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All Journal Lontar Komputer: Jurnal Ilmiah Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Journal of Education and Learning (EduLearn) JUTI: Jurnal Ilmiah Teknologi Informasi Journal of Telematics and Informatics Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) JOIV : International Journal on Informatics Visualization JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal RESISTOR (Rekayasa Sistem Komputer) Journal of Computer Science and Informatics Engineering (J-Cosine) EDUMATIC: Jurnal Pendidikan Informatika Jurnal Teknologi Informasi, Komputer, dan Aplikasinya (JTIKA ) Dielektrika : Jurnal Ilmiah Kajian Teori dan Aplikasi Teknik Elektro JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Jurnal Abdi Insani Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Teknik Informatika (JUTIF) Jurnal Begawe Teknologi Informasi Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Lontar Komputer: Jurnal Ilmiah Teknologi Informasi
Fitri Bimantoro
Informatics Engineering Dept., Faculty Of Engineering, University Of Mataram
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Public Health Social Sciences Transportation Other

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Sistem Pakar Diagnosa Penyakit Gigi dengan Metode Bayesian Network Berbasis Website Aisyah, Yunda; Bimantoro, Fitri; Irmawati, Budi
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 3 No 2 (2019): December 2019
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1593.435 KB) | DOI: 10.29303/jcosine.v3i2.260

Abstract

Teeth serve to chew food, say words clearly, form a harmonious face and for a better appearance. Healthy teeth and gums will make it easy to eat well and enjoy good food. There are some problems that can affect oral health, but good care will make the teeth and gums strong. Lack of public awareness of maintaining dental health can cause major problems later on. In this case, an expert system tool for diagnosing dental diseases will be made using the website-based Bayesian Network method. The initial step in this study was to collect data, such as data on dental disease, data on dental disease symptoms and the weight of each symptom of dental disease used. The data was obtained from three dental disease doctors in three health centers in East Lombok. After getting the data, then calculating the weights for each symptom, the results of the calculation will be summed then divided by the number of symptoms suffered by the patient. The results of these calculations can be consulted by a dental specialist.
Pengembangan Perintah Gestur Tangan Menggunakan Leap Motion untuk Aplikasi Floorplanner Marcellino, Hendy; Ario Yudo Husodo; Fitri Bimantoro
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 7 No 2 (2023): Desember 2023
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v7i2.516

Abstract

Architecture is part of the art of life and works best when it seems to give expression to the life that inhabits it. As technology has developed a lot, the field of architecture has also experienced many developments supported by technology such as making architectural designs. The development experienced in making architectural designs is that it is no longer required to draw design choices with side views on a lot of paper but instead use a simulation application for making architectural designs that are displayed through a monitor layer in 3D so that they can see more realistically. After many innovations emerged regarding simulation applications which generally still use hardware such as a mouse, then these innovations shifted to connecting the simulation application with the virtual world where hardware such as a mouse has been replaced by using gestures or limb movements such as parts of the hand or other parts of the body. While other fields like medic already use virtual tool interaction, architecture fields still just use mouse and keyboard. One of the virtual interaction devices used to be able to detect fingers and palms to interact with 3D simulation applications is Leap Motion. Leap Motion is starting to be widely used to carry out various ways of interacting with hands because it is more interactive and interesting to use even many people think that it can be used for hand rehabilitation or therapy too. However, even though many innovations have developed, there is still no innovation in the use of a hand gesture command system using Leap Motion for simulation applications to design architectural designs in 3D views. Based on these things, the authors designed and developed hand gesture commands using Leap Motion for Architectural Design App. The hand gesture command system used for the Floorplanner simulation application will be tested using a system usability scale by users with architectural, informatics, and unfamiliar backgrounds. Based on the tests carried out, it can be seen that the system is running properly even though it requires getting used to the device first and getting a score from the System Usability Scale of 59,167 out of scale from 0 to 100 which means it is still accepted by users or declared as "Marginally Acceptable" category.
Klasifikasi Citra Lubang pada Permukaan Jalan Beraspal dengan Metode Convolutional Neural Networks (CNN): Image Classification of Potholes on Paved Road Surfaces with the Convolutional Neural Networks (CNN) Method Ni Nyoman Citariani Sumartha; I Gede Pasek Suta Wijaya; Fitri Bimantoro; Gibran Satya Nugraha
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 8 No 1 (2024): Juni 2024
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v8i1.557

