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All Journal Jurnal Bisnis dan Manajemen Journal of Innovation and Applied Technology Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal POINTER Jurnal Pengabdian Kepada Masyarakat (Indonesian Journal of Community Engagement) Sinkron : Jurnal dan Penelitian Teknik Informatika Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Seminar Nasional Teknologi Informasi Komunikasi dan Industri DIKEMAS (Jurnal Pengabdian Kepada Masyarakat) JPKMI (Jurnal Pengabdian Kepada Masyarakat Indonesia) Jurnal Sistem Informasi, Teknologi Informasi, dan Edukasi Sistem Informasi (JUST-SI) Bulletin of Social Informatics Theory and Application
Bayu Rahayudi
Fakultas Ilmu Komputer - Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Public Health Social Sciences

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Optimasi Pendistribusian Air Mineral menggunakan Algoritma Genetika Arsti Syadzwina Fauziah; Imam Cholissodin; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 2 (2022): Februari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Distribution is one of the marketing activities carried out with the aim of distributing products from producers to consumers. This distribution is very important in marketing activities, if there is no distribution activity then the goods will not reach consumers from less affordable areas. Mineral water products almost dominate the beverage industry market and with population growth it is possible that the need for mineral water will continue to increase. At the point when the interest for mineral water expands, the job of distribution turns out to be important. In this distribution interaction, a method is needed that can handle the problems, this research was carried out using the Genetic Algorithm method in finding the optimization value contained in the Traveling Salesman Problem (TSP) to find the optimal total distance value in this distribution activity. Based on this research, the parameters are the cr 0.1, the mr 0.9, the popsize is 1000th population. The maximum iteration is 100th generation, the average fitnesss is 0.006438, and the total distance generated is more optimal than the route made by the courier of 35.3 km on the first courier, 35.8 km on the second courier and 34.9 km on the third courier.
Analisis Sentimen Twitter terhadap Kebijakan Pemberlakuan Pembatasan Kegiatan Masyarakat menggunakan Metode Support Vector Machine Dhimas Wida Syahputra; Bayu Rahayudi; Lailil Muflikhah
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

COVID-19 or Coronavirus Disease-19 is a virus that infects the respiratory tract with mild to severe symptoms. The government enforces a regulation, namely the Penerapan Pembatasan Kegiatan Masyarakat (PPKM) to reduce the number of positive COVID 19. Pros and cons occur among the community. People usually express opinions on social media, such as Twitter. So that the public can express a public opinion about government policies regarding PPKM. From the public opinion on Twitter, we can analyze the sentiment. Sentiment analysis is used to determine whether a comment is negative or positive. In this case, sentiment analysis determines public comments on PPKM regulations on Twitter social media. The Support Vector Machine (SVM) algorithm is used to find out the sentiment in tweet comments. There are 500 Twitter commentary documents with a comparison of training data and data of 80% and 20%. Parameter search was conducted with the best results on the degree kernel polynomial value 3, the learning rate value 0.0001, and the Complexity 1 value. The results of the K-Fold Cross Validation test using the best parameters, namely the average accuracy of 77.2%, precision 83.3%, recall 68.7%, and F measure 75.11%.
Analisis Sentimen Komentar pada Media Sosial Twitter tentang PPKM Covid-19 di Indonesia dengan Metode Naive Bayes Aldi Bagus Sasmita; Bayu Rahayudi; Lailil Muflikhah
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

The ongoing spread of COVID-19 brings many changes, including Indonesia country. The proper handling for each sector to deal with this pandemic is still ongoing with various efforts including the establishment of policies to intercept the expansion of the virus. The government's policy-setting effort to cut the spread of COVID-19 is the Pemberlakuan Pembatasan Kegiatan Masyarakat, known as PPKM. This policy received various responses from the public through many media, especially digital media through personal social media accounts, especially in the form of comments. Twitter social media platform becomes an effective argumentation space, especially for the phenomenon that is being discussed a lot, including the PPKM policy. Various responses in the form of comments need to be analyzed by sentiment with a classification of positive or negative responses that acts as a sentence filter. The reason of this reasearch on the Naive Bayes method is to determine the value of accuracy in the classification of public sentiment on Twitter social media in response to the PPKM policy carried out by the government in Indonesia. The consequence of the research conducted this time stated that the Naive Bayes Classifier algorithm using the NLTK Filtering Library has the highest accuracy such as Tala Filtering Library and the Combined Stopword Filtering Library. The accuracy results obtained by the NLTK Library Filtering is 77.2%, Tala Filtering Library is 76,6%, and The Combined Stopword Filtering Libray is 75,2%.
Klasifikasi Topik Skripsi pada Skripsi Mahasiswa FILKOM Universitas Brawijaya Periode 2015-2019 menggunakan Algoritme Support Vector Machine Dimas Adi Syahbani Achmad Putra; Bayu Rahayudi; Achmad Ridok
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

