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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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Analisis Sentimen Pengguna Twitter terhadap Pembayaran Cashless menggunakan Shopeepay dengan Algoritma Random Forest Thifal Fadiyah Basar; Dian Eka Ratnawati; Issa Arwani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 3 (2022): Mei 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Shopeepay is an electronic money service issued by the shopee company for transactions at shopee, offline payments at shopeepay partners, and storing the returned funds for use in subsequent transactions. Many shopeepay users in Indonesia raise many opinions on this platform, one of which is the microblogging site, namely Twitter. Sentiment analysis or opinion mining is computational learning to identify and extract as well as study opinions, sentiments, emotions, judgments and views in text form. Random Forest which is one of the methods in conducting Sentiment Analysis and enters the type of Decision tree method. In this study, the random forest classifier algorithm was used to classify the opinions of twitter users on the shopeepay platform. From the implementation, the values ​​for the results with a tree depth of 55 and the number of trees 300 resulted in 95% precision, 94% recall, 95% F1-Score and 95% accuracy.
Analisis Sentimen berbasis Aspek terhadap Ulasan Hotel Tentrem Yogyakarta menggunakan Algoritma Random Forest Classifier Hana Chyntia Morama; Dian Eka Ratnawati; Issa Arwani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 4 (2022): April 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The development of tourism has increased visits in tune with the hospitality industry in Indonesia. One of the popular five-star hotels is Hotel Tentrem Yogyakarta. The large number of hotel review data makes visitors confused to make the right decision. Sentiment analysis can overcome this problem by processing review text data which was initially unstructured into information that has positive, negative or neutral values. In addition, aspect categorization is also carried out so that it is easier for visitors to find reviews according to their purpose. The aspects used in this research are room aspects, service aspects, location aspects, swimming pool aspects, and gym aspects. Hotel review data was obtained by scraping using the Webscraper.io tool on the Tripadvisor website. Classification was carried out using the Random Forest Classifier algorithm and term frequency-inverse document frequency (TF-IDF) word weighting. After analyzing the test, the aspect that is used is only the room aspect because it has a balanced proportion of sentiment compared to other aspects. The proportion of sentiment is considered important in the classification of sentiment. The test is carried out based on the parameter scenario of the number of trees and the depth of the tree. The number of trees used in this study is 300 and the depth of the tree is 10. The test results prove that the greater the number of trees and the depth of the tree, the better the prediction results. The best classification results in the room aspect is 90% for the accuracy value and the f1 score.
Analisis Sentimen pengguna Twitter terhadap Vaksinasi Sinovac dan AstraZeneca menggunakan Algoritma CART Rani Metivianis; Dian Eka Ratnawati; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 4 (2022): April 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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The first case of Covid-19 appeared in Indonesia on March 2, 2020 which caused various diseases that interfere with the respiratory system in humans. With the Covid-19 prevention strategy by requiring the public to vaccinate. Vaccines are substances that form a weakened immune system and can form antibodies for those who have not been exposed to the COVID-19 virus. There are various kinds of vaccines in Indonesia, namely Sinovac, AstraZeneca, Prifzer-BioNtech, Moderna, Sinopharm, Johnson & Johnson, CaSino, Spuntnik V. In this study, two types of vaccines were widely discussed by netizens, namely Sinovac and AstraZeneca. Sinovac is the first vaccine in Indonesia which has become a national vaccination program, while the AstraZeneca vaccine is ranked second after the Sinovac vaccine which was discussed by netizens due to the halal-haram debate on the AstraZeneca vaccine. This study aims to analyze public opinion on the Sinovac vaccine and Astrazeneca vaccine in Indonesia. Analysis was carried out on 671 tweets related to the Sinovac vaccine and Astrazeneca vaccine using the Classification and Regression Tree (CART) algorithm. 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% with precision, 77%, recall 75%, f1 score 76%, and accuracy 76%.
