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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Ilmu Komputer MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Jurnal Ilmiah Kursor Journal of Innovation and Applied Technology International Journal of Local Economic Governance Journal of Environmental Engineering and Sustainable Technology Jurnal Pembangunan dan Alam Lestari Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics Journal of Information Systems Engineering and Business Intelligence KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Knowledge Engineering and Data Science Jambura Law Review Indonesian Journal of Electrical Engineering and Computer Science International Journal of Engineering, Science and Information Technology Indexia Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) Bulletin of Culinary Art and Hospitality Bulletin of Social Informatics Theory and Application Jurnal ilmiah teknologi informasi Asia Signal and Image Processing Letters
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Fish Image Classification Using Adaptive Learning Rate In Transfer Learning Method Rizka Suhana; Wayan Firdaus Mahmudy; Agung Setia Budi
Knowledge Engineering and Data Science Vol 5, No 1 (2022)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um018v5i12022p67-77

Abstract

The existence of fish species diversity in coastal ecosystems which include mangrove forests, seagrass beds and coral reefs is one of the benchmarks in determining health in coastal ecosystems. It is certain that we must maintain, preserve and care for so that conservation efforts need to be carried out in water areas. Many experts at the Indonesian Fisheries and Marine Research and Development Agency often classify fish images manually, of course it will take a long time, therefore with today's developments they can use the latest technology.  One of the reliable techniques in terms of image classification is Convolutional Neural Network (CNN). As time goes by, of course, many people want fast learning and solving new problems faster and better, so transfer learning appears, which adopts part of CNN, the name is modified convolution layer. Observing the needs of experts in the field of marine conservation, the researchers decided to solve this problem by using transfer learning modifications. The transfer learning used is an architectural model from the pre-trained Mobilenet V2, which is known for its light computing process and can be applied to our gadgets and other embedded tools. The research image data used is 49.281 data of various sizes and there are 18 types of fish, in the pre-processing data there is a resize of the image to a size of 224x224 pixels. testing with the modified transfer learning architectural model obtained an accuracy score of 99.54%, this model is quite reliable in classifying fish images.
Hybrid Artificial Bee Colony and Improved Simulated Annealing for the Capacitated Vehicle Routing Problem Farhanna Mar'i; Hafidz Ubaidillah; Wayan Firdaus Mahmudy; Ahmad Afif Supianto
Knowledge Engineering and Data Science Vol 5, No 2 (2022)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um018v5i22022p109-121

Abstract

Capacitated Vehicle Routing Problem (CVRP) is a type of NP-Hard combinatorial problem that requires a high computational process. In the case of CVRP, there is an additional constraint in the form of a capacity limit owned by the vehicle, so the complexity of the problem from CVRP is to find the optimum route pattern for minimizing travel costs which are also adjusted to customer demand and vehicle capacity for distribution. One method of solving CVRP can be done by implementing a meta-heuristic algorithm. In this research, two meta-heuristic algorithms have been hybridized: Artificial Bee Colony (ABC) with Improved Simulated Annealing (SA). The motivation behind this idea is to complete the excess and the lack of two algorithms when exploring and exploiting the optimal solution. Hybridization is done by running the ABC algorithm, and then the output solution at this stage will be used as an initial solution for the Improved SA method. Parameter testing for both methods has been carried out to produce an optimal solution. In this study, the test was carried out using the CVRP benchmark dataset generated by Augerat (Dataset 1) and the recent CVRP dataset from Uchoa (Dataset 2). The result shows that hybridizing the ABC algorithm and Improved SA could provide a better solution than the basic ABC without hybridization.
Riset Optimasi Industri Manufaktur Menggunakan Metode Meta-Heuristic Wayan Firdaus Mahmudy
Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) 2023: SNESTIK III
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/p.snestik.2023.4428

Abstract

Food Menu Recommendations Based on Recommended Dietary Allowances using Genetic Algorithm Muhammad Ardhian Megatama; Wayan Firdaus Mahmudy; Edy Santoso
Bulletin of Culinary Art and Hospitality Vol. 1 No. 2 (2021)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (374.666 KB) | DOI: 10.17977/um069v1i22021p70-77

Abstract

Nowadays, there are still often unbalanced nutritional problems such as overnutrition or malnutrition. Many factors can affect it, one of which is an unbalanced diet. One solution that can be done is a system for optimizing nutritional needs. In this study, the method used for optimization is genetic algorithms. Genetic algorithms are one of the metaheuristic methods that are often used for optimization problems. A particular chromosome representation is designed to provide suitable solutions. The system can provide food recommendations with nutrients close to a person's nutritional needs by using the genetic algorithm. Based on the test results obtained, the difference in nutrition from food recommendations with nutritional needs is below 5 percent.
Penyelesaian Penjadwalan Flexible Job Shop Problem Menggunakan Real Coded Genetic Algorithm M Chandra Cahyo Utomo; Wayan Firdaus Mahmudy; Marji Marji
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 1 (2017): Januari 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (635.876 KB)

