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All Journal Jurnal Ilmu Komputer Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) SENTIA 2015 MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Teknologi Informasi dan Multimedia Jurnal Informatika dan Rekayasa Elektronik Journal of Information Systems and Informatics TRIDARMA: Pengabdian Kepada Masyarakat (PkM) Jurnal Bumigora Information Technology (BITe) Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Manajemen Informatika Jayakarta ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat JURNAL ELEKTRO DAN INFORMATIKA SWADHARMA (JEIS) International Journal of Electronics and Communications Systems Journal Of Information System And Artificial Intelligence Jurnal Sistem Informasi dan Teknologi (SINTEK) Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) SATIN - Sains dan Teknologi Informasi Journal Of Artificial Intelligence And Software Engineering Journal of Management, Entrepreneurship and Tourism Jurnal Pengabdian kepada Masyarakat IPTEKS Jurnal Pengabdian Pada Masyarakat IPTEKS Sintek Kuwera
Triwijoyo, Bambang Krismono
Universitas Bumigora
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Medicine & Pharmacology Nursing Social Sciences Other

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Model Fast Tansfer Learning pada Jaringan Syaraf Tiruan Konvolusional untuk Klasifikasi Gender Berdasarkan Citra Wajah Bambang Krismono Triwijoyo
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 18 No. 2 (2019)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v18i2.376

Abstract

The face is a challenging object to be recognized and analyzed automatically by a computer in many interesting applications such as facial gender classification. The large visual variations of faces, such as occlusions, pose changes, and extreme lightings, impose great challenge for these tasks in real world applications. This paper explained the fast transfer learning representations through use of convolutional neural network (CNN) model for gender classification from face image. Transfer learning aims to provide a framework to utilize previously-acquired knowledge to solve new but similar problems much more quickly and effectively. The experimental results showed that the transfer learning method have faster and higher accuracy than CNN network without transfer learning.
Developing Application in Anticipating DDoS Attacks on Server Computer Machines Anthony Anggrawan; Raisul Azhar; Bambang Krismono Triwijoyo; Mayadi Mayadi
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 20 No. 2 (2021)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v20i2.410

Abstract

The use of server computer machines in companies is primarily a web hosting server that is very easy to experience threats, especially external security threats such as attempts to infiltrate, hacking, viruses, and other malicious attacks. Having a secure server is indispensable for working online and especially if involved in business-related network transactions. The Server's realization to be safe from threats is to protect the server machine's security on the hardware and software side and pay attention to network security that goes to the server machine. Generally, firewall applications on router devices have configuration limitations in securing the network, namely non-integrated applications. In other words, it is necessary to manage the perfect firewall configuration to anticipate Distributed Daniel attacks of Service (DDoS) attacks. Therefore, this study aims to integrate existing firewall applications for router devices into an integrated program to secure the network. The methodology used is the Network Development Life Cycle (NDLC). The research results on this developed application program can overcome DDoS attacks without setting up a firewall on the router device and can automatically monitor DDoS attack activities from outside the Server. Securing servers from DDoS attacks without setting up a firewall on the router device and automating the monitoring of DDoS attack activity from outside the Server are the novelties of this study that have not been available in previous studies.
Sistem Informasi Geografis Pemetaan Jaringan Irigasi dan Embung di Lombok Tengah Ahmat Adil; Bambang Krismono Triwijoyo
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 20 No. 2 (2021)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v20i2.1112

Abstract

Irigasi sebagai alternatif pengairan lahan tadah hujan pada musim kemarau, digunakan untuk meningkatkan produksi hasil pertanian. Pemetaan Jaringan irigasi dan embung pada Kabupaten Lombok Tengah menggunakan sistem data spasial dan non-spasial, yang selama ini masih menggunakan pemetaan secara konvensional. Data Spasial dapat menunjuk posisi geografis dengan setiap karakteristik memiliki satu lokasi yang harus ditentukan dengan cara yang unik. Pemetaan dengan model data spasial, dirancang dengan tahapan seperti analisa kebutuhan perangkat lunak, desain, pembuatan kode program dan pengujian. Metode yang digunakan dalam penelitian ini adalah Analisis spasial, merupakan kumpulan – kumpulan dari teknik yang dapat digunakan untuk melakukan pengolahan data SIG. Hasil dari analisis data spasial sangat bergantung dari lokasi atau tempat di mana objek sedang dianalisis. Manipulasi data, akan menampilkan jendela manipulasi data non-spasial jaringan irigasi, embung, dan kecamatan. Pada jendela manipulasi data, pengguna dapat melakukan penambahan, perubahan dan penghapusan terhadap data tabular yang ada, dan memiliki fasilitas pencarian sesuai dengan data yang sedang diakses.
Convolutional Neural Network With Batch Normalization for Classification of Emotional Expressions Based on Facial Images Bambang Krismono Triwijoyo; Ahmat Adil; Anthony Anggrawan
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 21 No. 1 (2021)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v21i1.1526

