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All Journal Perfecting a Video Game with Game Metrics JITK (Jurnal Ilmu Pengetahuan dan Komputer) ILKOM Jurnal Ilmiah Indonesian Journal of Electrical Engineering and Computer Science Conference on Business, Social Sciences and Technology (CoNeScINTech)
Mohd Sanusi Azmi
Universiti Teknikal Malaysia Melaka
Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science

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New instances classification framework on Quran ontology applied to question answering system Fandy Setyo Utomo; Nanna Suryana; Mohd Sanusi Azmi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 1: February 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i1.9794

Abstract

Instances classification with the small dataset for Quran ontology is the current research problem which appears in Quran ontology development. The existing classification approach used machine learning: Backpropagation Neural Network. However, this method has a drawback; if the training set amount is small, then the classifier accuracy could decline. Unfortunately, Holy Quran has a small corpus. Based on this problem, our study aims to formulate new instances classification framework for small training corpus applied to semantic question answering system. As a result, the instances classification framework consists of several essential components: pre-processing, morphology analysis, semantic analysis, feature extraction, instances classification with Radial Basis Function Networks algorithm, and the transformation module. This algorithm is chosen since it robustness to noisy data and has an excellent achievement to handle small dataset. Furthermore, document processing module on question answering system is used to access instances classification result in Quran ontology.
Framework of diacritic segmentation for Arabic handwritten document Ahmed Abdalla Shiekh; Mohd Sanusi Azmi; Maslita Abd Aziz; Mohammed Nasser Al-Mhiqani; Salem Saleh Bafjaish
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp1001-1008

Abstract

In recent Arabic standard language and Arabic dialectal texts, diacritics and short vowels are absent. There are some exceptions have been made for the Arabic beginner learner scripts, religious texts and as well as a significant political text. In addition, the text without diacritics is considered ambiguous due to numerous words with different diacritic marks seem identical. However, this paper we present a framework for segmenting diacritics from Arabic handwritten document by using region-based segmentation technique. Since Arabic handwritten and Mushaf Al-Quran contain many diacritical marks. Hence, the diacritics must be properly extracted from Arabic handwritten document to avoid losing some good features. Furthermore, the proposed framework is devised specifically to segment diacritics from Arabic handwritten image, thus there will be no feature extraction, feature selection, and classification processes included. Besides, we will present the methodology that is used to fulfil the objectives of this paper. The pre-processing phases will be explained and more specifically segmentation phase for segmenting diacritics which is the phase we concentrate more in this article. Lastly, we will identify the proposed technique region-based segmentation to facilitate our development throughout the experimental process.
Skew correction for mushaf Al-Quran: a review Salem Saleh Bafjaish; Mohd Sanusi Azmi; Mohammed Nasser Al-Mhiqani; Ahmed Abdalla Sheikh
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 1: January 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i1.pp516-523

Abstract

Skew correction have been studied a lot recently. However, the content of skew correction in these studies is considered less for Arabic scripts compared to other languages. Different scripts of Arabic language are used by people. Mushaf A-Quran is the book of Allah swt and used by many people around the world. Therefore, skew correction of the pages in Mushaf Al-Quran need to be studied carefully. However, during the process of scanning the pages of Mushaf Al-Quran and due to some other factors, skewed images are produced which will affect the holiness of the Mushaf Al-Quran. However, a major difficulty is the process of detecting the skew and correcting it within the page. Therefore, this paper aims to view the most used skew correction techniques for different scripts as cited in the literature. The findings can be used as a basis for researchers who are interested in image processing, image analysis, and computer vision.
Internet of things: security requirements, attacks and counter measures Maria Imdad; Deden Witarsyah Jacob; Hairulnizam Mahdin; Zirawani Baharum; Shazlyn Milleana Shaharudin; Mohd Sanusi Azmi
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1520-1530

Abstract

Internet of Things (IoT) is a network of connected and communicating nodes. Recent developments in IoT have led to advancements like smart home, industrial IoT and smart healthcare etc. This smart life did bring security challenges along with numerous benefits. Monitoring and control in IoT is done using smart phone and web browsers easily.  There are different attacks being launched on IoT layers on daily basis and to ensure system security there are seven basic security requirements which must be met. Here we have used these requirements for classification and subdivided them on the basis of attacks, followed by degree of their severity, affected system components and respective countermeasures. This work will not only give guidelines regarding detection and removal of attacks but will also highlight the impact of these attacks on system, which will be a decision point to safeguard  system from high impact attacks on priority basis.
Implementation of Advanced SQL Using Java Server Pages as Frontend Nur Atikah Arbain; Abdul Razak Hussain; Norhayati Harum; Mohd Sanusi Azmi
Conference on Business, Social Sciences and Technology (CoNeScINTech) Vol 3 No 1 (2023): Conference on Business, Social Sciences and Technology (CoNeScINTech)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/conescintech.v3i1.8328