Abstract

A pothole is a bowl-shaped indentation in the road surface, less than 1 meter in diameter. The presence of potholes on the highway can endanger the safety of road users, so repairs need to be done as soon as possible. Images of potholed roads have high complexity, variations consisting of color contrast, hole size, presence of puddles or not, lighting when taking pictures, background and others. For this reason, an approach is needed that can classify images with a high degree of variation by extracting the important information contained in them. Judging from the potential success of using the Convolutional Neural Networks (CNN) approach in identifying images of potholes that will be reported for entry into the Public Works Service's road improvement record, the authors propose the idea of "Pothole Image Classification on Asphalt Road Surfaces with the Convolutional Neural Networks (CNN) Method”.
User Requirement Analysis dalam penerapan metode User Centered Design sebagai pendukung kebutuhan UI/UX dalam aplikasi NTB Mall Agitha, Nadiyasari; Ario Yudo Husodo; Fitri Bimantoro
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 7 No 2 (2023): Desember 2023
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v7i2.576

Abstract

User requirement analysis merupakan satu hal yang penting dilakukan dalam pembuatan sebuah user interface/user experience (UI/UX) menggunakan metode User Centered Design (UCD). Hal ini dikarenakan pada tahapan ini terdapat identifikasi dan dokumentasi kebutuhan pengguna. NTB mall adalah e-commerce pertama milik pemerintah daerah NTB dengan tujuan menjual produk unggulan daerah dari Usaha Mikro, Kecil Menengah (UMKM), Pedagang Kaki Lima (PKL) dan dibantu dengan pemantauan oleh Kelompok Sadar Wisata (Pokdarwis). Dalam pembuatan UI/UX NTBMall, diperlukan user requirement analysis yang kuat untuk mendapatkan penggunaan NTBMall yang sesuai dengan kebutuhan pengguna. User requirement analysis dibagi menjadi beberapa tahapan secara berurutan. Penggunaan user requirement analysis telah terbukti menghasilkan UI/UX yang menarik, dibuktikan dengan hasil pengujian SUS bernilai 72.82 yang mengartikan bahwa user telah puas dengan aplikasi NTBMall.
Pelatihan Desain Grafis Untuk Masyarakat Pelaku Wisata Di Lombok: Graphic Design Training for Tourism Communities In Lombok Widiartha, Ida Bagus Ketut; Afwani, Royana; Bimantoro, Fitri; Husodo, Ario Yudo; Agitha, Nadiyasari
Jurnal Begawe Teknologi Informasi (JBegaTI) Vol. 4 No. 2 (2023): JBegaTI
Publisher : Program Studi Teknik Informatika, Fakultas Teknik Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jbegati.v4i2.1113

Abstract

Lombok merupakan salah satu tujuan wisata utama yang ada di Indonesia, keindahan alamnya tidak kalah dengan Bali yang sudah terlebih dahulu terkenal di Manca Negara. Keberagaman budaya dan produk lokal yang dimiliki juga sangat banyak dan mendukung peningkatan jumlah kunjungan wisata. Promosi yang dilakukan oleh pemerintah tidak dapat mengakomodir semua obyek wisata dan mempromosikan produk lokal dari masyarakat tersebut, karena seiring dengan kesadaran masyarakat tentang pentingnya pariwisata dalam meningkatkan kesejahteraan, banyak sekali muncul obyek wisata baru dan produk- produk baru yang tidak tersentuh oleh promosi pemerintah. Dan promosi yang dilakukan secara konvensional membutuhkan biaya yang sangat mahal. Diera digital saat ini media sosial, memegang peranan sangat penting dalam mempromosikan sesuatu. Selain kemampuannya untuk mempromosikan produk ataupun obyek, media sosial juga bisa digunakan untuk membuat personal branding yang pada hilirnya dapat mendatangkan keuntungan materi. Untuk membuat konten yang menarik perlu pelatihan ketrampilan kepada masyarakat untuk dapat meningkatkan kemampuannya dalam membuat konten yang ditampilkan dalam media sosial sehingga lebih banyak orang melihat dan berkomentar yang pada akhirnya dapat menjadi media promosi yang murah
The Palmprint Recognition Using Xception, VGG16, ResNet50, MobileNet, and EfficientNetB0 Architecture Aprilla, Diah Mitha; Bimantoro, Fitri; Suta Wijaya, I Gede Pasek
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 2 (2024): April 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i2.7577

