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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 The International Journal of Accounting and Business Society 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 Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE) 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 Jurnal Pengabdian Masyarakat Teknologi Informasi dan Informatika
Wayan Firdaus Mahmudy
Brawijaya University
Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Optimasi Algoritme Genetika Untuk Memaksimalkan Laba Pembangunan Perumahan Muhammad Faris Mas'ud; Imam Cholisoddin; Wayan Firdaus Mahmudy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Residence is a basic need. The main function of the residence is for a place to rest, security and family activities. Residential development highly demand along High population growth in the Malang city. when building homes, developers always prioritize the benefits in every construction without reducing the quality of the building. House construction requires human resources and some limited material, therefore genetic algorithms will be very helpful in terms of profit-seeking search. Based on several other Genetic Algorithm studies, this algorithm produces the expected solutions such as: hijab profit optimization, optimization of efficient distribution of goods and optimization of selection of targeted building workers. In accordance with the tests performed using data from Margobasuki Residence, obtained the optimal amount of benefits.
Penerapan Metode Decision Tree dan Algoritme Genetika Untuk Klasifikasi Risiko Hipertensi Selly Kurnia Sari; Wayan Firdaus Mahmudy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Hypertension is one of the third most deadly diseases after stroke and tuberculosis which reached 6.7% of the total age in Indonesia. This shows that hypertension in Indonesia needs serious attention as an effort to deal with this problem. Handling is needed as a step in early detection of hypertension. In relation to the classification for detection of hypertension, one method that can be used is the Decision Tree (DT). But in the previous study DT method produced a fairly low accuracy. To optimize the accuracy of the DT method, Genetic Algorithm (GA) is used. GA is used to generate new rules. To find out the difference in the results of accuracy, a comparison test of DT-C4.5 and DT-GA is conducted. The test uses the same test data. The test results show the DT-GA algorithm produces the highest average accuracy of 84%. While the DT-C4.5 algorithm produces the highest average accuracy of 70,5%. The best parameters to produce the best accuracy are population size 60, Cr = 0,3, Mr = 0,7, with the maximum number of generations used is 10. From the results of these tests it can be concluded that GA can be used to generate new rules from DT
Optimasi Kebutuhan Gizi Untuk Ibu Hamil Dengan Menggunakan Hybrid Algoritma Genetika dan Simulated Annealing Binti Robiyatul Musanah; Wayan Firdaus Mahmudy; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 4 (2019): April 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Nutritional needs are very necessary for pregnant women. Good nutrition is balanced nutrition and according to needs. If the needs of pregnant women are not suitable can experience Chronic Energy Deficiency with these problems, a system is needed to fulfill the nutrition of pregnant women who can provide solutions in the form of food ingredients in accordance with the method of Hybrid Genetic Algorithms and Annealing Simulation. In the process of solving this problem at Simulated Annealing or Genetic Algorithm. This hybrid process is in a crossover process using a single intersection, mutation insertion for the mutation process and the use of elits in the selection and simulation of Annealing. The previous test results obtained parameters with the Hybrid GA and SA method obtaining the best parameter value which is equal to 100 (population size) fitness which obtained an average of 0.06268, the value of 105 (generation) obtained by average fitness0. 06823, i 4 with a fitness value of 0.6, the average is 0.06792, and the average temperature with a value of 1 and apha is 0.5 obtained by the best fitness with an average of 0.06800 along with 0.08876. The hybridization suitability of GA and SA reached 0.08804 higher than the average GA suitability value of 0.05519 and SA suitability which was 0.04382 with a specified time of 1 minute and the requirements generated from the system were insufficient for the nutritional needs of the pregnant women.
Optimasi Bobot Awal Extreme Learning Machine menggunakan Algoritme Genetika untuk Klasifikasi Penanganan Human Papilloma Virus Rizki Ramadhan; Wayan Firdaus Mahmudy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 6 (2019): Juni 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Human Papilloma Virus is a virus that causes warts in humans. There are so many types of treatment for this virus, the most common types of treatment are immunotherapy and cryotherapy. The symptoms that appear in the patient are almost similar, so that proper handling is needed. Based on this, the Extreme Learning Machine method is used to classify the types of treatment of Human Papilloma Virus. The symptom parameters used were 6 parameters and the classes used were immunotherapy and cryotherapy. In this research, the initial weight of the Extreme Learning Machine was optimized by Genetic Algorithm and then the weight was used by the Extreme Learning Machine method for the classification process of the types of treatment of the Human Papilloma Virus. The amount of data used is 118 data with the data ratio for the training process and the test process is 80:20. The Extreme Learning Machine parameters used are 10 hidden neurons and binary sigmoid activation functions. The test results obtained the best classification accuracy level of 100% for both treatment, cryotherapy and immunotherapy from 3 of 10 testing with an average computation time of 350,3 seconds using the initial weight which was optimized by the Genetic Algorithm with the best parameter population size of 70, the number generations of 160, the crossover rate of 0.9 and the mutation rate of 0.1.
Aplikasi Jaringan Syaraf Tiruan Resilient Backpropagation pada Prediksi Magnitudo dan Lokasi Gempa Bumi Bagus Priambodo; Wayan Firdaus Mahmudy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 13 (2020): Publikasi Khusus Tahun 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Untuk dipublikasi di Knowledge Engineering and Data Science (KEDS)
Optimasi Penjadwalan Pekerja Kebun Menggunakan Algoritme Genetika Andreas Patuan G. Pardede; Wayan Firdaus Mahmudy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 13 (2020): Publikasi Khusus Tahun 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Artikel dipublikasikan di Jurnal Nasional Terakreditasi, Knowledge Engineering and Data Science
Klasifikasi Risiko Penyakit pada Ibu Hamil menggunakan Metode Modified K-Nearest Neighbor (MKNN) Yogi Pinanda; Wayan Firdaus Mahmudy; Edy Santoso
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

