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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal POINTER Sinkron : Jurnal dan Penelitian Teknik Informatika Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Jurnal Informatika dan Multimedia JAST : Jurnal Aplikasi Sains dan Teknologi TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Sistem Informasi, Teknologi Informasi, dan Edukasi Sistem Informasi (JUST-SI) DEDIKASI PKM Jurnal Informatika dan Multimedia Enrichment: Journal of Multidisciplinary Research and Development Majority Science Journal
Dian Eka Ratnawati
Brawijaya University, Malang
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other

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Prediksi Hasil Panen Udang Vaname menggunakan Algoritme Backpropagation Neural Network Harris Imam Fathoni; Bayu Rahayudi; Dian Eka Ratnawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 8 (2022): Agustus 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Shrimp (Caridea) is one of the commodities that are often exported every year. In cultivation, to maintain the productivity of shrimp harvests, there are several parameters that must be seen every day. Forecasting is used to help farmers to be used as a reference in terms of shrimp maintenance until the final harvest. This research used shrimp cultivation for four years from 2016 until 2019 as data inputs Then normalization of data is carried out which will then be processed using the backpropagation method to find the forecasting value for vaname shrimp yields. The final results were denormalized again and then evaluated using the MAPE (Mean Absolute Percentage Error) method and obtained in this study the optimal value with a minimum MAPE of 3.65% using the hidden neuron parameter = 1, the epoch value = 1000 and the initial random weight range value from -1 up to 1.
Analisis Sentimen Aplikasi MyXL menggunakan Metode Support Vector Machine berdasarkan Ulasan Pengguna di Google Play Store Dimas Diandra Audiansyah; Dian Eka Ratnawati; Buce Trias Hanggara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 8 (2022): Agustus 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Review on Google Play Store is one of the features used to provide a rating of an application. MyXL is a self-service application provided by PT XL Axiata Tbk on the Google Play Store that is useful for users to perform XL services easier such as activating internet packages, checking credit, checking remaining quota, etc. However, the review on the application is only in the form of text with no specific meaning and there are some high ratings but the reviews given are negative reviews, for that a sentiment analysis is needed that can classify reviews as user sentiment. In this research, the scraping stage was carried out for collecting application user review data, followed by the text preprocessing stage to process data by selecting data and turning it into more structured data. The data from the text preprocessing were word weighted using the Term Frequency - Inverse Document Frequency (TF-IDF) method. Then sentiment classification is carried out using the Support Vector Machine (SVM) algorithm. The best results were obtained with the SVM algorithm for sentiment testing for 2 classes using the value of training data and test data of 80%:20%, the total data is balanced with 160 positive and 160 negative data, experiments with cross validation K = 5 and the use of a linear kernel. The results obtained for the average value of 88% accuracy, 88% precision, 88% recall and 88% f-measure.
Analisis Sentimen Objek Wisata Danau Toba berdasarkan Ulasan Pengunjung menggunakan Algoritma Support Vector Machine Immanuel Tri Putra Sihaloho; Dian Eka Ratnawati; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 9 (2022): September 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Lake Toba is one of the tourist destinations in Indonesia and is designated as one of the five developments of the National Tourism Strategic Area which is the government's super priority program in tourism development in Indonesia. Therefore, Lake Toba tourism managers need to know the perspective of visitors as evaluation material. Data acquisition of visitor reviews of Lake Toba attractions can be easily obtained through the Tripadvisor website using web scraping techniques. Reviews from Tripadvisor will be categorized into three classes, namely positive, neutral and negative. Before doing the classification, do text preprocessing to process the data into more structured data for research needs and carry out word weighting using the Term Frequency - Inverse Document method. Then the classification is carried out using the Support vector Machine algorithm. The best results in testing using the Support vector Machine algorithm are testing on 2 sentiment classes with a total of 220 data, using a linear kernel and a C value of 100. Accuracy, precision, recall, and f1-score values ​​in this machine learning model are successively were 83%, 84%, 83%, and 83%.