A thesis is a scientific paper that discusses a particular topic or field, written and designed by a student with the guidance of a supervisor as a condition for obtaining a bachelor's degree. In the last five years, various titles and thesis topics have been designed by students of the Faculty of Computer Science, Universitas Brawijaya. The research data used is the title of the thesis with labeling based on the thesis topic of FILKOM UB students on the UB repository website. The topic class of the title of this classification thesis consists of areas of interest in FILKOM, namely Image Processing, Software Engineering, Decision Support Systems. The data used are 225 data with each topic totaling 75 data. This study aims to determine the classification of the thesis title data that has been labeled with the topic with the Support Vector Machine Algorithm using the Radial Basis Function kernel and the selection of Chi-Square features. The results of the system evaluation obtained by testing applying 10-fold cross-validation and 50% of the features used with Chi-Square are accuracy = 0.88, recall = 0.9063, precision = 0.881, f1-score = 0.8789 with the best parameter values ​​from the Support Vector Machine namely parameter (sigma) RBF kernel = 2.5, parameter (lambda) = 0.3, parameter (gamma) = 0.001, parameter C (complexity) = 0.1, parameter (epsilon) = 0.00001, and iteration = 75.
Optimasi Rute Multiple Travelling Salesman Problem Distribusi Produk PT Indomarco Adi Prima (Stock Point Nganjuk) menggunakan Algoritme Ant Colony Optimization dan Algoritme Genetika Bisma Anassuka; Imam Cholissodin; Bayu Rahayudi
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

PT. Indomarco Adi prima (Stock Point Nganjuk) is a company engaged in the distribution sector. Good transportation and distribution are important in a distribution company, where products can be delivered to consumers in good conditions, at the designated place and on time. Product distribution from PT. Indomarco Adi Prima (Stock Point Nganjuk) to consumers through stores on a large scale is a fairly complex problem, because there are many locations that must be visited. This problem and involves many sales called the Multiple Traveling Salesman Problem. Inappropriate route selection can reduce efficiency in the distribution process. So, it is necessary to make optimization to get the optimal route. This research is an attempt to optimize the route using the hybrid ant colony optimization (ACO) algorithm and genetic algorithm, so that it can determine the shortest route that will be passed by sales to retail stores. The test results show that the hybrid ant colony optimization (ACO) algorithm and genetic algorithm are able to produce a 74,3% better route than the previous route with a total distance difference of 709.219km. The optimal parameters obtained are the maximum ACO iteration of 100, the number of GA generations of 20, the number of ants is equal to the point of each salesman, a combination of α= 0.4 and β= 0.8, a combination of Cr= 1, and Mr= 0.6, so that the total distance average is 244.849 km and the fitness value is 0.040841.
Analisis Sentimen Masyarakat terhadap Isu New Normal Scenario berdasarkan Opini dari Twitter menggunakan Algoritma Naive Bayes Classifier Muhammad Nurhuda Rusardi; Bayu Rahayudi; Putra Pandu Adikara
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

The COVID-19 pandemic has spread to various countries around the world, the country of Indonesia has not escaped the ferocity of the COVID-19 pandemic, the rate of positive cases in Indonesia has experienced an increase. The government has taken various ways to suppress positive cases of COVID-19, one of which is the implementation of the New Normal. Twitter is a social media that is widely used by Indonesian people in many ways. Topics regarding the New Normal can appear on Twitter's trending topic feature because many Indonesians discuss the implementation of the New Normal in Indonesia, various opinions regarding the implementation of the New Normal scenario in Indonesia will be obtained using text mining techniques by using the Twitter API crawling, the texts data must go through data cleaning process to make easy classification process by using Naive Bayes Classifier method. At first, the data have been labelled to ease the sentiment analysis process. The last process is classification process by using Naive Bayes Classifier method. After the classification process, the predicted sentiments are evaluated using 5-fold cross validation and confusion matrix. This research yields average accuracy 0,86, precision, 0,86, recall 0,86, and f-measure 0,86.
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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Abstract

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%.
Analisis Sentimen Opini Masyarakat terhadap Pelayanan Rumah Sakit Umum Daerah menggunakan Metode Support Vector Machine dan Term Frequency - Inverse Document Frequency Jasico Da Comoro Aruan; Bayu Rahayudi; Achmad Ridok
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

