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All Journal 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 Sains Teknologi dan Lingkungan (JSTL) 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
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Journal : Journal of Computer Science and Informatics Engineering (J-Cosine)

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Sistem Pakar Diagnosa Awal Penyakit Mata dengan Metode Bayesian Network Novanita Laylatul Husna; Fitri Bimantoro
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 4 No 2 (2020): December 2020
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v4i2.287

Abstract

Almost every human activity needs an eye to support these activities, therefore it will have a bad effect if the eyes experience interference. Disorders that can be experienced in the eye can occur from minor disorders to disorders that cause loss of vision and even death. Based on the results of the Rapid Assessment Assessment of Avoidable Blindness (RAAB), the blindness rate in districts/cities in NTB was 4%. This is not only due to medical-related problems but also due to social problems related to knowledge from the community, facilities, and resources. To make it easier for the public to make an initial diagnosis of eye disease, one thing that can be done is to use an expert system. Various methods can be implemented for expert systems, one of which is the Bayesian Network method. Based on the results of accuracy testing that has been done, this application provides an accuracy rate of 84.99%. Whereas, if the system diagnosis results are a subset of expert diagnostic results, the accuracy rate is 89.99% and based on the results of the use made by the general public, this application has been running well and has provided clear information related to the diagnosis of eye disease.
Sistem Pakar Diagnosa Kelainan Sistem Ortopedi pada Manusia dengan Metode Forward Chaining dan Dempster Shafer: Expert System for Diagnosing Abnormalities of Human Orthopedics System using forward chaining and Dempster Shafer Method Nurhaini Rahmawati; Fitri Bimantoro
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 5 No 1 (2021): June 2021
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v5i1.382

Abstract

The bones and skeleton are very important parts of orthopedics and are the most vulnerable parts of the body. One of the obstacles in the diagnosis of orthopedic disorders is the distance from the hospital and the few orthopedic doctors. This study developed an expert system that runs on an Android-based smartphone to diagnosa 13 types of abnormalities in the orthopedic system with 92 symptom input based on the knowledge of 3 experts using the forward chaining and dempster shafer methods to obtain conclusions about the type of orthopedic disorder suffered. Based on the test results with theoretical calculations, it is found that the system calculation results are in accordance with the results of manual calculations. In testing the accuracy of the system, from 30 examples of cases tested on 3 experts, the accuracy value was obtained based on the average expert weight of 81.11%, the weight of each expert in sequence is 80.00% for expert 1, 83.33% for expert 2, and 73.33% for expert 3, where this accuracy value shows that the performance of the dempster shafer method in diagnosing orthopedic disorders is good and it can be said that the dempster shafer method suitable to be applied in cases of orthopedic disorders. The MOS (Mean Opinion Score) test on 30 respondents resulted in an MOS value of 4.45 from a scale of 5 which indicates that the system is feasible to use and is categorized into a good system
Pengenalan Pola Tulisan Tangan Aksara Bima menggunakan Ciri Tekstur dan KNN: Handwriting Recognition of Bima Script using Texture Features and KNN Fitri Bimantoro; Arik Aranta; Gibran Satya Nugraha; Ramaditia Dwiyansaputra; Ario Yudo Husodo
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 5 No 1 (2021): June 2021
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v5i1.387

Abstract

As the fact, that is Bima script did not familiar to bimanese, Bima script as a cultural heritage needs to be preserved. Pattern recognition has been used to recognize several of ancient script. Gray Level Co-occurence Matrix (GLCM) as features exctraction and K Nearest Neighbour (KNN) as a classifier show the good performance to recognize of an ancient script. so, in this research we use GLCM and KNN to recognize Bima script. we use 2640 images of handwritting bima Script that is collected from 10 volunter. Each volunter write 22 of Bima script twelve times each script. The experimental result show that the performance of our model is good enough, with 60.86% of accuracy that is obtained by manhattan distances.
Ekstraksi Fitur Citra Radiografi Thorax Menggunakan DWT dan Moment Invariant: Feature Extraction of Thorax Radiography Image Using DWT and Moment Invariant I Gede Pasek Suta Wijaya; Ditha Nurcahya Avianty; Fitri Bimantoro; Rina Lestari
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 5 No 2 (2021): December 2021
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v5i2.423