Abstract

Scheduling is a problem that is quite difficult if it should be prosecuted in quick time and will be more troublesome if the arrangement is scheduled for something uncertain with many options that require a more complicated decision. Jobshop scheduling model is one example of scheduling problems that were encountered in the manufacturing industry. Completion of complex problem and the best solution can only be obtained by trying all possibilities. Genetic algorithm is one of algorithms which can provide complex solutions to problems within acceptable time rationally, so that it can be applied to the Flexible Job Shop problem. Genetic Algorithm is able to take into account by trying to exchange arrangements provided and/or try to replace the array directly (crossover and/or mutation).
Implementasi Modified K-Nearest Neighbor Dengan Otomatisasi Nilai K Pada Pengklasifikasian Penyakit Tanaman Kedelai Tri Halomoan Simanjuntak; Wayan Firdaus Mahmudy; Sutrisno Sutrisno
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 2 (2017): Februari 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (554.805 KB)

Abstract

Various diseases and pest attacks can cause serious problems to the soybean crop. One threat to the soybean crop development research centers and is the developer of the plant pests. Pests can reduce soybean yields by 80 % even if no serious control. Classification is needed to determine the types of diseases that attack soybean plants. This research use of Soybean Disease Data Set consisting of 266 training data and desktop-based applications to be built by implementing the algorithm Modified K - Nearest Neighbor, the parameter value of K is determined by the system using brute force methods to find the best K value. Each value of K with accuracy the best results will be recorded and used as the parameter value of K in the process of testing new data. K values in this method to define the number of nearest neighbors used for the classification process. The test results showed that the value of the parameter K affects the classification results and the accuracy result. Average accuracy tends to decrease with the addition of the value of k , while increasing the number of training data also accompanied by an increase in the accuracy of the results, for training data with imbalanced class accuracy values decreased with increasing amount of data. The results of the highest accuracy on the test at 100 % with a value of k = 1 and an average accuracy of 5 times the experimental is 98.83 %.
Optimasi Pemilihan Pekerja Bangunan Proyek Pada PT. Citra Anggun Pratama Menggunakan Algoritma Genetika Arviananda Bahtiar; Wayan Firdaus Mahmudy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 2 (2017): Februari 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (427.501 KB)

Abstract

PT. Citra Anggun Pratama is a company engaged in construction, one of their human resources are the builders. Problems often encountered in the company is the incompatibility of builder election to the needs of corporate projects that resulted in disruption of the project. Genetic algorithm is one type of Evolutionary Algorithms (EAs) are the most popular and commonly used because of their ability to solve various complex problems, so it can be applied to find optimal solutions to the problems of election workers. Process of finding solutions in this study begins with the generation of chromosome accommodated in the population, then carried the crossover and mutation rate to get the new generation then be selected to get the best solution. Based on test results obtained best results on the population size of 420, 150 iterations, combination of Mr 0.5 and Cr 0.5 which is optimal or near-optimal results. The result is a recommendation in the way of the builder selection.
Penentuan Portofolio Saham Optimal Menggunakan Algoritma Genetika Rinda Wahyuni; Wayan Firdaus Mahmudy; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 1 (2017): Januari 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (673.15 KB)

Abstract

In making investments investors often faced with two things, return expectation and risk rate. Therefore to reduce the risk rate investors diversifying by combining securities in investment, or commonly referred to a stock portfolio. This research implements genetic algorithm to determine the proportion of stocks to generate optimum return expectation with risk rate that can be justified. Based on the test result, genetic algorithm can determine the stocks proportion with greater return expectation and risk rate is smaller than manual calculation using single index model. The largest fitness is 0,356522 in exercise condition of genetic algorithm parameter with population size is 100, the number of generations is 100, crossover rate 0,3, and mutation rate 0,7.
Optimasi Komposisi Pakan Sapi Perah Menggunakan Algoritma Genetika Durrotul Fakhiroh; Wayan Firdaus Mahmudy; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 1 (2017): Januari 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (802.777 KB)