Abstract

In web-based applications, communication between web (frontend) and database (backend) is crucial as it is not only used to store and retrieve data but also to perform other processes either at the frontend or backend. However, the process that is performed at frontend could lead to data leak due to weak security. Therefore, this paper presents the idea by storing all process including prepared statements of Create, Retrieve, Update and Delete (CRUD) and calculations into database using PL/SQL programming language (Oracle) where web based of Java Server Pages (JSP) is used as a frontend. The framework of Model View Controller (MVC) is applied as the guideline to handle the development of web based. Besides events advanced SQL such as stored procedures, functions and trigger event are implemented where they are used to commit the operation of CRUD. As the output, all operation of CRUD, calculation, error handling (exception handlers) is committed and process at backend while frontend is used only to display data and send input from user. As conclusion, the transaction data between web and database can be secured as well as all processes are performed in the database.
MUSIC RECOMMENDATION SYSTEM BASED ON COSINE SIMILARITY AND SUPERVISED GENRE CLASSIFICATION Jamie Mayliana Alyza; Fandy Setyo Utomo; Yuli Purwati; Bagus Adhi Kusuma; Mohd Sanusi Azmi
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 9 No 1 (2023): JITK Issue August 2023
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v9i1.4324

Abstract

Categorizing musical styles can be useful in solving various practical problems, such as establishing musical relationships between songs, similar songs, and finding communities that share an interest in a particular genre. Our goal in this research is to determine the most effective machine learning technique to accurately predict song genres using the K-Nearest Neighbors (K-NN) and Support Vector Machine (SVM) algorithms. In addition, this article offers a contrastive examination of the K-Nearest Neighbors (K-NN) and Support Vector Machine (SVM) when dimensioning is considered and without using Principal Component Analysis (PCA) for dimension reduction. MFCC is used to collect data from datasets. In addition, each track uses the MFCC feature. The results reveal that the K-Nearest Neighbors and Support Vector Machine offer more precise results without reducing dimensions than PCA results. The accuracy of using the PCA method is 58% and has the potential to decrease. In this music genre classification, K-Nearest Neighbors (K-NN) and Support Vector Machine (SVM) are proven to be more efficient classifiers. K-Nearest Neighbors accuracy is 64,9%, and Support Vector Machine (SVM) accuracy is 77%. Not only that, but we also created a recommender system using cosine similarity to provide recommendations for songs that have relatively the same genre. From one sample of the songs tested, five songs were obtained that had the same genre with an average accuracy of 80%.
Rectified Linear Units and Adaptive Moment Estimation Optimizer on ANN with Saved Model Prediction to Improve The Stock Price Prediction Framework Performance Sekhudin Sekhudin; Yuli Purwati; Fandy Setyo Utomo; Mohd Sanusi Azmi; Pungkas Subarkah
ILKOM Jurnal Ilmiah Vol 15, No 2 (2023)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v15i2.1586.271-282

Abstract

A stock is a high-risk, high-return investment product. Prediction is one way to minimize risk by estimating future prices based on past data. There are limitations to solving the stock prediction problem from previous research: limited stock data, practical aspects of application, and less than optimal stock price prediction results. The main objective of this study is to improve the prediction performance by formulating and developing the stock price prediction framework. Furthermore, the research provides a stock price prediction framework that can produce better prediction results than the previous study with fast computation time. The proposed framework deals with data generation, pre-processing and model prediction. In further, the proposed framework includes two prediction methods for predicting stock closing prices: stored model prediction and current model prediction. This study uses an artificial neural network with Rectified Linear Units as an activation function and Adam Optimizer to predict stock prices. The model we have built for each forecasting method shows a better MAPE value than the model in previous studies. Previous research showed that the lowest MAPE was 1.38% for TLKM shares and 0.81% for BBRI. Our proposed framework based on the stored model prediction method shows a MAPE value of 0.67% for TLKM shares and 0.42% for BBRI. While the current model prediction method shows a MAPE value of 0.69% for TLKM shares and 0.89% for BBRI. Furthermore, the stored model prediction method takes 1.0 seconds to process a single prediction request, while the current model prediction takes 220 seconds.
Co-Authors Abdul Razak Hussain Ahmed Abdalla Sheikh Ahmed Abdalla Shiekh Bagus Adhi Kusuma Deden Witarsyah Fandy Setyo Utomo Fandy Setyo Utomo Hairulnizam Mahdin Jamie Mayliana Alyza Maria Imdad Maslita Abd Aziz Mohammed Nasser Al-mhiqani Nanna Suryana Norhayati Harum Nur Atikah Arbain Pungkas Subarkah Salem Saleh Bafjaish Sekhudin Sekhudin Shazlyn Milleana Shaharudin Yuli Purwati Zirawani Baharum