Abstract

The palmprint is a part of the human body that has unique and detailed characteristics of the pattern of palm lines, such as the length and width of the palm (geometric features), principal lines, and wrinkle lines. It began to be developed as a tool for recognize a person. The palmprint dataset used comes from Kaggle, namely BMPD. The palmprint images in this dataset were taken in 2 sessions. In the first session, there was not much variation in rotation compared to the second session. This research uses Convolutional Neural Network (CNN) models with Xception, VGG16, ResNet50, MobileNet, and EfficientNetB0 architectures to see the best performance. The results of this research showed that the MobileNet model had the best performance with an accuracy of 96.6% and a loss of 14.3%. For Precision results of 94%, Recall 96%, and F1-Score 94%. Meanwhile, Xception obtained an accuracy of 88.3% and a loss of 52.9%, VGG16 70.8% and a loss of 109.8%, ResNet50 5.8% and a loss of 307.9%, and EfficientNetB0 3.3% and a loss of 340.1%.
Temu Kembali Citra Menggunakan Metode Local Binary Pattern Rotation Invariant (Lbprot) dan Cosine Distance Similarity Zuhraini, Marlia; Wijaya, I Gede Pasek Suta; Bimantoro, Fitri
DIELEKTRIKA Vol 9 No 1 (2022): DIELEKTRIKA
Publisher : Jurusan Teknik Elektro Fakultas Teknik Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Image retrieval is a method of searching for an image by comparing the query image with the image in the database. One of the important things in image retrieval is the feature extraction process. Currently, the feature extraction method needed is reliable in recognizing images that are rotated at various angles or invariant to rotation such as the Local Binary Pattern Rotation Invariant (LBPROT) method. In addition to the feature extraction method, what is also important is the distance measurement method. The distance measurement method used is the Cosine Distance Similarity method. the combination of these two methods resulted in the highest average precision and recall at a ratio of 70%:30% of 98.06% and 96.78% for normal images and for images that were rotated at an angle of 90o of 97.08% and recall of 96,70%. In addition, testing on rotational images produces the lowest average precision and recall at an angle of 45° at 0%.
Implementasi Convolutional Neural Network pada Multi-label Classification Wajah Manusia Berdasarkan Usia, Gender, dan Ras Maulana Surya Negara; Muhamad Irzan; Ahmad Dia’ul Haqqi; Fitri Bimantoro
DIELEKTRIKA Vol 11 No 2 (2024): DIELEKTRIKA
Publisher : Jurusan Teknik Elektro Fakultas Teknik Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/dielektrika.v11i2.389

Abstract

Klasifikasi wajah manusia merupakan bidang penelitian penting dalam pengenalan pola dan computer vision, dengan fokus pada informasi seperti jenis kelamin, usia, ras, dan ekspresi wajah. Penelitian ini bertujuan untuk meningkatkan klasifikasi multi-label wajah manusia menggunakan convolutional neural network (CNN). Metode tradisional seperti Local Binary Pattern (LBP) dan Random K-Nearest Neighbor (KNN) menunjukkan keterbatasan dalam akurasi dan ketergantungan pada ekstraksi fitur manual, sementara metode CNN yang lebih modern menunjukkan peningkatan akurasi yang signifikan. Penelitian ini bertujuan meningkatkan klasifikasi multi-label wajah manusia berdasarkan usia, gender, dan ras menggunakan convolutional neural network (CNN). Menggunakan dataset UTKFace, model CNN diuji dengan berbagai arsitektur dan teknik augmentasi data. Hasil terbaik menunjukkan akurasi 82.98% untuk usia, 90.36% untuk gender, dan 79.48% untuk ras. Penggunaan augmentasi data dan peningkatan jumlah filter CNN secara signifikan meningkatkan akurasi model. Meskipun ada tantangan dalam mengklasifikasikan usia "teenager" dan ras "Indian" serta "Others" akibat distribusi data yang tidak seimbang, hasil ini menunjukkan potensi besar CNN dalam klasifikasi multi-label wajah manusia. Pengembangan lebih lanjut direkomendasikan dengan fine-tuning arsitektur CNN dan eksplorasi metode augmentasi data serta transfer learning.
PENGENALAN POLA SUKU KATA AKSARA BIMA DENGAN BARIS TANDA BUNYI MENGGUNAKAN EKSTRAKSI CIRI MOMENT INVARIANT DENGAN METODE ANN Rizqullah, Muhammad Naufal; Dwiyansaputra, Ramaditia; Bimantoro, Fitri
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 6 No 1 (2024): March 2024
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v6i1.188