Abstract

COVID-19 is an infectious disease caused by the coronavirus family, namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The fastest method to identify the presence of this virus is a rapid antibody or antigen test, but confirming the positive status of a COVID-19 patient requires further examination. Lung examination using chest X-ray images taken through X-rays of COVID-19 patients can be one way to confirm the patient's condition before/after the rapid test. This paper proposes a feature extraction model to detect COVID-19 through chest radiography using a combination of Discrete Wavelet Transform (DWT) and Moment Invariant features. In this case, haar wavelet transform and seven Hu moments were used to extract image features in order to find unique features that represent chest radiographic images as suspected COVID-19, pneumonia, or normal. To find out the uniqueness of the proposed features, it is coupled with the kNN and generic ANN classification techniques. Based on the performance parameters assessed, it turns out that the wavelet-based and moment invariant thorax radiographic image feature model can be used as a unique feature associated with three categories: Normal, Pneumonia, and Covid-19. This is indicated by the accuracy value of 82.7% in the kNN classification technique and the accuracy, precision, and recall of 86%, 87%, and 86% respectively with the ANN classification technique.
Classification of Glaukoma Image with ANN Based on Blood Vessels on Retina Fundus Image Using Comparison of Otsu-Thresholding Method and Canny Edge Detection Teguh Ardian Samudra; Gibran Satya Nugraha; Fitri Bimantoro
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 6 No 1 (2022): June 2022
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v6i1.439

Abstract

Glaucoma is an eye disease that can lead to permanent blindness caused by increased Intraocular Pressure (IOP). There are several methods to detect glaucoma, namely Optical Nerve Hypoplasia Stereo Photographs (ONHSPs), Optical Coherence Tomography (OCT), Scanning Laser Polarimetry (SLP), and Confocal Scanning Laser Ophthalmoscopy (CSLO). However, these methods require a lot of money and expert supervision. In this paper, glaucoma classification will be carried out using the ANN method with a comparison of the otsu-thresholding segmentation method and canny edge detection with the aim of knowing which method gives better results in diagnosing glaucoma images based on the parameters of accuracy, sensitivity, and specificity. The dataset used is RIM-ONE r2 and r3 which will be extracted using 5 features of GLCM and 6 statistical features, and obtained an accuracy of 76% for the otsu-thresholding method, and 79% for canny edge detection.
Pengenalan Pola Tulisan Tangan Suku Kata Aksara Sasak Menggunakan Metode Integral Projection dan Neural Network Dina Juliani U M, Eka; Wijaya, I Gede Pasek Suta; Bimantoro, Fitri
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 3 No 1 (2019): June 2019
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1503.815 KB) | DOI: 10.29303/jcosine.v3i1.222

Abstract

This paper presents sasak ancient scripts using integral projection and neural network. The purpose of using these two methods is to find out how to work this methods and how much accuracy is obtained in pattern recognition of sasak ancient scripts. The data used is 1260 handwritten image data. Testing is done by knowing the effect of the number of nodes in a hidden layer and the effect of the number of hidden layers in a network. The highest accuracy on average is in the use of 2 hidden layers where 21 nodes for the first hidden layer and 14 nodes for the second hidden layer. The experiment resulted in the obtained accuracy rate of 41.38%.
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.
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 Aldian Wahyu Septiadi Alif Sabrani Aliyah Fajriyani Alwi Pratama 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 Halil Akhyar Hamidi, M. Zaenuddin Hamidi, Mohammad Zaenuddin Hanung Adi Nugroho Hendrawan 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 Ramadian Ridho Illahi 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 Zubaidi, Ariyan Zuhraini, Marlia Zul Rijan Firmansyah