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IJID (International Journal on Informatics for Development)
Published by Universitas Islam Negeri Sunan Kalijaga Yogyakarta
ISSN : 22527834     EISSN : 25497448     DOI : -
Core Subject : Science,
Computer Science & IT
One important point in the accreditation of higher education study programs is the availability of a journal that holds the results of research of many investigators. Since the year 2012, Informatics Department has English language. Journal called IJID International Journal on Informatics for Development. IJID Issues accommodate a variety of issues, the latest from the world of science and technology. One of the requirements of a quality journal if the journal is said to focus on one area of science and sustainability of IJID. We accept the scientific literature from the readers. And hopefully these journals can be useful for the development of IT in the world. Informatics Department Faculty of Science and Technology State Islamic University Sunan Kalijaga.
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Articles 8 Documents
 1 
Search results for , issue "Vol. 10 No. 2 (2021): IJID December" : 8 Documents clear
Handwriting Arabic Character Recognition Using Features Combination Qomariyah, Fitriyatul; Utaminingrum, Fitri; Muchlas, Muchlas
IJID (International Journal on Informatics for Development) Vol. 10 No. 2 (2021): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2021.2360

Abstract

The recognition of Arabic handwriting is a challenging problem to solve. The similarity among the fonts appears as a problem in the recognition processing. Various styles, shapes, and sizes which are personal and different across individuals make the Arabic handwriting recognition process even harder. In this paper, the data used are Arabic handwritten images with 101 sample characters, each of which is written by 15 different handwritten characters (total sample 101x15) with the same size (81x81 pixels). A well-chosen feature is crucial for making good recognition results. In this study, the researcher proposed a method of new features extraction to recognize Arabic handwriting. The features extraction was done by grabbing the value of similar features among various types of font writing, to be used as a new feature of the font. Then, City Block was used to compare the obtained feature to other features of the sample for classification. The Average accuracy value obtained in this study was up to 82%.
Analysis of Remote Access Trojan Attack using Android Debug Bridge Aprilliansyah, Deco; Riadi, Imam; Sunardi
IJID (International Journal on Informatics for Development) Vol. 10 No. 2 (2021): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2021.2839

Abstract

The security hole in the android operating system sometimes not realized by users such as malware and exploitation by third parties to remote access. This study conducted to identify the vulnerabilities of android operating system by using Ghost Framework. The vulnerability of the android smartphone are found by using the Android Debug Bridge (ADB) with the exploitation method as well as to analyze the test results and identify remote access Trojan attacks. The exploitation method with several steps from preparing the tools and connecting to the testing commands to the testing device have been conducted. The result shows that android version 9 can be remote access by entering the exploit via ADB. Some information has been obtained by third parties, enter and change the contents of the system directory can be remote access like an authorized to do any activities on the device such as opening lock screen, entering the directory system, changing the system, etc.
Sentiment Analysis of Tweets on Prakerja Card using Convolutional Neural Network and Naive Bayes Hardjita, Pahlevi Wahyu; Nurochman; Hidayat, Rahmat
IJID (International Journal on Informatics for Development) Vol. 10 No. 2 (2021): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2021.3007

Abstract

The Indonesian government launched the Prakerja (pre-employment) card in the midst of the COVID-19 pandemic, andthe local citizens have voiced their opinions about this controversial program through social media such as Twitter. People’scomments on it can be useful information, and this research tries to analyze the sentiment regarding the Prakerja Card programusing the Convolutional Neural Network and Naive Bayes methods. The main task in this sentiment analysis is analyzing the dataand then classifying them into one of the following classes: positive, negative or neutral. Naive Bayes is an algorithm that is often usedin sentiment analysis research, and the results have been very good. Convolutional neural network (CNN) is a deep learning algorithmthat uses one or more layers commonly used for pattern recognition and image recognition. Having applied these methods, thisresearch found that the CNN model with the GlobalMaxPooling layer is the best model of the other two CNN models. Sentimentanalysis has the best accuracy of 78.5% on the CNN method, and NBC of 76.2% accuracy. The best accuracy result in K-fold withfive classes is 85.4% on the CNN model with a learning rate optimization of 0.00158. While the average accuracy on NBC only reached75.3%
Face Mask Wearing Detection Using Support Vector Machine (SVM) Muhammad Nur Yasir Utomo; Fajrin Violita
IJID (International Journal on Informatics for Development) Vol. 10 No. 2 (2021): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2021.3038

Abstract

As an effort to prevent the spread of the Covid-19, various countries have implemented health protocol policies such as work-from-home, social distancing, and face mask-wearing in public places. However, monitoring compliance with the policy is still difficult, especially for the face mask policy. It is still managed by humans and is costly. Thus, this research proposes a face mask-wearing detection using a soft-margin Support Vector Machine (SVM). There are three main stages: feature selection and preprocessing, model training, and evaluation. During the first stage, the dataset of 3833 images (1915 images with face masks and 1918 images without face masks) was prepared to be used in the training stage. The training stage was conducted using SVM added with the soft-margin objective to overcome images that could not be separated linearly. At the final stage, evaluation was conducted using a confusion matrix with 10 folds cross-validation. Based on the experiments, the proposed method shows a performance accuracy of 91.7%, a precision of 90.3%, recall of 93.5%, and an F-measure of 91.8%. Our method also worked fast, taking only 0.025 seconds to process a new image. It is 7.12 times faster than Deep Learning which requires 0.18 seconds for one classification.
The Relational Data Model on The University Website with Search Engine Optimization Alifi, Muhammad Riza; Hayati, Hashri; Wonoseto, Muhammad Galih
IJID (International Journal on Informatics for Development) Vol. 10 No. 2 (2021): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2021.3223

