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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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Perbandingan Ruang Warna RGB dan HSV dalam Klasifikasi Kematangan Biji Kopi Haidar Azmi Rabbani; Muh. Arif Rahman; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 6 (2021): Juni 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Coffee is one of the most popular drinks in the world, and is favored by many group, including in Indonesia. The taste image of coffee has the characteristics of each type of coffee. One thing that influences the image of the taste of coffee is the maturity of the coffee beans. For this reason, an introduction to the level of maturity of coffee beans is carried out by utilizing the color space of the coffee bean image. The research conducted utilizes a comparison of the extraction of RGB and HSV color spaces as the first test and the addition of LBP texture extraction in the second test. Based on tests carried out on 500 images of coffee beans, the best accuracy was 99.2% in the first test and 98.2% in the second test. Testing using a backpropagation neural network.
Pengelompokkan Kondisi Komputer pada Bank X di Seluruh Indonesia Menggunakan Metode K-Medoids Clustering Muthia Maharani; Dian Eka Ratnawati; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 5 (2021): Mei 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Bank X is one of the largest public banks in Indonesia. With the banking process running up to the operational process of Bank X which run every day for 24 hours, a very good quality computer is needed. So the process of upgrading computer must always be done. The large number of computers at Bank X makes the process of upgrading computers is one of Bank X's biggest expenses. Other than that, in several work units at Bank X, the process of upgrading computer is still not effective. From these problems, the research will be conducted in the form of grouping computer conditions at Bank X all over Indonesia using the K-Medoids Clustering method. This research was conducted to classify which computers are really need, need enough, and which computers do not need to upgrade. The results of this grouping are that there are 237 computer in cluster 0 no need to upgrade, 126 computer are in cluster 1 with a very need to upgrade, and 769 computer are in cluster 2 with condition good enough but need to be reviewed because it is quite necessary to do a computer upgrade. For testing using the Silhouette Coefficient, clustering with 2 clusters is the best because it has the highest silhouette score, which is 0.624684967. And also the test for amount of data which showed that 90% of the original data was the minimum presentation for data amount for accurate results. The results of the research will be given to Bank X as a recommendation to find out which computers need to be upgraded so that they can be followed up more quickly.
Optimasi Rute Distribusi Produk PT Indomarco Adi Prima (Stock Point Nganjuk) Dengan Algoritma K-Means Dan Ant Colony Optimization (K-ACO) Wahyu Bimantara; Bayu Rahayudi; Imam Cholissodin
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 6 (2021): Juni 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Product distribution companies require cost-effectiveness and efficiency, one of the supporting factors a determining the optimal distribution route. The distribution route is closely related to the Traveling Salesman Problem. In the distribution process from the warehouse or stock point, Nganjuk PT Indomarco Adi Prima has a Multiple Traveling Salesman Problem which involves more than one salesman in the distribution process. To solve MTSP problems, you can search for it by traveling to all possible routes. However, when there are more routes, more time is needed. This research is an effort to optimize the distribution route of PT Indomarco Adi Prima's Nganjuk stock point products using the K-Means and Ant Colony Optimization (K-ACO) methods, in which the K-Means method a used to divide MTSP problems into smaller problems than each problem. Then each of these problems will find the shortest route with ACO. In the tests carried out, K-ACO can save salesmen a traveling distance of 565.801 km. While testing using the Silhouette Coefficient, K-Means resulted in a 76.72% better solution when compared to the results of real sales trips. These results indicate that the use of K-ACO can minimize the total distance traveled from the problem.
