Garuda - Garba Rujukan Digital

Sistem Pakar Menggunakan Metode Certainty Factor dalam Akurasi Identifikasi Penyakit pada Paru Siska, Ayu Prima; Yunus, Yuhandri; Sumijan, Sumijan
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 2
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jsisfotek.v3i2.111

Lungs are a very importand part of the human organ, which functions as a place for oxygen exchange. This organ that is located under the ribs has a very heavy task, as well as the pollution of the air we breathe everyday which will cause various diseases in the lungs. Lung disease is a disease that is common to everyone, and there are still many who are less concemed with lung healty, so that is causes many indications of lung diseas. Expert system is a system that uses human knowledge recorded in a computer to solve a problem. The purpose og this study was to datermine the accuracy of disease identification in the lungs using the Certainty Factor method. The date obtained is datae about the symptoms that prove wherher a person has lung disease or not and conduct an analysis of the date, so that later conclusions can be abtained from the facts found using an expert system of the Certianty Factor method. The date obtained is date about the sympyoms thet prove whethera person has lung as a problem solving metric which is a parameter value to show the amount of trust. The result of the research from an expert system on pulmonary disease with pulmonary tuberkolosis (TBC) with a certainty level og 68%. Expert system on lung disease using the Certainty Factor method can make it easien for sufferes to know and handle prevention and handling.

Identifikasi Gejala Kerusakan Motor Matic Tipe Lexi Merk Yamaha dengan Menggunakan Metode Forward Chaining Berbasis Web Agasi, Andre; Sumijan, Sumijan
Jurnal Sistim Informasi dan Teknologi 2020, Vol. 2, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jsisfotek.v2i4.122

The Motorcycle Industry Association (AISI) announced that automatic motorcycle sales data has increased. The high use of automatic motorbikes at this time is not accompanied by the ability to repair damage to motorbikes by users. due to lack of information on how to maintain motorbikes, negligence in monthly service, and delaying repairs that should have been done but were postponed until they were seriously damaged. The expert system is an alternative to help mechanics and motorbike users to consult early symptoms of motor damage. Developing the Expert System application provides an overview of motor matic damage. The data comes from interviews with mechanics and data on the types of problems given by experts. After data collection, analysis and problem solving were carried out using the Forward Chaining method with the preparation of rules or rules. The results of the rule formulation are implemented into a system that aims to determine the extent to which the PHP programming language is applied in identifying damage to motorbike matic lexi. Followed by testing the results so that the results of the process carried out with the help of the application match the results of the process carried out manually. The results of the application are that it can provide early symptom clues to the lexi matic motor damage. The application of the Forward Chaining method is applied to systems that have an accuracy level of up to 80%, therefore the system can be said to be good enough to be implemented.

Metode Multi Attribute Utility Theory (MAUT) Untuk Penilaian Kinerja Guru Yamin, Abdul Yamin; Defit, Sarjon; Sumijan, Sumijan
Computer Science and Information Technology Vol 4 No 3 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i3.5920

The performance assessment of teachers is a foundation or basis for the development decisions in terms of promotion and career of teachers in a madrasah or school. Currently, teacher performance assessment at Pondok Pesantren MTI Canduang is limited to teachers who are civil servants (PNS) or have obtained certification. In an effort to improve the quality of education, it is important to evaluate the performance of all teachers, including those who are not civil servants. The conventional method of assessment using paper-based evaluation sheets is considered inaccurate and inefficient due to the large number of teachers being assessed. Furthermore, there is no appropriate method for making decisions regarding teacher reward programs. Therefore, the purpose of this research is to apply the Multi Attribute Utility Theory (MAUT) method for teacher performance assessment. This method aims to provide a basis for decision-making in recommending teachers who deserve rewards in each assessment period. Based on the test results using the MAUT method with 40 teacher data and 12 defined assessment criteria, it was found that 3 data points for Tsanawiyah level had the highest value of 0.797 and the lowest value of 0.332, while 3 data points for Aliyah level had the highest value of 0.874 and the lowest value of 0.386. Thus, the research results can help the madrasah determine the best alternatives according to predefined criteria and weights. The resulting web-based application can facilitate the assessment process by making it easier, faster, and more accurate.