Abstract

The Bimanese script is one of the archipelago's cultural heritage that needs to be preserved. The problem arose when some Bimanese people doubted the existence of the Bimanese script. Therefore, it is essential to safeguard the Bimanese script and learn the Bimanese script starting from reading and then understanding the letters. After that, add a line of sound marks to entirely understand the Bimanese script's meaning. This study aims to build an Artificial Neural Network (ANN) model to recognize the Bimanese Script Syllable Pattern with Sound Sign Lines by using Moment Invariant feature extraction. Before doing the training, first, determine the parameters on the ANN using the Tuning Hyperparameter, in the test, using a dataset of 2250 images of the Bimanese script. Based on the results of the tests carried out based on the optimal parameters, the accuracy is 77.59%, precision is 78.44%, recall is 77.61%, and F1-Score is 77.33%. Then for testing using K-Fold cross-validation, the best results were obtained using K = 9 with a ratio of 8:1 where the resulting accuracy was 79.74%. Overall the results of this study are expected to preserve the Bimanese script and are developed more widely.
EAR DISEASE CLASIFICATION USING DEEP LEARNING WITH XCEPTION AND MOBILENET-V2 ARCHITECTURE Setiawan, Lalu Rudi; Wijaya, I Gede Pasek Suta; Bimantoro, Fitri
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 6 No 2 (2024): September 2024
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v6i2.426