Analisis Sentimen Ulasan Aplikasi Dana dengan Metode Random Forest Fanka Angelina Larasati; Dian Eka Ratnawati; Buce Trias Hanggara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 9 (2022): September 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Digital Wallet is an electronic application that can be used to make financial transactions online, without physical money and without cards, users only use smartphones in conducting financial transactions. A popular digital wallet application during this pandemic is Dana. The Dana app has many users, so there are often positive, negative and neutral reviews that are irrelevant to the rating given on the Google Play Store. The Dana application review data will be obtained using the Web Scraping technique using the Google-Play-Scraper API. The data from the scraping will then be done by text preprocessing to clean the text so that the data can be executed. Sentiment analysis can detect whether a text contains positive, negative or neutral opinions from user reviews that do not match the rating. Random Forest is a method in analysis that consists of several decision trees as a classifier. In this study, the random forest method was used by dividing three classes of sentiment, namely positive, negative and neutral. Also taking evaluation indicators, namely accuracy, recall, precision and f-measure. The test is carried out based on the number of trees and the depth of the tree to 1354 data by dividing the data by 250 data per class. Based on the results of tests and analyzes that have been carried out, with a comparison of training data and test data of 80%: 20%, namely precision 84%, recall 84%, F1-Score 84% and accuracy of 84% with a tree depth of 65 and a tree number of 400.
Analisis Sentimen Ulasan Aplikasi PeduliLindungi dengan Metode Random Forest Muhammad Reza Utama Pulungan; Dian Eka Ratnawati; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 9 (2022): September 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

PeduliLindung is an application developed by the Ministry of Communication and Information (KOMINFO) in collaboration with the Covid-19 Handling Committee. This application is useful for tracing user activities to places visited, getting vaccination info, and also notification of regulations that apply in Indonesia during the Covid-19 pandemic. The PeduliLindung application is used by more than Fifty million users based on information on the total downloads available on the Playstore platform. With many PeduliLindung users during the pandemic, there are often positive, negative and neutral reviews of the PeduliLindung application, especially on the App Store platform. This PeduliLindung application review data will be a data source for analysis and also classifying the sentiment. The PeduliLindung application review data will be obtained using the Scrapping technique where this process can extract data from website pages. The classification method used is Random Forest by testing the depth of the tree and the number of trees. The evaluation methods used are Confusion Matrix. The results of the study with a tree depth of 65 and the number of trees 400 got the best values, namely precision 71%, recall 71%, F1-Score 71% and accuracy 72% with a ratio of 90% training data and 10% test data.
Penggunaan Metode Ekstraksi Fitur Tekstur Gray Level Co-ocurrrence Matrix dan K-Nearest Neighbor untuk Identifikasi Jenis Penyakit Tanaman Apel Muhammad Iqbal Mustofa; Muhammad Tanzil Furqon; Dian Eka Ratnawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 9 (2022): September 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Indonesia is a country with a tropical climate that makes it easy for apple plants to grow, even the apple crop farming industry is one of the fields that is widely cultivated in Indonesia. Malang is one of the largest apple producing areas in Indonesia. It was also explained in the data from the Central Statistics Agency (BPS) in 2019 that Malang Regency could produce 1,406,173 quintals of apples. In apple cultivation, pest and disease control is one of the important factors in the development of apple plants because it can affect the yield and quality of apples. There are several main diseases that attack plants such as Apple Scab caused by the fungus Venturia inaequalis, Black Rot caused by the fungus Botryosphaeria obtusa and Cedar-Apple Rust caused by the fungus Gymnosporangium juniperi-virginianae. Information technology is needed to speed up the process of identifying apple plant diseases. This study utilizes the results of texture feature extraction of Gray Level Co-occurrence Matrix (GLCM) and the K-Nearest Neighbor classification method. In this study, the data used were 1943 leaf images with 4 classes including Apple Scab, Black Rot, Cedar Apple Rust and Healthy. The GLCM features used in this research are Variance, Homogeneity, Energy and Correlation. In the evaluation, the K-fold cross validation method was used to eliminate bias in the data with k=10. Of all the tests carried out, the highest average accuracy was 84.56% at an angle of 90° with a value of d=2 and at a value of k=3 with the Euclidean Distance calculation method.