Pengembangan Sistem Informasi Pelaporan pada Korwilker Pendidikan dan Kebudayaan Kecamatan Bareng berbasis Web Elfa Fatimah; Issa Arwani; Dian Eka Ratnawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 4 (2022): April 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Reporting activities are activities that are commonly found in various agencies, both government agencies, and central agencies. The school reports on school data and student data, which is then sent and recapitulated by the Coordinator for Education and Culture of the Bareng sub-district. The reporting process still uses a manual system, there is no overall system integration. We need a system that can facilitate the reporting process and make monthly recordings that can also provide convenience in managing reporting. Therefore, research was conducted on the Development of a Web-Based Reporting Information System at the Education and Culture Coordinator of the Bareng District. The development of this information system is carried out using the waterfall development method which consists of the stages of needs analysis, system design, implementation, and testing and is developed on a web-based basis. The results of this study obtained 2 actors with 14 functional needs and 1 non-functional need. This system has been tested API using postman, validation testing using the black box method and compatibility testing. In this test, validation tests are carried out on all functional requirements that provide valid results and system compatibility testing can be run well on various browsers and platforms.
Klasifikasi Citra Sistem Isyarat Bahasa Indonesia (SIBI) dengan Metode Convolutional Neural Network pada Perangkat Lunak berbasis Android Sherryl Sugiono Sindarto; Dian Eka Ratnawati; Issa Arwani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 5 (2022): Mei 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The standarized Indonesian Sign System (SIBI) is one of the media that helps communication among the deaf and mute in a wider community. It is known that 211.889 Indonesians are persons with disabilities consisting of 6.5% (13.802) are deaf and 2.6% (5.580) are speech impaired. Many ordinary citizens do not understand sign language which becomes a limitation for communicating with the deaf or mute. This research develops an application named IBIS with real-time sign language translator system. The real-time sign language translator system is developed using the convolutional neural network method with Tensorflow Lite Model Maker as the development medium. Researcher used the convolutional neural network method as the accuracy is relatively high. The model is integrated into Android based application developed with Flutter framework. IBIS application development starts from system and interface design using the waterfall method. Furthermore, the system is implemented in accordance to the defined requirements. The model is integrated into the Android based application using tflite_flutter and tflite_flutter_helper plugin. After that, testing is carried out for IBIS application and object detection model. The test for application testing includes validation testing and usability testing. The validation test is carried out using the blackbox method with the results show that all functionalities is in accordance with the defined requirements. Usability test with System Usability Scale (SUS) method reached a value of 86 and fall into the acceptable category. Testing for object detection model is done by comparing the original class with the detected class. The accuracy test reached 88% for 15 classes.
Analisis Perbandingan Klasifikasi Topik Skripsi Mahasiswa menggunakan K-Nearest Neighbor dan Support Vector Machine (Studi Kasus: Jurusan Sistem Informasi, Fakultas Ilmu Komputer, Universitas Brawijaya) Fitria Yesisca; Dian Eka Ratnawati; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 5 (2022): Mei 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

JPTIIK (Journal of Information Technology and Computer Science Development) is a platform that presents student journals of FILKOM UB. In this platform, journals have not been classified based on the thesis theme which refers to the 2018 FILKOM thesis guidebook, especially for the Information Systems department. From these problems, it was decided to classify topics in the majors of SI, FILKOM, UB based on the title, abstract, and a combination of abstract titles. There are 3 thesis themes used in the classification process, namely development, data and information management, and IS governance and management. The data collected was 300 with a comparison of 125 development, 100 SI governance and management, and 75 management data and information. This classification will compare the K-Nearest Neighbor and Support Vector Machine methods and will compare the classification results based on the title, abstract, and abstract title. Tests with a value of K=9 for the KNN method, a value of C=10 and iteration=50 on the title and abstract, and iteration=150 for the abstract title on SVM got the best accuracy value. The results of the classification based on the title and abstract of the SVM method get the highest accuracy value compared to the KNN method with the classification results in the title getting an accuracy value of 97.08%, precision 97.81%, recall 96.91%, and f-measure 97.11% while for Abstract titles get 97.08% accuracy, 97.93% precision, 96.67% recall, and 97.07% f-measure.