Abstract

Emotion recognition through facial images is one of the most challenging topics in human psychological interactions with machines. Along with advances in robotics, computer graphics, and computer vision, research on facial expression recognition is an important part of intelligent systems technology for interactive human interfaces where each person may have different emotional expressions, making it difficult to classify facial expressions and requires training data. large, so the deep learning approach is an alternative solution., The purpose of this study is to propose a different Convolutional Neural Network (CNN) model architecture with batch normalization consisting of three layers of multiple convolution layers with a simpler architectural model for the recognition of emotional expressions based on human facial images in the FER2013 dataset from Kaggle. The experimental results show that the training accuracy level reaches 98%, but there is still overfitting where the validation accuracy level is still 62%. The proposed model has better performance than the model without using batch normalization.
Data Mining Earthquake Prediction with Multivariate Adaptive Regression Splines and Peak Ground Acceleration Dadang Priyanto; Bambang Krismono Triwijoyo; Deny Jollyta; Hairani Hairani; Ni Gusti Ayu Dasriani
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 3 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i3.3061

Abstract

Earthquake research has not yielded promising results because earthquakes have uncertain data parameters, and one of the methods to overcome the problem of uncertain parameters is the nonparametric method, namely Multivariate Adaptive Regression Splines (MARS). Sumbawa Island is part of the territory of Indonesia and is in the position of three active earth plates, so Sumbawa is prone to earthquake hazards. Therefore, this research is important to do. This study aimed to analyze earthquake hazard prediction on the island of Sumbawa by using the nonparametric MARS and Peak Ground Acceleration (PGA) methods to determine the risk of earthquake hazards. The method used in this study was MARS, which has two completed stages: Forward Stepwise and Backward Stepwise. The results of this study were based on testing and parameter analysis obtained a Mathematical model with 11 basis functions (BF) that contribute to the response variable, namely (BF) 1,2,3,4,5,7,9,11, and the basis functions do not contribute 6, 8, and 10. The predictor variables with the greatest influence were 100% Epicenter Distance and 73.8% Magnitude. The conclusion of this study is based on the highest PGA values in the areas most prone to earthquake hazards in Sumbawa, namely Mapin Kebak, Mapin Rea, Pulau Panjang, and Pulau Saringi.
Co-Authors Abi Mas'ud Agus Pribadi Aguswandi, Lalu Heri Ahmat Adil Amrullah, Rahayun Andi Sofyan Anas Anthony Anggrawan Ayu Dasriani, Ni Gusti Azhar, Raisul Cahaya Ardi, L. Nanda Christopher Michael Lauw Dadang Priyanto Dadang Priyanto Damar, Lalu Riyandi Deny Jollyta Diah Supatmiwati Dian Syafitri Chani Saputri Elyakim Nova Supriyedi Patty, Elyakim Nova Supriyedi Ervina Farijki Fahly, Moh. Rizky Galih Hendro Martono Hairani Hairani Hariri, Muhammad Husain Husain Islamiah, Nuratun Kartarina, Kartarina Khasnur Hidjah Lalu Riyandi Damar Lalu Yuda Rahmani Karnaen Lilik Widyawati Martono, Gallih Hendro Mayadi Mayadi Miftahul Madani Miswaty, Titik Ceriyani Muhammad Haris Nasri MUHAMMAD TAUFIK Neny Sulistianingsih Ni Wayan Yuli Ariyanti Noviansyah Noviansyah, Noviansyah Resmiranta, Dading Oktaviadi Risca Anggraeni Dwiputri Santoso, Heroe Satrani, Azral Sirojul Hadi Tajuddin, Muhammad Tomi Tri Sujaka Zulfikri, Muhammad Zulfiqri, Muhammad