Regional General Hospital is a health service institution owned by the local government. The services provided by hospitals are required to always make changes, so that the services can be in accordance with the expectations and needs of the community. Hospitals as one of the institutions that have the function of providing health services must of course be in accordance with predetermined standards. Regarding improving the quality of hospital services, the government as the main actor who plays a direct role both to be responsible and to plan, regulate, organize, foster, and supervise the implementation of improving the quality of health in this case through several public policy products has explicitly discussed and regulated everything related to achieving this. Based on the needs of hospitals in assessing public sentiment as an important point in the accreditation process of hospitals, it is necessary to analyze the sentiments of public opinion towards hospitals. To perform sentiment analysis, the method used in this research is Support Vector Machine and word weighting uses Term Frequency-Inverse Document Frequency. Testing using Cross Validation with 132 training data and 33 test data resulted in an accuracy value of 88% and recall of 87.5%, precision of 90% and f-measure of 87.5%. This value is obtained when using the parameters C=1 and Itermax=1000.
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,
Co-Authors Abdullah Harits Abdurrahim, Ahmad Azmi Abhiram, Muhammad Tegar Achmad Choirur Roziqin Achmad Ridok Adam Hendra Brata Ade Wahyu Muntizar Adi Mashabbi Maksun Adi Maulana Rifa'i Adi, Tri Adinda Putri, Lintang Gladyza Adinugroho, Sigit Aditya Septadaya Aditya, Nathanael Chandra Afif Ridhwan Ageng Wibowo Agus Wahyu Widodo Agus Wahyu Widodo, Agus Wahyu Ahmad Afif Supianto Ahmada Bastomi Wijaya Aldi Bagus Sasmita Aldous Elpizochari Alfarisi, Raihan Alfian Reza Pahlevi Alip Setiawan Allifira Andara Hasna Alvian Akmal Nabhan Amaliah Gusfadilah Andhi Surya Wicaksana Andro Subagio Angga Wahyudi Kurniawan Pratama Anggi Novita Sari Anne Diane Rachmadani Arif Indra Kurnia Arina Rufaida Aristides, Joy Vianoktya Arjun Nurdiansyah Arsan, Danish Alif Arsti Syadzwina Fauziah Audia Refanda Permatasari Ayezha Halidar Putri Irwanda Ayuda Dhira Pramadhari Bachtiar, Harsya Bafagih, Novel Bagas Laksono Bastian Dolly Sapuhtra Basuki, Akbar Lucky Bisma Anassuka Brillian Aristyo Rahadian Buce Trias Hanggara Budi Darma Setiawan Cahyo Gusti Indrayanto Candra Dewi Candra Dewi Chandra, Ardhya Khrisna Christina Sri Ratnaningsih Cindy Cynthia Nurkholis Dahnial Syauqy Daniel Agara Siregar Dany Primanita Kartika Sari Dany Primanita Kartikasari Davia Werdiastu Dedy Surya Pradana Dese Narfa Firmansyah Devi Nazhifa Nur Husnina Dhaifa Farah Zhafira Dhimas Wida Syahputra Dhiva Mustikananda Diamanta, Ananda Dian Eka Ratnawati Dian Ratnawati Dian Sisinggih Dimas Adi Syahbani Achmad Putra Djoko Pramono Djoko Pramono Dloifur Rohman Alghifari Dwi H Sulistyarini Dwija Wisnu Brata Dwija Wisnu Brata Dwija Wisnu Brata Dzulkarnain, Tsania Dzulkarnain, Tsania - Edgar Maulana Thoriq Edy Santoso Eko Wahyu Hidayat Ellita Nuryandhani Ananti Ema Rosalina Eni Hartika Harahap Fadilah Islamawan, Adam Faiz Abiyandani Faizatul Amalia Fajar Pangestu Faradila Puspa Wardani Faris Febrianto Farizky Novanda Pramuditya Fauzia, Sri Febrina Sarito Sinaga Ferina Kusuma Anjani Ferry Jiwandhono Fitria Yesisca Gagas Budi Waluyo Gani Kharisma Wardana Gilang Pratama Gusti Reza Maulana Haidar Azmi Rabbani Hanggara , Buce Trias Hardyan