Pengembangan Sistem Informasi Pengelola Inventaris Sekolah berbasis Web menggunakan Laravel (Studi Kasus : SMA Negeri 1 Sungai Ambawang) Fauzidan Iqbal Ghiffari; Dian Eka Ratnawati; Widhy Hayuhardhika Nugraha Putra
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 13 (2022): Publikasi Khusus Tahun 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Dipublikasikan di JUST-SI
Implementasi Algoritma Support Vector Machine dan Model Bag-of-Words dalam Analisis Sentimen mengenai PILKADA 2020 pada Pengguna Twitter Raja Farhan Ramadha Pohan; Dian Eka Ratnawati; Issa Arwani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 10 (2022): Oktober 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Social media is a digital platform used to gather information. One of the social media in Indonesia that has the most users is Twitter. Twitter is a social media platform in a form of a microblog, that allows users to exchange opinions and share ideas. One of the topics that was widely discussed on Twitter was the implementation of the Pilkada 2020. Pilkada 2020 attracted the attention of many Twitter users because the implementation was carried out in the midst of a pandemic. Tweets or tweets of Twitter users here are used as objects to conduct sentiment analysis on related topics. This analysis process is carried out by implementing the Support Vector Machine algorithm to classify positive and negative tweets. This study uses 400 tweets, consisting of 187 positive tweets and 213 negative tweets. The scores of accuracy, precision, recall, and f1-score in this machine learning model are 87.5%, 87.4%, 87.4%, and 87.4%, respectively. This value is obtained using the C parameter of 5, and the max_iter parameter of 100.
Optimasi Portofolio Saham menggunakan Algoritma Genetika Adaptif pada Indeks Saham LQ45 Rama Humam Syarokha; Dian Eka Ratnawati; Achmad Ridok
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 13 (2022): Publikasi Khusus Tahun 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Diterbitkan di JTIIK (Jurnal Teknologi Informasi dan Ilmu Komputer)
Pengembangan Aplikasi Ekstraksi KTP dan Reverse Geocoding pada Perangkat Bergerak untuk Verifikasi dan Validasi Data Pendaftar Data Terpadu Kesejahteraan Sosial (DTKS) RE. Miracle Panjaitan; Bayu Rahayudi; Dian Eka Ratnawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 12 (2022): Desember 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Based on the 1945 Constitution of the Republic of Indonesia, the state is responsible for caring for the poor to meet the basic needs of humanity. The resources of social welfare in villages, assist the process of collecting data and verifying and validating the data of the poor. The results of the verification and validation are reported to the regent/mayor, then submitted to the governor, then forwarded to the Minister. Data that has been verified and validated must be based on information technology and integrated under the responsibility of the Minister. Integrated data belonging to the Ministry of Social Affairs is called the Integrated Data on Social Welfare (DTKS) and is used as a reference for the provision of Social Assistance (BANSOS). In fact, many recipients of Social Assistance (BANSOS) were found who should not be the target of this work program of the Ministry of Social Affairs. Researchers developed an ID card extraction and reverse geocoding application to help the verification and validation process, namely by matching the address obtained from the KTP extraction results with the location of the reverse geocoding results when taking photos of the ID card. This address matching is done by utilizing the Google Vision and Geocoder libraries. If the addresses match, then the DTKS registrant verification process can continue. If the addresses do not match, the DTKS registrant verification process cannot continue. This system was tested 10 times, with 5 experiments at the exact location with the ID card address and 5 at different locations with the ID card address. The success rate of this system trial is 95,7%.