Optimasi Rute Distribusi Produk Minuman dan Makanan pada Distributor Nestle (CV Forward Kediri) dengan Algoritma Ant Colony Optimization Allifira Andara Hasna; Bayu Rahayudi; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 7 (2021): Juli 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The distribution process at CV Forward Kediri involves more than one sales for the product delivery process. In this case, the route determination management from the distributor is very important so that the distribution process can be more optimal. The problem experienced by many salespeople in finding the closest route is known as the Multiple Traveling Salesman Problem. One of the optimization algorithms to solve the closest route-finding problem is the Ant Colony Optimization algorithm. This algorithm is algorithm that is inspired by groups of ant colonies in finding a path to get food. In this study, to determine the resulting solution from the Ant Colony Optimization algorithm, a comparison of the initial conditions with the system was carried out. By testing the parameters of Ant Colony Optimization, the optimal parameters are obtained, namely the iteration of 2000, the alpha value, the beta value of 0.1, the rho value of 0.3, and the tau value of 0.03. Based on the results of the comparison of the system using the Ant Colony Optimization algorithm, with an average fitness of 121.27 with the original condition of 179.42, it turns out that the results obtained by the system are much shorter than the original condition so that it can provide more optimal results.
Klasifikasi Tweets Masyarakat yang Membicarakan Layanan GoFood dan GoRide pada GoJek Dimedia Sosial Twitter Selama Masa Kenormalan Baru (New Normal) dengan Metode Naive Bayes Alvian Akmal Nabhan; Bayu Rahayudi; Dian Eka Ratnawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 7 (2021): Juli 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Twitter is a social media that has long been used and is still a trend today. On Twitter, a lot of users write an opinion on something that is currently being discussed and becomes a trend topic. Early May 2020 the world was shaken by the presence of Coronavirus Disease-19 which causes all life in all parts of the world to be constrained, especially the government sector which has an impact on economic activity has decreased. In Indonesian, a lot of companies have gone bankrupt and must terminate the employment. At that time, the transportation sector companies were the most affected is GoJek online transportation which was successful as a unicorn start-up. GoJek was badly hit by the implementation of the PSBB in various regions. Therefor, the community grouped tweets for existing services on GoJek in social media twitter during the pandemic and new normal . In this study case, the GoJek services used are GoFood and GoRide using Naive Bayes classification model with testing using cross validation and confusion matrix. From this classification, good accuracy result are obtained by testin with 10-fold with mean accuracy 0,94, precission 0,73, recall 0,72 f-measure 0,72.
Implementasi Algoritme Ant Colony Optimization untuk Optimasi Rute Distribusi Produk Kebutuhan Pokok dari Toko Sasana Bonafide Mojoroto Revan Yosua Cornelius Sianturi; Bayu Rahayudi; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 7 (2021): Juli 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Efficient work is a profitable job because it is free from certain problems, such as distance problems in the distribution process. Therefore, optimization is one of the solutions that can be relied on as an efficient way to solve a problem, such as the Ant Colony Optimization's algorithm (ACO) in optimizing the distribution route of goods or basic needs products at the Sasana Bonafide store. The optimization problem in this study utilized the concept of the Multi Traveling Salesman Problem (M-TSP) because it involved more than one distributor and had a single depot, which was the Sasana Bonafide store. This study utilized data on customers who lived in 34 different addresses. In this study, ACO succeeded in producing the best solution by combining parameter values to solve the distance optimization problem. The combination of the ACO parameter values utilized in this study, namely the control constant for the intensity of the ant pheromone trail was 1, the visibility control constant was 1, the evaporation constant for the ant pheromone trail was 0.1, and the number of iterations was 500. These parameters were utilized in system testing that tested four times using four different actual data and produced the best solution with each percentage, which was 31.56% produced a distance of 39.4 km, 23.25% produced a distance of 43.52 km, 23.66% produced a distance of 44.14 km, and 25.97% produced a distance of 39.97 km.