Zalfi Harris Imam Fathoni Haryuni Siahaan Hayunanda, alanela ganagisarama Heryadi Mochamad Ramdani Hidayati, Chofifa Hilmy Ramadhan, Achmad Zhafran Huda Minhajur Rosyidin Husalie, Levin Vinnu Imam Cholisoddin Imam Cholissodin Imam Cholissodin Immanuel Tri Putra Sihaloho Indriati Indriati Indriati Indriati Indriati, Indriati - Intan Sartika Eris Maghfiroh Irany Windhyastiti Irwan Shofwan Issa Arwani Issa Arwani Ivan Agustinus Jasico Da Comoro Aruan Jefri Hendra Prasetyo Jonemaro, Eriq Muhammad Adams Jumerlyanti Mase K., Anggraeni Dwi Kautsar, Ahmad Izzan Kevin Nastatur Chatriavandi Khairul Rizal Krishna Febianda Ksatria, Willyan Eka Kurnianingtyas, Diva Laila Diana Khulyati Lailil Muflikhah Liwenki Jus'ma Olivia M. Ali Fauzi M. Ali Fauzi M. Attala Reza Syahputra Made Tri Ganesha Madjid, Marchenda Fayza Marji Marji Marpaung, Veronika Oktafia Marwa Mudrikatussalamah Maulana Syahril Ramadhan Hardiono Maulana, M. Ighfar Maulidhia, Abrilian Meriza Nadhira Atika Surya Michael Eggi Bastian Mochammad Ilman Asnada Mohammad Aditya Noviansyah Mohammad Setya Adi Fauzi Mohammad Zahrul Muttaqin Muh. Arif Rahman Muhammad Ferian Rizky Akbari Muhammad Hidayat Muhammad Ikhsan Nur Muhammad Jibril Alqarni Muhammad Kevin Sandryan Muhammad Nadzir Muhammad Nurhuda Rusardi Muhammad Razan Nadhif Muhammad Reza Utama Pulungan Muhammad Shidqi Fadlilah Muhammad Syahputra Muhammad Tanzil Furqon Mukhtar Darma Hidayat, Alif Ahmad Muthia Maharani Muzayyani, Muhammad Farid Nadiah Nur Fadillah Ramadhani Najihah, Siti Waheeda Nanang Yudi Setiawan Nanang Yudi Setiawan Nanda Alifiya Santoso Putri Nashihul Ibad Al Amin Niken Hendrakusuma Wardani, Niken Hendrakusuma Nilna Fadhila Ganies Novanto Yudistira Nur M. F. Dinia Nurfadhilah, Rakhmad Giffari Nuril Haq, Muhammad Nurizal Dwi Priandani Nurul Hidayat Nurul Ihsani Fadilah Obed Manuel Silalahi Panjaitan, RE. Miracle Pascad Wijanata, Ida Bagus Prakosa, Wira Zeta Pramudita, Julina Larasati Primayuda, Averil Priscillia Vinda Gunawan Purnomo, Welly Putra Pandu Adikara Putranto, Rezky Donny Putri Ratna Sari Putri, Firda Qhafari, Abi Al Qoid A Fadhlurrahman Rafli, Mohammad Ali Rahinda, Muhammad Abiyyi Ramadhani, T. Zalfa Randy Cahya Wihandika Rani Metivianis Rasif Nidaan Khofia Ahmadah RE. Miracle Panjaitan Reinaldi Guista Pradana Ismail Reiza Adi Cahya Renaldi Muhammad Revan Yosua Cornelius Sianturi Reyhan Dzickrillah Laksmana Reza Aprilliana Fauzi Rheza Raditya Andrianto Rifwan Hamidi Riswan Septriayadi Sianturi Riza Rizqiana Perdana Putri Rizky Ardiawan Rizky Nuansa Nanda Permana Rohimatus Sholihah Roisul Setiawan Roma Akbar Iswara Rudianto Raharjo Safa S Istafada Saifurrijaal, Muchammad Salsabila, Dhea Rani Sandi Dewo Rahmadianto Satrio Agung Wicaksono Sekeon, Yerobal Gustaf Setiana, Maya Setiawan, Roisul Shafira Eka Aulia Putri Slamet Thohari Sofi Hidyah Anggraini Sugeng Santoso Sugiarto S Sugiono Sugiono Sukmawati, Annisa Sultan Saladdin Sultan, Muhammad Attharsyah Firdaus Supraptoa Supraptoa Tanica Rakasiwi Tasya Agiyola Teri Kincowati Tri Astoto Kurniawan Trias Hanggara, Buce Trio Pamujo Wicaksono Ulva Febriana Umar Basher, Nizar Umu Khouroh Vivilia Putri Agustin Wahyu Bimantara Wayan Firdaus Mahmudy Welly Purnomo Welly Purnomo Weni Agustina Wenny Ramadha Putri Wibowo, Dhimas Bagus Bimasena Wicaksono, Satrio A. Widhy Hayuhardhika Nugraha Putra Widhy Hayuhardika Nugraha Putra Widodo, Ibnu Sam Widyadhana, Fawwaz Kumudani Wiku Galindra Wardhana Wisnu Brata, Dwija Yahya, Faiz Yesaya Sergio Vito Putranta Yudi Setiawan, Nanang Yuita Arum Sari Yusuf Afandi Zhafira, Dhaifa Farah