Pregnant women need to increase their knowledge to find out how big the level of risk of getting a disease, especially because of the vulnerability of pregnant women. Classification of the level of disease risk in pregnant women is expected to assist users in finding the right solution to overcome it. The classification method used to determine the level of disease risk for pregnant women uses Modified K-Nearest Neighbor (MKNN). Classification of disease risk levels in pregnant women using the Modified K-Nearest Neighbor (MKNN) method can make it easier to detect disease based on existing factors. The Modified K-Nearest Neighbor (MKNN) method is implemented on the expert system inference engine so that conclusions can be drawn based on existing knowledge. The results of the accuracy of the system obtained after testing is 85% which indicates that the Modified K¬-Nearest Neighbor (MKNN) method is suitable for studying the level of disease risk in pregnant women.
Algoritma Penanganan Constraint pada Persoalan Penjadwalan Perkuliahan Universitas di Lingkungan Pendidikan Tinggi Keagamaan Islam (PTKI) Fatchurrochman Fatchurrochman; Arif Nur Afandi; M Zainal Arifin; Wayan Firdaus Mahmudy
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 9, No 2 (2023): Volume 9 No 2
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v9i2.64546

Abstract

Penjadwalan perkuliahan di universitas adalah kegitan rutin yang membutuhkan waktu relatif lama untuk menyelesaikannya jika dikerjakan secara manual. Waktu yang dibutuhkan akan semakin besar ketika semakin banyak constraint yang dipertimbangkan. Mekanisme penanganannya akan berbeda di tiap universitas karena mungkin mereka mempunyai constraint yang unik. Dalam paper ini dipaparkan berbagai algoritma penanganan untuk tiap jenis constraint dalam persoalan penjadwalan perkuliahan. Algoritma penjadwalan perkuliahan otomatis yang digunakan dalam penjadwalan otomatispenelitian ini adalah sequential search yang bekerja dengan cara mencari slot waktu yang masih belum dipergunakan untuk ditempati oleh kelas perkuliahan . Bila slot waktu telah dipergunakan maka sistem akan mencari slot waktu yang lain secara berurutan. Uji coba dilakukan di program studi Teknik Informatika UIN Malang pada semester Ganjil tahun akademik 2021/2022. Hasilnya menunjukkan bahwa dengan 10 constraint, sistem yang dibangun dapat menjadwalkan 190 kelas perkuliahan secara otomatis dan 21 kelas perkuliahan dijadwalkan secara interaktif. Dengan sistem yang diajukan maka seluruh kelas perkuliahan sebanyak 211 dapat terjadwal meskipun ada pelanggaran soft constraint oleh 17 kelas perkuliahan.
Database optimization for improved system performance and response time of hospital management information system Rahayudi, Bayu; Priandani, Nurizal Dwi; Hanggara , Buce Trias; Mahmudy, Wayan Firdaus
Bulletin of Social Informatics Theory and Application Vol. 5 No. 2 (2021)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v5i2.491