Co-Authors Abdurrahman Airlangga, Aria Abhiram, Muhammad Tegar Achmad Arwan Achmad Ridok Achmad, Riza Putra Adhitya, I Made Yoga Adrian Firmansah, Dani Afif Ridhwan Afrida Djulya Ika Pratiwi Agus Wahyu Widodo Agustin Kartikasari Ahmad Afif Supianto Akbar, Rozaq Aldy Satria Alfa Fadlilah Alifah, Syafira Almira Syawli, Almira Alvian Akmal Nabhan Amonito, Kurnia Ana Mariyam Puspitasari Anak Agung Bagus Arisetiawan Anam, Syaiful Ardhiansyah, Muhammad Hanif Arief Andy Soebroto Arif Pratama Asmoro, Priandhita Sukowidyanti Asroru Maula Romadlon Audia Refanda Permatasari Ayu Dwi Lestari, Cynthia Ayulianita A. Boestari Azizul Hanifah Hadi Bayu Rahayudi Bayu Satriawan, Eka Bayu Septyo Adi Bella Krisanda Easterita Bening Herwijayanti Berton, Freddy Toranggi Buce Trias Hanggara Buce Trias Hanggara Buchori Anantya Firdaus Budi Darma Setiawan Cahyo Gusti Indrayanto Candra Dewi Dany Primanita Kartikasari Darma Setiawan, Budi Darmawan, Riski Davia Werdiastu Denny Manuel Yeremia Sinurat Deny Tisna Amijaya, Fidia Devi Nazhifa Nur Husnina Dewi Yanti Liliana Dhiva Mustikananda Dimas Diandra Audiansyah Dimas Fachrurrozi Azam diniyah, zubaidah Diva, Zahra Djoko Pramono Dwi Ari Suryaningrum Dwi Febry Indarwati Dwi Purwono, Prayoga Dwija Wisnu Brata Dyva Pandhu Adwandha Dzulkarnain, Tsania Dzulkarnain, Tsania - Easterita, Bella Krisanda Edgar Maulana Thoriq Edy Santoso Elfa Fatimah Ema Agasta Entra Betlin Ladauw Eva Agustina Ompusunggu Fadhil, Muhammad Farrasseka Fadila, Putri Nur Faiz Anggiananta Winantoro Fanka Angelina Larasati Fathin Al Ghifari Fatthul Iman Fauzan Dwi Kurniawan, Fauzan Dwi Fauzidan Iqbal Ghiffari Figgy Rosaliana Firdaus, Muhammad Fariz Fitra Abdurrachman Bachtiar Fitri Dwi Astuti Fitria Yesisca Fitria, Tharessa Ghani Fikri Baihaqi glenando Gusti Ngurah Wisnu Paramartha Hadi Wijoyo, Satrio Hamas, radityo Hana Chyntia Morama Hanggara, Buce Trias Hanifa Maulani Ramadhan Haris Haris, Haris Harris Imam Fathoni Hasibuan, Herida Hafni Hasibuan, Raka Ardiansyah Heru Nurwasito Hilal, Khaliffman Rahmat Hilmy Ramadhan, Achmad Zhafran Huda Minhajur Rosyidin I Dewa Gede Ngurah Bramasta Darmawan Ibnu Aqli Ibnu Aqli, Ibnu Ibrahim Kusuma Ilyas, Muhaimin Imam Cholissodin Imam Cholissodin Imam Cholissodin Immanuel Tri Putra Sihaloho Indriati ., Indriati Indriati Indriati Ismiarta Aknuranda Issa Arwani Issa Arwani Isti Marlisa Fitriani Izza, Aisyah Nurul Jesika Silviana Situmorang Jibril Averroes, Muhammad Juan Michel Hesekiel Kartika, Annisa Wuri Kelvin Anggatanata Kevin Renjiro Khairi Ubaidah Khoba, Ahmad Faiz Khofifatunnabilah, Khofifatunnabilah Kirana, Urdha Egha Krishna Febianda