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Sujacka Retno
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Journal of Advanced Computer Knowledge and Algorithms
Published by Universitas Malikussaleh
ISSN : -     EISSN : 30318955     DOI : http://doi.org/10.29103/jacka.v1i1.14530
Core Subject : Science,
Computer Science & IT
JACKA journal published by the Informatics Engineering Program, Faculty of Engineering, Universitas Malikussaleh to accommodate the scientific writings of the ideas or studies related to informatics science. JACKA journal published many related subjects on informatics science such as (but not limited to): Adversarial Machine Learning: Addressing security concerns and developing algorithms robust to adversarial attacks. Anomaly Detection Algorithms: Identifying unusual patterns or outliers in data. Automated Machine Learning (AutoML): Developing algorithms that automate the machine learning model selection and hyperparameter tuning. Automated Planning and Scheduling: Developing algorithms for autonomous decision-making and task scheduling. Bayesian Networks: Utilizing probability theory to model and analyze uncertain systems. Computer Vision: Developing algorithms for image and video analysis, enabling machines to interpret visual information. Constraint Satisfaction Problems (CSP): Designing algorithms to solve problems subject to constraints. Deep Learning: Developing algorithms for neural networks with multiple layers to model complex patterns. Distributed AI Algorithms: Implementing AI algorithms that can work across multiple interconnected devices or nodes. Ensemble Learning: Combining multiple models to improve overall system performance. Evolutionary Algorithms: Utilizing principles of natural selection for optimization and problem-solving. Experiential Learning Algorithms: Designing algorithms that improve performance through experience and learning. Expert Systems: Creating rule-based systems that emulate human expertise in specific domains. Explainable AI (XAI): Developing algorithms that provide transparency and explanations for AI decisions. Fuzzy Logic: Implementing logic that deals with uncertainty and imprecision in decision-making. Genetic Algorithms: Implementing algorithms inspired by genetic evolution for optimization tasks. Knowledge Representation and Reasoning: Creating structures and algorithms to represent and manipulate knowledge. Machine Learning Algorithms: Designing algorithms that enable systems to learn from data and make predictions. Multi-agent Systems: Designing algorithms for systems with multiple interacting agents. Natural Language Processing (NLP): Creating algorithms that understand and process human language. Neuroevolution: Combining evolutionary algorithms with neural networks for optimization. Optimization Algorithms: Developing algorithms focused on improving the performance, efficiency, or decision-making of systems by finding optimal solutions to problems. Pattern Recognition: Developing algorithms to identify patterns within data. Reinforcement Learning: Designing algorithms that learn through trial and error, often applied in decision-making systems. Robotics Algorithms: Designing algorithms for autonomous navigation, manipulation, and decision-making in robots. Semantic Web Technologies: Implementing algorithms for structuring and retrieving information on the web. Sentiment Analysis Algorithms: Analyzing text data to determine sentiment or emotion. Speech Recognition: Developing algorithms to convert spoken language into text. Swarm Intelligence: Developing algorithms based on collective behavior, as seen in swarms or colonies. Time Series Forecasting Algorithms: Predicting future values based on historical data patterns.
Arjuna Subject : Ilmu Komputer (semua kategori) - Teori Komputasi dan Matematika
Articles 50 Documents
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Analysis of the Naïve Bayes Classifier Method in Classifying the Weather Conditions in Aceh Tamiang Syafira, Defy
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 2 (2024): Journal of Advanced Computer Knowledge and Algorithms - April 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i2.15889

Abstract

Naive Bayes Classifier is a method that aims to predict future conditions. This method is a sub-part of classification algorithms. In this study, tests were tested out to predict weather conditions at a certain time. The results of the studies carried out on 4 weather conditions in 3 different cities in Indonesia using Naive Bayes Classifier method the accurate prediction accuracy is 92.1%, while using ARIMA (Autoregressive Integrated Moving Average) method the accuracy results obtained are 86.8 %. These results indicate that Naive Bayes Classifier has a greater percentage level of accuracy than ARIMA, which is 5.3%.
Implementation of Finite State Automata Method in Text to Speech Conversion System Meiyanti, Rini; Sandy, Cut Lika Mestika
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 3 (2024): Journal of Advanced Computer Knowledge and Algorithms - July 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i3.16917