Abstract

Hambatan terbesar yang dialami oleh peternak sapi perah adalah penggunaan komposisi pakan yang tidak efisien. Dalam sudut pandang ekonomi, biaya untuk pembelian pakan ternak merupakan biaya tertinggi dalam usaha peternakan, sehingga harus ditekan serendah mungkin untuk memaksimalkan pendapatan dengan tetap memperhatikan nutrisi yang dibutuhkan oleh sapi perah. Agar dapat mencapai dua hal tersebut dilakukan optimasi terhadap ransum agar dapat memenuhi kebutuhan nutrisi dengan biaya yang minimal. Algoritma genetika merupakan salah satu metode yang sesuai untuk memecahkan permasalahan optimasi. Representasi yang digunakan adalah real code dimana setiap kromosom mewakili bobot dari bahan pakan, dan panjang kromosom tergantung dari banyaknya bahan pakan. Metode crossover yang digunakan adalah extended intermediete, proses mutasi menggunakan metode random mutation, sedangkan elitism adalah metode yang digunakan dalam proses seleksi. Berdasarkan hasil pengujian yang telah dilakukan, diperoleh parameter optimal yaitu pada populasi 100, generasi 200, serta kombinasi cr dan mr sebesar 0.3 dan 0.3. Hasil akhir yang didapatkan berupa rekomendasi komposisi ransum dengan biaya yang minimal dan kebutuhan nutrisi sapi perah tetap terpenuhi.
Implementasi Algoritma Nearest Insertion Heuristic dan Modified Nearest Insertion Heuristic Pada Optimasi Rute Kendaraan Pengangkut Sampah (Studi Kasus: Dinas Kebersihan dan Pertamanan Kota Malang) Dea Widya Hutami; Wayan Firdaus Mahmudy; Marji Marji
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 2 (2017): Februari 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (385.331 KB)