Implementasi Naïve Bayes dalam M-Series 4 Mobile Legends untuk Prediksi Kemenangan Tamaza, Muhammad Abyanda; Defit, Sarjon; Sumijan, Sumijan
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i1.6707

Mobile Legends is a game made by a developer from China called Moontoon which implements the Multiplayer Online Battle Arena (MOBA) system which is currently popular. The popularity of this game is proven by the holding of low, middle and high level tournaments. Recently a high level or international tournament called the M-Series World Championship was held in Indonesia. This game is played by two teams consisting of five players with the aim of destroying enemy targets in the form of towers. The problem in this game is winning and losing. One of the factors that determines victory or defeat is the choice of hero. The wrong hero composition during the draft pick stage can make it difficult for your team to play and lead to unexpected results. This research aims to predict the percentage level of Mobile Legends wins based on the drafted heroes. Prediction is the process of minimizing errors in systematically estimating the future based on past information. The technique used in this research is the Naïve Bayes algorithm. The Naïve Bayes algorithm is a classification method based on probability. This method consists of four stages, namely data understanding, data preparation, data analysis, and results analysis. This research dataset is provided by Youtube MPL Indonesia. The dataset consists of 880 training data and 90 test data for M-Series 4 Mobile Legends. The results of this research provide a percentage value in the form of prediction of 96.67%, precision of 95.65% and recall of 97.78%. The results of an accuracy rate of 96.67% using the Naïve Bayes algorithm show that predictions using the Naïve Bayes algorithm can be applied to predict win ratios in M-Series 4 Mobile Legends.

Glaucoma detection in retinal fundus images using residual network architecture Islami, Fajrul; Sumijan, Sumijan; Defit, Sarjon
Bulletin of Electrical Engineering and Informatics Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i5.7621

Glaucoma is a significant eye disease that can lead to irreversible vision loss if not detected and treated early. This research focuses on developing an automated glaucoma detection system using a combination of a convolutional neural network (CNN) with the residual network 18 (ResNet18) architecture, locality sensitive hashing (LSH), and Hamming distance calculation. The CNN model is trained to extract meaningful features from retinal images, while LSH enables efficient indexing and retrieval of similar images. Hamming distance calculations are utilized to measure the dissimilarity between binary codes obtained from LSH. A dataset of 506 retinal images, consisting of 117 glaucoma images, 19 glaucoma suspect images, and 370 healthy images. The proposed glaucoma detection system achieved an average accuracy of 99.96%, sensitivity of 99.97%, and specificity of 99.94% during training, and 82.37% accuracy, 86.78% sensitivity, and 73.55% specificity during testing. Comparative analysis demonstrated its superiority over traditional methods. Further research should focus on larger datasets and explore multi-class classification for different glaucoma stages. The proposed system has potential for early glaucoma detection, facilitating timely intervention, and preventing vision loss.

Comparison Analysis of HSV Method, CNN Algorithm, and SVM Algorithm in Detecting the Ripeness of Mangosteen Fruit Images Anam, M. Khairul; Sumijan, Sumijan; Karfindo, Karfindo; Firdaus, Muhammad Bambang
Indonesian Journal of Artificial Intelligence and Data Mining Vol 7, No 2 (2024): September 2024
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v7i2.29739

Mangosteen contains a substance known as Xanthone, a phytochemical compound with the distinctive red component in mangosteen that is known for its properties as an anticancer, antibacterial, and anti-inflammatory agent. Additionally, Xanthone has the potential to strengthen the immune system, promote overall health, support mental well-being, maintain microbial balance in the body, and improve joint flexibility. The mangosteen fruit is consumable when it reaches maturity, displaying a dark purplish-black color. Besides the edible part of the fruit, the peel also possesses remarkable medicinal properties. To detect whether the fruit is ripe or not, this research employs image processing techniques. The study utilizes the HSV (Hue, Saturation, and value) color space method, CNN (Convolutional Neural Network) algorithm, and SVM (Support Vector Machine) algorithm. These methods and algorithms are chosen for their relatively high accuracy levels. The dataset used in this research is obtained from mangosteen datasets available on Kaggle. The results of this study indicate that the HSV method achieved an accuracy of 86.6%, SVM achieved an accuracy of 87%, and CNN achieved an accuracy of 91.25%. From the achieved accuracies, it is evident that the CNN algorithm yields higher accuracy compared to the others.

Improved adaptive multi-threshold method for automatic identification of rhinosinusitis in paranasal sinus images Putra, Ondra Eka; Sumijan, Sumijan; Tajuddin, Muhammad
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i1.pp119-129

Rhinosinusitis, characterized by inflammation of the mucosa or mucous membrane within the paranasal sinuses, anatomical cavities situated in the facial bones, is the focus of this investigation. This study employs computed tomography (CT)-scan images comprising sagittal slices of the paranasal sinuses, acquired through a CT device featuring a Philips Ingenuity CT model MRC880 tube type, identified by tube serial number 163889, with a pixel value resolution of 0.24 mm. The primary objective of this research is to automatically identify and delineate rhizosinusitis-affected areas. This involves the application of multi-threshold values during the segmentation process, utilizing the improved adaptive multi-threshold (IAMT) segmentation method. The research dataset encompasses 380 slices of CTscans derived from 10 patients displaying indications of rhinosinusitis. Analysis of the test results reveals that the smallest observed rhinosinusitis size in this study is 0.05 cm2 on the right side, while the largest size measures 1.81 cm2 , yielding an accuracy rate of 96.66%. The magnitude of rhinosinusitis sizes serves as an indicative measure of the extent of inflammation within the paranasal sinus region, thereby suggesting a potential need for more intensive treatment interventions for the affected patients.