Penerapan Algoritma Genetika untuk Optimasi Penjadwalan Pondok Pesantren berdasarkan Constraint Ustadz (Studi Kasus: Yayasan Pendidikan Budi Utomo, Gadingmangu, Perak, Jombang) Huda Minhajur Rosyidin; Bayu Rahayudi; Dian Eka Ratnawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 5 (2022): Mei 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Scheduling with a manual process will be less efficient because it takes a long time, problems in the preparation of the schedule become complex if the number of components increases or the size of each component increases. It is hoped that the resulting schedule will not only avoid clashes, but also adjust to the ustadz's constraints that must be met. Genetic Algorithm is an iterative, self-adjusting and probabilistic algorithm in the search for global optimization. The process of initializing the chromosomes by generating command data representing integers, where the command code entered for each gene is randomized. The chromosome with the highest fitness value is an illustration of the solution in this schedule. Based on the tests carried out,
Naive Bayes untuk Klasifikasi Pergantian Operating System pada Personal Computer di Bank X Syifa Namira Neztigaty; Dian Eka Ratnawati; Dany Primanita Kartikasari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 6 (2022): Juni 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Bank X is one of the largest banks in Indonesia. The Desktop Team, which is one of the teams that carry out risk identification and periodic evaluation on PCs. Through this evaluation, the Desktop Team found many operating systems on PCs at Bank X were end-of-support. This condition poses a risk if there are bugs or security holes in the operating system that can lead to data theft. In order to avoid this incident, the entire operating system of end-of-support PCs must be replaced with a newer operating system. Currently the operating system replacement activity has been carried out, but it is still done manually and has not been effective. The process has succeeded in replacing ±5,000 PCs. Through this system, the Desktop Team Desktop Team will get the class results from the PC. The data could be classified by using data mining classification method, namely Naive Bayes. From the PC attribute data does not yet have a class, the system will perform data processing. Then the data is calculated using the existing functions on the controller, by accessing classified PC database. Information about the classification results is displayed on the prediction results page. From the results of testing the accuracy value is 92.8371%.
Pengembangan Sistem Informasi Pelayanan Pasien berbasis Web (Studi Kasus: Balai Pemasangan Gigi Setia Kawan) Fathin Al Ghifari; Dian Eka Ratnawati; Issa Arwani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 6 (2022): Juni 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Setia Kawan is a place that serves the manufacture and installation of dentures. The service flow starts from registration, calling, consulting, measuring, manufacturing, installing and paying. Setia Kawan has a problem, namely the recording of queue data and receipts is still done manually. This causes queues to pile up, as employees need to handle 2 jobs. Another problem is that when a patient wants to make a warranty claim, employees need time to make sure the receipt is genuine and valid by looking for data in the queue archive on that date. Because of this problem, Setia Kawan received criticism that the services provided were very long. Based on that problem, the researcher created a patient service information system which on the admin side has features to manage patient data, queues, bookings and payments. The information system on the Patient side has features for booking queues, changing schedules and canceling bookings. The development of this system uses the waterfall model because all requirements have been defined at the requirements analysis stage which produces 2 actors, 11 functional requirements and 1 non-functional. The implementation phase produces 12 interface pages on the Admin side and 4 on the Patient side. Based on the results of functional testing, both sides get a success value of 100%. The results of the usability test using the usability scale (SUS) system get 68 points for the admin frontend and 75 for the patient frontend. SUS for the admin frontend is in the OK and marginal categories, while the patient frontend is in the Good and Acceptable category.
Perbandingan Algoritma Naive Bayes dan Support Vector Machine untuk Analisis Sentimen terhadap Review Produk Aster Kosmetik Malang Marketplace Shopee Dhiva Mustikananda; Dian Eka Ratnawati; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 7 (2022): Juli 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Aster Cosmetics Malang is a popular beauty shop in Malang City. Aster Cosmetics uses the Shopee online shopping platform as a product promotion medium. Online shopping provides many conveniences in the midst of the COVID-19 pandemic. On the online shopping platform there is a feature to add product reviews, where product reviews can be used as a consideration for potential buyers in making decisions. Shopee is used as a data source for sentiment analysis on Aster Cosmetics Malang product reviews. The review data are classified into positive, negative, and neutral categories. Classification is done by comparing the Naive Bayes algorithm and Support Vector Machine. This study uses 300 data for the classification of 3 sentiments, namely positive, negative, and neutral, then 200 data for the classification of 2 sentiments, namely positive and negative. Testing by comparing the two methods using the same test parameters, namely the percentage of training data and test data 80%:20% and cv=10. The classification results get the highest accuracy value of the Support Vector Machine method in the classification of 2 sentiments with an accuracy value of 87.56%, precision 88.81%, recall 86.76% and f-measure 86.85%, the highest accuracy results in the classification of 3 sentiments using the Support Vector Machine method with an accuracy value of 79.71%. , precision 81.56%, recall 79.56% and f-measure 79.36%.
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