Abstract

Sebagai kota yang sedang tumbuh Kota Malang mengalami berbagai masalah, salah satu aspek yang sedang menjadi masalah kota adalah masalah kebersihan kota. Produksi sampah semakin tahun semakin meningkat seiring dengan peningkatan penduduknya. Oleh karena itu, dibutuhkan pengelolaan sampah yang efektif dan efisien terutama dalam hal pengangkutan sampah. Namun pengangkutan sampah di Kota Malang dirasa masih kurang karena belum adanya rute khusus untuk truk-truk pengangkut sampah, sehingga waktu yang dibutuhkan untuk mengangkut seluruh sampah dari 70 TPS ke TPA membutuhkan waktu dan biaya bahan bakar yang cukup boros. Dari perbandingan antara metode Nearest Insertion Heuristic dengan metode modifikasinya, menunjukkan bahwa metode Nearest Insertion Heuristic menghasilkan jarak yang lebih pendek. Hasil terbaik didapatkan apabila dari 35 truk pengangkut sampah, urutan jalan truk yang digunakan adalah 18 truk berkapasitas 8 m³ kemudian 17 truk berkapasitas 6 m³.
Co-Authors A.N. Afandi Abdul Latief Abadi Abdul Latief Abadi Achmad Arwan Achmad Basuki Achmad Ridok Adimoelja, Ariawan Aditama, Gustian Adyan Nur Alfiyatin Agi Putra Kharisma, Agi Putra Agung Mustika Rizki Agung Mustika Rizki, Agung Mustika Agung Setia Budi Agus Naba Agus Wahyu Widodo Agus Wahyu Widodo Agus Wahyu Widodo, Agus Wahyu Ahmad Afif Supianto Ahmad Afif Supianto Ahmad Afif Supianto Aji Prasetya Wibawa Al Khuluqi, Mabafasa Alauddin, Mukhammad Wildan Alfiani Fitri Alfita Rakhmandasari Alfiyatin, Adyan Nur Alqorni, Faiz Amalia Kartika Ariyani Amalia Kartika Ariyani Amalia Kartika Ariyani Anantha Yullian Sukmadewa Andi Kurniawan Andi Maulidinnawati A K Parewe Andi Maulidinnawati A. K. Parewe Andreas Nugroho Sihananto Andreas Pardede Andreas Patuan G. Pardede Andrew Nafalski Angga Vidianto Aprilia Nur Fauziyah Aprilia Nur Fauziyah Arief Andy Soebroto Arinda Hapsari Achnas Armanda, Rifki Setya Arviananda Bahtiar Arya, Putu Bagus Asyrofa Rahmi Asyrofa Rahmi Asyrofa Rahmi Asyrofa Rahmi Asyrofa Rahmi, Asyrofa Bagus Priambodo Bayu Rahayudi Binti Robiyatul Musanah Budi Darma Setiawan Burhan, M.Shochibul Cahya, Reiza Adi Cahyo Prayogo, Cahyo Candra Dewi Candra Fajri Ananda Cleoputri Yusainy Darmawan, Abizard Hashfi Dea Widya Hutami Dhaifullah, Afif Naufal Diah Anggraeni Pitaloka Didik Suprayogo Dinda Novitasari Dinda Novitasari, Dinda Diny Melsye Nurul Fajri Dita Sundarningsih Durrotul Fakhiroh Dyan Putri Mahardika Edi Satriyanto Edy Santoso Eko Widaryanto Elta Sonalitha Ervin Yohannes Evi Nur Azizah Fadhli Almu’iini Ahda Fais Al Huda Fajri, Diny Melsye Nurul Fatchurrochman Fatchurrochman Fatwa Ramdani, Fatwa Fauzi, Muhammad Rifqi Fauziatul Munawaroh Febriyana, Ria Fendy Yulianto Fitra Abdurrachman Bachtiar Fitri Anggarsari Fitria Dwi Nurhayati Gayatri Dwi Santika Ghozali Maski Grady Davinsyah Gusti Ahmad Fanshuri Alfarisy Gusti Ahmad Fanshuri Alfarisy, Gusti Ahmad Fanshuri Gusti Eka Yuliastuti Hafidz Ubaidillah Hamdianah, Andi Hanggara , Buce Trias Herman Tolle Hernando, Deo Heru Nurwarsito Hidayat, Luthfi Hilman Nuril Hadi Ida Wahyuni Imada Nur Afifah Imam Cholisoddin Imam Cholissodin Imam Cholissodin Imam Cholissodin Indriati Indriati Irvi Oktanisa Ishardita Pambudi Tama Ismiarta Aknuranda Jauhari, Farid Khozaimi, Ach. Kukuh Tejomurti, Kukuh Kuncahyo Setyo Nugroho Kuncahyo Setyo Nugroho Kurnianingtyas, Diva Lily Montarcih Limantara M Chandra Cahyo Utomo M Fadli Ridhani M Shochibul Burhan, M Shochibul M. Shochibul Burhan M. Zainal Arifin Mabafasa Al Khuluqi Mar'i, Farhanna Marji Marji Mayang Anglingsari Putri, Mayang Anglingsari Mochamad Anshori Moh. Khusaini Moh. Sholichin Moh. Zoqi Sarwani Mohammad Zoqi Sarwani Mohammad Zoqi Sarwani, Mohammad Zoqi Mu’asyaroh, Fita Lathifatul Muh. Arif Rahman Muhammad Ardhian Megatama Muhammad Faris Mas'ud Muhammad Halim Natsir Muhammad Isradi Azhar Muhammad Khaerul Ardi Muhammad Noor Taufiq Muhammad Rivai Muhammad Rofiq Nadia Roosmalita Sari Nadia Roosmalita Sari Nadia Roosmalita Sari Nadya Oktavia Rahardiani Nashi Widodo Ni Wayan Surya Wardhani Nindynar Rikatsih Novanto Yudistira Novi Nur Putriwijaya Nurizal Dwi Priandani Nurul Hidayat Oakley, Simon Oktanisa, Irvi Philip Faster Eka Adipraja Prayudi Lestantyo Purnomo Budi Santoso Putra, Firnanda Al Islama Achyunda Putri Hasan, Vitara Nindya Putu Indah Ciptayani Qoirul Kotimah Rachmansyah, Ghenniy Rachmawati, Christina Rani Kurnia Rayandra Yala Pratama, Rayandra Yala Retno Dewi Anissa Riani, Garsinia Ely Rifa’i, Muhaimin Rikatsih, Nindynar Rinda Wahyuni Rizal Setya Perdana Rizal Setya Perdana Rizdania, Rizdania Rizka Suhana Rizki Ramadhan Rody, Rafiuddin Ruth Ema Febrita Ryan Iriany S, M Zaki Samaher . Saragih, Triando Hamonangan Sari, Nadia Roosmalita Sari, Nadia Roosmalita Selly Kurnia Sari Setyawan Purnomo Sakti Sudarto Sudarto Sukarmi Sukarmi, Sukarmi Sulistyo, Danang Arbian Sutrisno . Sutrisno Sutrisno Syafrial Syafrial Syafrial Syafrial Syaiful Anam Syandri, Hafrijal Tirana Noor Fatyanosa, Tirana Noor Titiek Yulianti Titiek Yulianti Titiek YULIANTI Tomi Yahya Christyawan Tri Halomoan Simanjuntak Ullump Pratiwi Utaminingrum, Fitri Utomo, M. Chandra Cahyo Vivi Nur Wijayaningrum Wahyuni, Ida Widdia Lesmawati Windi Artha Setyowati Yeni Herawati Yogi Pinanda Yogie Susdyastama Putra Yudha Alif Aulia Yudha Alif Auliya Yudha Alif Auliya, Yudha Alif Yulia Trianandi Yusuf Priyo Anggodo Yusuf Priyo Anggodo Yusuf Priyo Anggodo Yusuf Priyo Anggodo, Yusuf Priyo