Vulnerability Testing and Analysis on Websites and Web-Based Applications in the XYZ Faculty Environment Using Acunetix Vulnerability Rahmi, Mifthahul; Yunus, Yuhandri; Sumijan, Sumijan
JITCE (Journal of Information Technology and Computer Engineering) Vol 8 No 2 (2024): Journal of Information Technology and Computer Engineering
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.8.2.83-96.2024

The internet's continuous evolution has profoundly impacted society through the advancement of website technology and applications, reshaping contemporary ways of life. These digital platforms offer unrestricted information access, overcoming spatial and temporal limitations. In the realm of software development, Vulnerability Assessment is essential for producing high-quality products, as seemingly minor errors can create dangerous vulnerabilities that malicious actors may exploit to pilfer information from websites or applications. This study examines the security level of the Integrated website and application within the Faculty of Medicine, Universitas Andalas (Fakultas XYZ) environment, utilizing the Acunetix Web Vulnerability Scanner tool. The initial scan revealed a threat level of 3 (high) for the Fakultas XYZ website and level 2 (medium) for the Integrated application. Following a recapitulation process, several web alerts were identified for optimization, including Cross-Site Scripting (XSS), Blind SQL Injection, Application error message, HTML form without CSRF protection, Development configuration file, Directory listing, Error message on page, and User credentials sent in clear text. The optimization process involved source code review and enhancement to improve website features. A subsequent scan post-optimization demonstrated a reduction in threat levels for both the website and the UNAND FK Symphony application, with both achieving threat level 1 (low).

Vulnerability Testing and Analysis on Websites and Web-Based Applications in the XYZ Faculty Environment Using Acunetix Vulnerability Rahmi, Mifthahul; Yunus, Yuhandri; Sumijan, Sumijan
JITCE (Journal of Information Technology and Computer Engineering) Vol. 8 No. 2 (2024)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.8.2.83-96.2024

The internet's continuous evolution has profoundly impacted society through the advancement of website technology and applications, reshaping contemporary ways of life. These digital platforms offer unrestricted information access, overcoming spatial and temporal limitations. In the realm of software development, Vulnerability Assessment is essential for producing high-quality products, as seemingly minor errors can create dangerous vulnerabilities that malicious actors may exploit to pilfer information from websites or applications. This study examines the security level of the Integrated website and application within the Faculty of Medicine, Universitas Andalas (Fakultas XYZ) environment, utilizing the Acunetix Web Vulnerability Scanner tool. The initial scan revealed a threat level of 3 (high) for the Fakultas XYZ website and level 2 (medium) for the Integrated application. Following a recapitulation process, several web alerts were identified for optimization, including Cross-Site Scripting (XSS), Blind SQL Injection, Application error message, HTML form without CSRF protection, Development configuration file, Directory listing, Error message on page, and User credentials sent in clear text. The optimization process involved source code review and enhancement to improve website features. A subsequent scan post-optimization demonstrated a reduction in threat levels for both the website and the UNAND FK Symphony application, with both achieving threat level 1 (low).

Detection of Keratitis in The Cornea By Developing An Active Contour Method Based on Contrast Features Negoro, Wahyu Saptha; Sumijan, Sumijan; Bukhori, Saiful
JOIV : International Journal on Informatics Visualization Vol 9, No 2 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.2.3356

Digital Image Processing (DIP) is a scientific discipline that uses computer image processing techniques. The object of this research is keratitis on the cornea. The image of keratitis is obtained using a slit lamp at Padang Aye Center (PAC) Hospital, based on the results of the diagnosis, namely by looking at the development of the infiltrate or also called hypopyon, measuring the ulcer borders horizontally and vertically to evaluate improvement or response to the treatment given. The clinical results cannot determine the extent and circumference of the keratitis layer area that responds to treatment in the corneal area. The images used were 206 slit lamp images of keratitis. This research provides knowledge in the form of contrast values in the Active Contour method, resulting in an update called Active Contour Contrast Adjustment (ACCA) in correctly segmenting keratitis objects and providing measurements of the area and perimeter of the keratitis area. Overall. The research results from 206 slit lamp images, 195 slit lamp images of keratitis could detect keratitis correctly, and eleven slit lamp images of keratitis could not be detected, resulting in an accuracy of 94.66%. Meanwhile, the standard Active Contour accuracy was not detected at all or 100% undetected. Based on 11 images not detected using the (ACCA) method from 206 images, an accuracy of 5.33% was obtained. So, the results obtained are outstanding and can be used as a reference for medical personnel.

Title

Found 41 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 41 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 41 Documents
Search