Abstract

The visibility of a university’s website on the search engine becomes an essential factor to reach a wider audience. One way to improve the visibility of a website is through Search Engine Optimization (SEO). University’s website development with SEO is inseparable from the data model because SEO supporting factors are parts of the consideration in the components and structure of the data model. This study aims to build a data model for a university website accompanied by SEO. The relational data model is used in this study based on the performance and maturity in defining schema-based design. This study was conducted through four sequential stages: literature review, planning, implementation, and evaluation. The resulting relational data model is one that has accommodated four supporting factors for SEO, namely Meta description, Meta keywords, URL structure, and image description. This study has succeeded in building a relational data model at the abstraction level of conceptual and logical.  In the conceptual data model, one entity and 11 attributes are formed. The logical data model was implemented in independent work environments using RelaX and operational requirements can be fulfilled by representing each table or relationship in the schema using relational algebra.
A Sign Language Prediction Model using Convolution Neural Network. Ndungi, Rebeccah; Karuga, Samuel
IJID (International Journal on Informatics for Development) Vol. 10 No. 2 (2021): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2021.3284

Abstract

The barrier between the hearing and the deaf communities in Kenya is a major challenge leading to a major gap in the communication sector where the deaf community is left out leading to inequality. The study used primary and secondary data sources to obtain information about this problem, which included online books, articles, conference materials, research reports, and journals on sign language and hand gesture recognition systems. To tackle the problem, CNN was used. Naturally captured hand gesture images were converted into grayscale and used to train a classification model that is able to identify the English alphabets from A-Z.  Then identified letters are used to construct sentences. This will be the first step into breaking the communication barrier and the inequality.  A sign language recognition model will assist in bridging the exchange of information between the deaf and hearing people in Kenya. The model was trained and tested on various matrices where we achieved an accuracy score of a 99% value when run on epoch of 10, the log loss metric returning a value of 0 meaning that it predicts the actual hand gesture images. The AUC and ROC curves achieved a 0.99 value which is excellent.
A Preliminary Study of the Integration of Big Data to Answer the Challenges of Islamic Education in the Technological Age Wandansari, Sarah Adilah; Islam, Fadli Jihadul; Rahma, Dinne
IJID (International Journal on Informatics for Development) Vol. 10 No. 2 (2021): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2021.3319

Abstract

Along with the rapid development of technology, individuals today are required to align every aspect of their lives with the technological developments of the industrial revolution 4.0, consisting of artificial intelligence, the internet of things, and big data presented in society. Notably, it was related to education, including Islamic education, which frequently stereotyped about delays in responding to globalization's challenges. This preliminary study aims to encourage empirical research that is still lacking by exploring the role of big data in Islamic education and combining data from general education that has similar a core. The study focused on using the scoping review method as a part of a literature review. As a result of this study, there are four impacted factors for strengthening the usage of big data: the performance and behavior factors of learning; the storage of education data; the update in the education system; and the use of big data in the education curriculum. Future studies should begin empirical research to elaborate more on these four impacted factors practically. 
Satisfaction Level from Digital Learning Implementation Using E-Learning Management System (LMS) UP45 at University of Proklamasi 45 Prayogo, Agung; Hartiyani, Selvy Dwi; Hartiyani, Erlinawaty; Dewi, Puti Adam
IJID (International Journal on Informatics for Development) Vol. 10 No. 2 (2021): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2021.3396

Abstract

Learning process in campus has undergone several fundamental changes since the COVID-19 pandemic. The face-to-face lectures cannot be fully implemented due to the increasing number of COVID-19 cases. The education sector continues to make some improvisation in learning methods. This study aims to measure the level of operational feasibility of a Moodle-based Learning Management System at University of Proklamasi 45 Yogyakarta. This study used Taro Yamane Formula as the sampling method. There are 1517 total students in the population with a minimum sample of 94 (error margin of 10%) requirement (actual sample = 120). The data were obtained from the dissemination of questionnaires, using linked scales processed using SPSS software. The respondents are the students, lecturers and academic staffs as the person in charge of the e-learning platform UP45. This method resulted in a decision on the use of e-learning along with the operational feasibility of the online learning system implemented at University of Proklamasi 45 Yogyakarta. The general conclusion of this study is that the operational feasibility of E-Learning UP45 Yogyakarta, can be used as a digital learning solution during the Covid-19 pandemic. The valid percentage that supports the implementation and maintenance of an online learning LMS-based is 72.5%.

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