritious substances for hypertension disease treatment. Not only nutritious substances, but also considering the price, availability and taste of the plant. Hypertension is a disease caused by high blood pressure. The selection of alternative medicinal plants for hypertension disease using Analytical Network Process (ANP) and Simple Multi Attribute Rating Technique (SMART) method. Analytical Network Process (ANP) method is used for determining the weights of each of the supporting criteria and Simple Multi Attribute Rating Technique (SMART) method is used for ranking of alternative medicinal plants selection. This research uses 10 data of medicinal plants to be tested. The result of Analytical Network Process (ANP) and Simple Multi Attribute Rating Technique (SMART) method use Spearman Rank correlation test with rs = 0.964 that means a relationship system and expert approach perfectly.
Penentuan Kenaikan Jabatan Karyawan Menggunakan Metode Fuzzy-Analytical Hierarchy Process (FAHP) di Pabrik Gula Lestari Patianrowo Nganjuk Erma Rafliza; Indriati Indriati; Rizal Setya Perdana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Career promotion is an important factor and heavily expected by the employees. Establishment of position that analyzed manually will be very disadvantage if there is Human Error or error conducted by humans related to the careful analysis towards the process compared to calculation conducted by machine. The implementation of Fuzzy-Analytical Hierarchy Process (FAHP) is conducted by determining matrix values of paired comparison as parameter about how important the parameter compared to other parameters. Three parameters as comparison are KIN (Individual Competence), KT (Core Competence), and KP (Role Competence). In this research, it used total test data of 78 which obtained result with accuracy level in the created system is 92.3%, in which matrix values of paired comparison as with expert statement, then if the level of importance for a parameter replaced to be slightly more important than value established by expert then accuracy level will be better, which is 94.87%. However, if the values established by expert replaced to be the opposite values then the obtained accuracy level is very low, which is only 79.48%. Therefore, although accuracy level by expert is already good, however, if a parameter changed to be slightly more important, then, the obtained result will be more optimal.
Analisis Sentimen Konten Radikal Melalui Dokumen Twitter Menggunakan Metode Backpropagation Brian Andrianto; Indriati Indriati; Sigit Adinugroho
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Twitter is a social networking service where users can post and interact with messages, known as "tweets". Twitter is also used by some people to give their opinions on something but sometimes too excessive even sometimes found a tweet that smells radical. The radical actions that exist in social media are usually referred to as radical content. The radical content available on social media can certainly harm some parties. There are also certain parties who utilize radical content to achieve certain goals. Therefore, in this study try to analyze the Indonesian tweet that contains the word radical, including in the content of radical positive or negative radical. Tweet can be from twitter that contains public opinion that leads to radical content will be classified. Tweet can be called a document or data will first go through the preprocessing process. Then the document was broken into 6 types of words, including the nouns, verbs and adjectives where each type of word will be divided again into positive and negative. After the break will be calculated how many the number of types of words in each document so that it can be converted into numbers that can then be incorporated into the algorithm formula.
Klasifikasi Hoax Pada Berita Kesehatan Berbahasa Indonesia Dengan Menggunakan Metode Modified K-Nearest Neighbor Andre Rino Prasetyo; Indriati Indriati; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

News is a source of information about current events which can be found in newspapers, television, the internet and other media. Currently the news that is disseminated often without writing the source clearly, especially the type of news about health, it can lead to misinterpretation because the news is not necessarily true or wrong so it takes a smart system to classify health news is whether included in the category of hoax or fact. The hoax classification process use several stages ranging from preprocessing consisting of tokenisasi and filtering. Continued with word-weighting process and cosine similarity to classification process using Modified K-Nearest Neighbor method. The results obtained based on the implementation and testing resulted in the best value of k amounted to 4, precision of 0,83 recall of 0,75 f-measure of 0,79 and the accuracy of 75%. The test results obtained because the health news content used is still too common, many non-standard words and the determination of k-values ​​used are very influential on whether or not the process of classification of health news documents.
Peramalan Debit Bendungan Dengan Menggunakan Metode Backpropagation dan Algoritme Genetika Beta Deniarrahman Hakim; Indriati Indriati; Ahmad Afif Supianto
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

Dam discharge forecasting is needed to plan water allocation plans for various needs such as for Hydropower plant, flood control and irrigation. Artificial neural network in this case backpropagation method has a learning method to change the weight of the value of the architecture of the artificial neural network.#Genetic algorithms can optimize the#weight of artificial neural networks to avoid the occurrence of a minimum local which is a weakness of backpropagation. Genetic algorithms will optimize the weight#of the artificial neural network so individuals which are produced as a weight representation with the best fitness value resulting from the optimization process with the genetic algorithm then used as the initial weight of the artificial neural network backpropagation method. The data used as input data is the dam discharge time series data the previous months. The data used is monthly debit data from 2008 to 2017. Input data will be processed to produce an output value which is the forecasted value of the dam discharge in the next month. The optimal training parameters for genetic algorithm and backpropagation training are the population size=100, the generation=100, Cr and Mr combination 0,6 and 0,4, the number of iterations=500, the value of learning rate=0,7. The test results using optimal parameters get the MSE value=0,04188
Query Expansion Pada LINE TODAY Dengan Algoritme Extended Rocchio Relevance Feedback Chandra Ayu Anindya Putri; Indriati Indriati; Ahmad Afif Supianto
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

LINE TODAY provides access to up-to-date news contents. Data on LINE TODAY are used to be able to do search engine feature. Query Expansion technique will be very useful if it is to be combined with search engine system where the queries inputted by users are combined with additional queries from the system. These additional queries will make queries generated by users more specific. In addition, users feedback (user judgement/explicit relevance feedback) assessing on each news can minimize ambiguous queries. The process begins with preprocessing technique consisting of several stages which are cleansing, case folding, tokenization, filtering, and stemming. And then, term weighting and cosine similarity. The next process is calculated using the Extended Rocchio Relevance Feedback method which is a traditional method from Rocchio Relevance Feedback to generate an additional queries. The results are obtained from implementation and testing process of Query Expansion on LINE TODAY with Extended Rocchio Relevance Feedback Algorithm resulted an average Precision value of 0.53308, Recall value of 0.81708, F-Measure value of 0.59553, and Accuracy value of 0.9574. The accuracy value obtained with Extended Rocchio Relevance Feedback method based on user judgement increase by 2% compared to automated search by the method of Rocchio Relevance Feedback.
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