Abstract

Hearing loss is a significant global health problem, with a high prevalence in Indonesia. Limited access to ENT specialists, especially in remote areas, causes delays in diagnosis and treatment of ear diseases. This research aims to develop an early diagnosis system for ear diseases using deep learning. The proposed method applies Xception and MobileNet-V2 Convolutional Neural Network (CNN) architecture with hyperparameter optimization using Bayesian Optimizer. The dataset consists of 1,101 images covering 20 types of ear diseases, collected using an endoscope ear cleaning kit at Mataram University Hospital. The dataset was divided into 60% training data, 20% validation data, and 20% test data. Xception recorded the best performance with accuracy, precision, recall, and f1-score of 0.911, 0.166, 0.166, and 0.151, respectively. The best model performance was obtained on MobileNet-V2 with the application of Bayesian Optimizer, resulting in the best hyperparameters at Unit Dense 174, Dropout Rate 0.2, and LXceptionearning Rate 0.003. This scenario resulted in an increase in accuracy, precision, recall, and f1-score compared to the scenario without hyperparameter search of 0.004, 0.010, 0.018, and 0.012, respectively. This research demonstrates the potential of deep learning in improving early diagnosis of ear diseases.
Co-Authors A.A.Sg. Mas Karunia Maharani Ade Ragil Purwandani Adi Sugita Pandey Afwani, Royana Agitha, Nadiyasari Agus Eko Minarno Ahmad Dia’ul Haqqi Ahmad Zafrullah Mardiansyah Aisyah, Yunda Akhyar, Halil Aldian Wahyu Septiadi Alif Sabrani Anita Rosana MZ Annisa Mujahidah Robbani Anugrah, Febrian Rizky Aohana, Mizanul Ridho Aprilla, Diah Mitha Aranta, Arik Arik Aranta Arik Aranta Ario Yudo Ario Yudo Husodo Ario Yudo Husodo Ario Yudo Husodo Ario Yudo Husodo Ario Yudo Husodo, Ario Yudo Arrie Kurniawardhani arrie kurniawardhany, arrie Ayu Septya Maulani B. Nurwahyu Hairani Bagaskara, Andhika Dwija Baiq Rizki Putri Utami Budi Irmawati Chaerus Sulton Cokro Mandiri, Mochammad Hazmi Daniel Swanjaya Darmawan, Riski dina hastari Dina Juliani U M, Eka Ditha Nurcahya Avianty Dwiyansaputra, Ramaditia Ellysabeth Usmiatiningsih Fachry Abda El Rahman Fadilah . Fahmi Syuhada Faqih Hamami fathin zulian tsany Fernanda Dicky Ivansyah Fiena Efliana Alfian Fuad Fadlila Surenggana Fuad Fadlila Surenggana Gibran Satria Nugraha Gibran Satya Nugraha Gibran Satya Nugraha Gibran Satya Nugraha Gibran Satya Nugraha Gibran Satya Nugraha Grendis, Nuraqilla Waidha Bintang Haidar Rahman Haidra Rahman Hamidi, Mohammad Zaenuddin Hanung Adi Nugroho Heri Wijayanto Hidhayah, Ratu Nisful Laily husnul khotimah I B K Widiartha I Gede Andika I Gede Pasek Suta Wijaya I Gede Putu Wirarama Wadashwara Wirawan I Gede Putu Wirarama Wedashwara W I Gede Wirarama Wedashwara W. I Putu Teguh Putrawan I Putu Teguh Putrawan I Wayan Agus Arimbawa I Wayan Agus Arimbawa, I Wayan Agus Ibrahim, Zaidah Ida Bagus Ketut Widiartha Ida Bagus Ketut Widiartha Imam Tantowi Isye Arieshanti Jatmika, Andy Hidayat Kansha, Lyudza Aprilia Lalu Zulfikar Muslim Lidia Ardhia Wardani Liza Yuliana Khairani Marcellino, Hendy Maulana Surya Negara Maulana, Sutan Fajri Mizanul Ridho Aohana Moh. Ali Albar Moh. Azzam Al Husaini Muhamad Irzan Muhammad Afif Ma'ruf Muhammad Daden Kasandi Putra Wesa Muhammad Edy Kurniawan Basri Muhammad Giri Restu Adjie Muhammad Hadi Muhammad Hadiasri Muhammad Khaidar Rahman Muhammad Sholihul Hamdi Muhammad, David Arizaldi Muntari Muntari Murpratiwi, Santi Ika Nanik Suciati Nazibullah Nazibullah Ni Nyoman Citariani Sumartha Nindya Alita Rosalia Noor Alamsyah Novanita Laylatul Husna Novita Nurul Fakhriyah Nugraha, Gibran Satya Nuraqilla Waidha Bintang Grendis Nurhaini Rahmawati Nurhalimah Nurhalimah Obenu, Juanri Priskila Patriaji Ibrahim Maulana Prof. I Gede Pasek Suta Wijaya Putu Wahyu Pratama Rabbani, Budiman Raihan, Muhammad Dzulhi Ramadhani, Rizky Insania Ramaditia Dwiyansaputra Ramaditia Dwiyansaputra Ramdhani, Ghina Kamilah Ramlah Nurlaeli Rani Farinda Regania Pasca Rassy Rijalul Imam Rina Lestari Riska Yulianti Rival Biasrori rizka amalia Rizki Rahmadi Rizqullah, Muhammad Naufal Robert Silas Kabanga Rosalina Rosalina Salma Nabilla Ulpa Salsabila Putri Rajani Said Satya Nugraha, Gibran Setiawan, Lalu Rudi Susi Rahayu Suwardiman Suwardiman Tazkiya Aulia Rachman Teguh Ardian Samudra Ulandari, Alisyia Kornelia Umbara Diki Pratama Wahyu Alfandi Wildan Suharso Yogi Permana Yudhis, Putu Yudhis Yudo Husodo, Ario Yufis Azhar Yunia Puspita Wulandari Zuhraini, Marlia Zul Rijan Firmansyah