Abstract

Sound processing uses a variety of methods. One of them is converting writing into sound or commonly known as Text To Speech.Text To Speech is a tool for converting writing input into sound by changing the phoneme of writing.Text To Speech Text To Speech consists of two sub-systems namely word to phoneme converters and phoneme to speech converter. The phoneme itself consists of word fragments that have different speech from one another with each other. To perform the phoneme separation process, the Finite State Automata method. Finite State Automata can recognise the simplest language and is an abstract machine whose input and output are discrete. The input system that is processed by the system only consists of two words. If there are more than two word inputs, the programme will not be able to perform word separation properly. After the word separation is done, then the system performs phoneme to speech converter.The resulting speech is processed by the Indo_TTS database which was database developed using the diphone prosody method concatenation prosody methodThe word that has been separated will be stored into the MySQL database as a result of words that have been tested by the system. Later this system will be intended for general public, students and people with speech impairment. The percentage of successful syllable separation and homograph sound output is 98.7% in the programme's success rate.
Comparison of Chen's Fuzzy Time Series and Triple Exponential Smoothing in Forecasting Medicine Stocks at the Blang Cut Kuala Community Health Center Devi, Salma; Yunizar, Zara; Retno, Sujacka
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 3 (2024): Journal of Advanced Computer Knowledge and Algorithms - July 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i3.16870

Abstract

Forecasting is estimating future conditions by examining conditions in the past. In social life, everything is uncertain and difficult to predict precisely, so forecasting is needed. Efforts are always made to make forecasts in order to minimize the influence of this uncertainty on a problem. In other words, forecasting aims to obtain forecasts that can minimize forecast errors, which are usually measured by the mean absolute percentage error. This method is usually used for time series-based forecasting and uses data or information from the past as a reference when predicting current data. This research will compare the application of the Fuzzy Time Series Chen method and the Triple Exponential Smoothing method in forecasting drug stock determination at the Kuala Community Health Center, Blang Mangat District, Lhokseumawe City Regency, Aceh. The research results showed that the Triple Exponential Smoothing method was better in forecasting drug stock inventories compared to Chen's Fuzzy Time Series method. Chen's Fuzzy Time Series method produces a MAPE value of 17.67%, which means it has an accuracy of 82.33%, while the Triple Exponential Smoothing method produces a MAPE value of 9.842%, which means it has an accuracy of 90.158%
The Application of the K-Nearest Neighbor (KNN) Method to Determine House Locations in the Batuphat and Tambon Tunong Areas, Aceh Khairi, Abil; Fahrezi, Irgi; Sahputra, Irfan; Anshari, Said Fadlan
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 1 (2024): Journal of Advanced Computer Knowledge and Algorithms - January 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i1.14531

Abstract

This study aims to apply the K-Nearest Neighbors (KNN) method to find the location of a house situated precisely on the border between Batuphat and Tambon Tunong. The issue faced by the college friends is the difficulty in determining whether the house falls within the Batuphat or Tambon Tunong area. The KNN method is used due to its ability to classify based on the nearest neighbors' distance.The data used in this research includes information on the house's location and the Batuphat and Tambon Tunong areas. The training process is conducted to form the KNN model based on the known location data, while the testing process is employed to classify the unknown house location into either the Batuphat or Tambon Tunong area.The results of the study demonstrate that the KNN method can be utilized to determine the location of a house situated on the border between Batuphat and Tambon Tunong. By considering the nearest neighbors' distance, the house can be classified into one of the areas with a high level of accuracy.This research contributes to providing a solution for college friends who face difficulties in determining the house location on the Batuphat and Tambon Tunong border. The KNN method can serve as an effective tool in addressing this problem. Moreover, this study can serve as a basis for further development in the field of location classification based on the KNN method.
Implementation of Tsukamoto Fuzzy Logic to Determine Sheep Livestock Population Based on Gender and Age Category in Aceh Tamiang Regency Agusniar, Cut; Khaira, Raziatul; Ramadan, Rifki
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 3 (2024): Journal of Advanced Computer Knowledge and Algorithms - July 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i3.16877