Abstract

A Regional Hospital in East Java has implemented a Hospital Management Information System, namely SIMRS, in their data management system but has experienced problems in the form of slow system response when accessed by many users, was experienced in the last years when the system had been running for four years since 2016. The system’s slow response causes hospital services to be disrupted and also the quality of service to decline. So, an analysis to the existing database system is carried out, which includes an analysis of the system‘s database performance. Since many SIMRS use database servers on their data processing, then their applications will be based on executing queries and stored procedures (most of the queries are stored in stored procedures). So that, analysis of those queries will be carried out. The optimization process will include analyzing and mapping the database’s queries, profiling, and analyzing the Actual Execution Plan. By doing so, it is known which parts of the query are causing a decrease in performance and time system response. Based on the analysis results, recommendations are given for improving and rewriting several stored procedures and query statements, and the system response time is getting better.
Advancements in Fire Alarm Detection using Computer Vision and Machine Learning: A Literature Review M Fadli Ridhani; Wayan Firdaus Mahmudy
Journal of Information Technology and Computer Science Vol. 8 No. 2: August 2023
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.202382554

Abstract

Fire is one of the most common and increasing emergencies that threaten public safety and social development. This can cause significant loss of life and damage. Fire detection systems play an important role in the early detection of fires. The purpose of this study is to provide a brief survey of the latest literature in the field, which can provide a foundation for researchers to develop a Fire Alarm Detection System with a Computer Vision and Machine Learning approach. The Computer Vision and Machine Learning approaches are popular and have been extensively studied because the advantages. The main challenges in fire detection systems are high false alarm rates and slow response times. This research presents potentials and emerging trends through Computer Vision and Machine Learning approaches for Fire Alarm Detection Systems in the future, including the selection of input features to the use of appropriate methods and the process flow of Fire Alarm Detection Systems.
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 Agung Mustika Rizki Agung Mustika Rizki, Agung Mustika Agung Setia Budi Agung Setia Budi, Agung Setia 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 Anissa, Retno Dewi 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 Aulia, Yudha Alif Bagus Priambodo 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 Dzikron, Ahmad Ahdani Edi Satriyanto Edy Santoso Effendi, Mas’ud 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 Fazlur Ihzanurahman 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 Ihsan Akram, Faiz Imada Nur Afifah Imam Cholisoddin Imam Cholissodin Imam Cholissodin Imam Cholissodin Imam Santoso Indriati Indriati Irvi Oktanisa Ishardita Pambudi Tama Ismiarta Aknuranda Jauhari, Farid Khozaimi, Ach. Kukuh Tejomurti, Kukuh Kuncahyo Setyo Nugroho Kuncahyo Setyo Nugroho Kurnianingtyas, Diva Lailil Muflikhah 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 Mochammad Anshori Moh. Khusaini Moh. Sholichin Moh. Zoqi Sarwani Mohammad Zoqi Sarwani Mohammad Zoqi Sarwani, Mohammad Zoqi Mu’asyaroh, Fita Lathifatul Muh Arif Rahman 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 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 Pardede, Andreas Philip Faster Eka Adipraja Pratama, Muhammad Fajarivan Prayudi Lestantyo Prima Zulvarina, Prima 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 Astuti Retno Dewi Anissa Riani, Garsinia Ely Rifa’i, Muhaimin Rinda Wahyuni Rizal Setya Perdana Rizal Setya Perdana Rizdania, Rizdania Rizki Ramadhan Rody, Rafiuddin Ruth Ema Febrita Ryan Iriany S, M Zaki Samaher . Saputro, Arkaditya Lanang Saragih, Triando Hamonangan Selly Kurnia Sari Setyawan Purnomo Sakti Sudarto Sudarto Suhana, Rizka Sukarmi Sukarmi, Sukarmi Sulistyo, Danang Arbian Sutrisno . Sutrisno Sutrisno Syafrial Syafrial Syafrial Syafrial Syaiful Anam Syandri, Hafrijal Tanjung, Lutfi Mitra Tirana Noor Fatyanosa, Tirana Noor Titiek YULIANTI Titiek Yulianti Titiek Yulianti Tomi Yahya Christyawan Tri Halomoan Simanjuntak Ubaidillah, Hafidz 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