Optimasi Penjadwalan Pekerja Shift di Rumah Makan Cepat Saji (Fast Food Restaurant) menggunakan Algoritma Genetika (Studi Kasus: Warung Gunung di Kediri) Ellita Nuryandhani Ananti; Imam Cholissodin; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 7 (2021): Juli 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Fast food restaurants are one of the businesses in the culinary field that are developing very rapidly at this time. Labor plays an important role in providing services to buyers where it can also affect income and also support the economy of a restaurant business, one of which is Warung Gunung (Wagu) in Kediri. In Wagu itself, there is a different division of job desc for each group of workers. When scheduling manually, it also takes a long time and is prone to human error. Therefore, it is necessary to have computerized scheduling of workers to carry out production activities and services to consumers effectively and efficiently. In this study, the scheduling process is carried out using the Genetic Algorithm method starting from the representation of chromosomes to the worker code and division, then carrying out a one-cut point crossover and reciprocal exchange mutation process to get new offspring which are then used in the selection process using elitism selection for the next generation. Based on the results of the parameter testing that has been carried out, it produces the most optimal solution without any violation of shift worker scheduling by producing the largest average fitness value is 1 which is found in the population size of 520, the number of generations is 450, and the combination of cr and mr is 0,6:0.4.
Optimasi Extreme Learning Machine dengan Particle Swarm Optimization untuk Klasifikasi Penyakit Jantung Koroner Rasif Nidaan Khofia Ahmadah; Bayu Rahayudi; Yuita Arum Sari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 9 (2021): September 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Heart disease is the leading cause of death globally. Several factors that can trigger heart disease include smoking, blood pressure, diabetes, lifestyle, diet, and stress levels. The minimal number of health workers in Indonesia and the different abilities of each doctor in diagnosing patients with heart disease, so that a system is needed to automatically diagnose the disease which functions to assist doctors and overcome delays in inpatient treatment. This system is a classification system using the Particle Swarm Optimization method and the Extreme Learning Machine for the diagnosis of heart disease, where the Particle Swarm Optimization method is used to optimize the parameters of the Extreme Learning Machine. In the tests carried out, the system succeeded in providing an accuracy value of 86%. This also shows that the use of PSO-ELM can increase the accuracy value than using the ELM method only in diagnosing heart disease.
Klasifikasi Email berdasarkan Tingkat Kepentingannya dengan menggunakan Metode Naive Bayes (Studi Kasus : PT. Green Air Pacific Surabaya) Kevin Nastatur Chatriavandi; Bayu Rahayudi; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 9 (2021): September 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

PT. Green Air Pacific Surabaya has received an average of 400 - 700 messages per day. So that the incoming email will overlap each other, this can complicate the process of managing email messages that are considered important. This study classifies emails based on their importance using the Naive Bayes method. The word weighting method used is basically TF (Term Frequency) and then normalized to WIDF (Weighted Inverse Document Frequency) weighting. To get a better word index, word weighting is modified by adding word weight if the word is included in the list of predetermined terms. In addition, testing in this study was carried out on the email title, email content and email title with content. From the test results, it was found that the system classifies email data quite well. It can be proven on the highest performance results with an accuracy value of 98,67%, a precision of 100% and an f-measure of 98,99% on the parameters of using email headers, TF weighting, modified TF weighting, and modified WIDF weighting with 240 training data. In addition, the results of testing and data validation using k-fold cross validation also provide an average performance result that is not much different, namely an accuracy value of 95,56%, precision of 93,86% and f-measure of 96,81%..
Prediksi Trend Harga Saham Jangka Pendek berdasarkan Fitur Technical Analysis dengan menggunakan Algoritma Random Forest Michael Eggi Bastian; Bayu Rahayudi; Dian Eka Ratnawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 10 (2021): Oktober 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Stock trading is a daily activity carried out by a stock trader. A stock trader can perform this trading activity on a capital market. In the capital market, you can see a chart that depicts the price movement of a stock in a certain period, also known as "Price Trend". The most important characteristic of a price trend is volatile and irregular changes in direction. Due to its volatile and irregular nature, a problem arises in knowing where the price trend will move. Any mistake in predicting the direction of the trend can cause losses. This study implements the random forest algorithm as a solution model, and technical analysis as a predictive feature to minimize errors in predicting future stock price trends. Based on the test results, the combination of the random forest algorithm and technical analysis is able to minimize errors in predicting price trends with an accuracy of 84% and an f1 score of 88%.
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