Abstract

This study implements the Tsukamoto Fuzzy Logic method to determine the sheep livestock population based on gender and age categories in Aceh Tamiang Regency. The population data of male and female sheep are categorized into three age groups: young, adolescent, and adult. The processes of fuzzification, fuzzy inference, and defuzzification are used to model the data and produce more accurate population predictions. Fuzzy rules are applied to consider the combination of membership levels of each age category and gender. The analysis results indicate that the sheep livestock population in Aceh Tamiang Regency is 5553,69007. The Tsukamoto Fuzzy Logic method has proven effective in handling uncertainty and variability in livestock population data, providing flexibility in complex data-driven decision-making. This study makes a significant contribution to the utilization of fuzzy logic methods for planning and managing livestock populations and can serve as a reference for policymakers in the livestock sector.
Web-Based Expert System Application for Early Diagnosis of HIV/AIDS Using the Naive Bayes Method Aisah, Sri Purwani; Adek, Rizal Tjut; Yunizar, Zara
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 4 (2024): Journal of Advanced Computer Knowledge and Algorithms - October 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i4.17809

Abstract

AIDS is a progressive decrease in the immune system so that opportunistic infections can appear and end in death, therefore the author created an early diagnosis system for HIV/AIDS using the website-based Naïve Bayes algorithm. Naïve Bayes is a simple probability classification that can calculate all possibilities by combining a number of combinations and frequencies of a value from the database obtained.the results of the research obtainedThe naïve Bayes algorithm can be implemented for early diagnosis of HIV/AIDS by means that the existing HIV/AIDS symptom data is adjusted to the patient's symptom data processed using the naïve Bayes algorithm and then it is concluded what the symptoms are and What is the solution.
Virtual Private Cloud (VPC) & Elastic Compute Cloud (EC2) with Remote Access Using PuTTY Terminal on Ubuntu in a Private VPN Syahputra, Irwanda; Akram, Rizalul
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 3 (2024): Journal of Advanced Computer Knowledge and Algorithms - July 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i3.16924

Abstract

One of the computer technologies that is commonly used by agencies/companies is the internet network which functions as a bridge to connect between one point to another. Apart from having the advantage of being a medium for long-distance communication, the internet also has a lack of security. One of the weakness found is the internet as a transmission medium for important or confidential data. One effort that can be made to overcome this problem is to build a private network in a public network service, which is often known as a Virtual Private Network (VPN). In this research, the VPN was built by combining a Virtual Private Cloud (VPC) with Elastic Compute Cloud (EC2) and using Ubuntu's Terminal in PuTTY Gen as remote access using network protocols for remote server needs from remote control.
Implementation of Data Mining for Vertigo Disease Classification Using the Support Vector Machine (SVM) Method Jasmin, Nadya; Dinata, Rozzi Kesuma; Sahputra, Ilham
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 4 (2024): Journal of Advanced Computer Knowledge and Algorithms - October 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i4.17807

Abstract

This research aims to implement advanced data mining techniques for the classification of vertigo disorders using the Support Vector Machine (SVM) method. Vertigo, characterized by a spinning sensation, can be triggered by various factors such as nervous system disorders and inner ear infections. With the rising prevalence of vertigo patients, there is a pressing need for more effective and efficient diagnostic tools. This study was conducted at Puskesmas Jangka in Bireuen Regency, involving the collection of vertigo patient data from the years 2023-2024. The collected data underwent a comprehensive preprocessing pipeline, including data cleaning, partitioning into training and testing datasets, and subsequent implementation of the SVM algorithm. The performance of the model was evaluated using the Mean Absolute Percentage Error (MAPE), resulting in a MAPE value of 28.47%.
Web Application Firewall (WAF) Design to Detect and Anticipate Hacking in Web-Based Applications Annas, Muhammad; Adek, Rizal Tjut; Afrillia, Yesy
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 3 (2024): Journal of Advanced Computer Knowledge and Algorithms - July 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i3.16315

Abstract

Data leakage cases have recently been rampant in Indonesia. One of the biggest is the leak of user data from BPJS Health in 2021, this data leak is certainly very detrimental to users. This research develops a Web Application Firewall (WAF) using ModSecurity and OWASP Core Rule Set to protect web applications from SQL Injection and XSS attacks. The methodology involves analyzing the functionality of the existing system using UML, with DVWA and WordPress as test objects. Results showed 100% SQL Injection and 99.8% XSS attack detection, with logs recording attacks in real-time. The findings emphasize the importance of WAF integration with web application built-in security, making significant contributions in the design and implementation of resilient WAFs, as well as improving resilience against evolving cyber threats.
Cover, Editorial Board, Acknowledgement and Table of Contents JACKA, JACKA
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 3 (2024): Journal of Advanced Computer Knowledge and Algorithms - July 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i3.17095

Abstract

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