Kusuma, Salsabila Azzahra' Zulfa Lailil Muflikhah Leonardo, Ryan Luqman Rizky Dharmawan M. Ali Fauzi Madjid, Marchenda Fayza Maghfiroh, Sofita Hidayatul Mahendra Data Mahendra Data Mala Nurhidayati Maliha Athiya Rahmani Marji . Marji Marji Marji Marji Marji Marji Maulana Syahril Ramadhan Hardiono Michael Eggi Bastian Mochammad Iskandar Ardiyansyah Rochman Moh Fadel Asikin Muh. Arif Rahman MUHAJIR Muhammad Iqbal Mustofa Muhammad Kevin Sandryan Muhammad Reza Utama Pulungan Muhammad Tanzil Furqon Muhyidin Ubaiddillah Muslimah, Fakhriyyatum Muthia Maharani Nabilah Iftah Nella Naily Zakiyatil Ilahiyah Nanang Yudi Setiawan Nanang Yudi Setiawan Nanda Alifiya Santoso Putri Nanda Petty Wahyuningtyas Nilna Fadhila Ganies Norma Desitasari Novirra Dwi Asri Nugraha Perdana, Aditya Nugraheni, Miftakhul Fitria Nur Adli Ari Darmawand Nur Khilmiyatul Ilmiyah Nuraini Anitasari Nuralam, Inggang Perwangsa Nurul Hidayat Nyimas Ayu Widi Indriana Oceandra Audrey Pandu Adikara, Putra Pangestu Ari Wijaya Panjaitan, RE. Miracle Prahesti, Suherni Prakoso, Ricky Pratomo Adinegoro Priyono, Mochammad Fajri Rahmatullah Rendra Puji Indah Lestari Purnomo, Welly Putra Pandu Adikara Putra, Alland Rifqy Putri, Nindy Alya Rachmad, Zikfikri Yulfiandi Raden Rizky Widdie Tigusti Rahma, Dzakiyyah Afifah Rahmah, Yusriyah Raisha, Serefika Raja Farhan Ramadha Pohan Rama Humam Syarokha Randy Cahya Wihandika Rani Metivianis Ratih Diah Puspitasari RE. Miracle Panjaitan Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Retno Indah Rokhmawati, Retno Indah Revi Anistia Masykuroh Rifqi Irfansyah, Nandana Rizal Setya Perdana Rizal Setya Perdana Robiata Tsania Salsabila Aditya Putri Rodiah Rodiah Ryan Leonardo Salsabillah, Dinar Fairus Saparila Worokinasih Saputro, Dimas Sarie, Riza Athaya Rania Satriawan, Eka Bayu Satrio Agung Wicaksono Satrio Hadi Wijoyo Sema Yuni Fraticasari Setiawan, Alexander Christo Setya Perdana, Rizal Setyowati, Andri Shafira Margaretta Sherly Witanto Sherryl Sugiono Sindarto Sigit Pangestu Silvia Ikmalia Fernanda Siregar, Fauziah Syifa R. Siti Fatimah Al Uswah Sobakhul Munir Siroj Sormin, Hartati Penta Angelina Sri Indrayani, Sri Suhhy Ramzini Sukmawati, A'inun Sutrisno Sutrisno Sutrisno, Sutrisno Syaiful Anam Syifa Namira Neztigaty Thifal Fadiyah Basar Titis Sari Kusuma Ulfa Lina Wulandari Utomo, Yoga Cahyo Vina Adelina Welly Purnomo Wibowo, Shinta Dewi Putri Widhy Hayuhardhika Nugraha Putra Wijanarko, Rizqi Winda Fitri Astiti Winurputra, Raihan Wiratama Paramasatya Yahya, Faiz Yolanda Nailil Ula Yudi Setiawan, Nanang Yuita Arum Sari Yunita Dwi Alfiyanti Yure Firdaus Arifin Zahra, Wardah