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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 217 Documents
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An Efficient Journal Articles Searching using Vector Space Model Algorithm Alvriyanto, Azis; Nuruzzaman, Muhammad Taufiq; Siregar, Maria Ulfah; Hidayat, Rahmat
IJID (International Journal on Informatics for Development) Vol. 9 No. 1 (2020): IJID June
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2020.09104

Abstract

One of the main feature of digital library is a search engine which depends on keywords submitted by a user. However, in the traditional algorithm, the computation performance, searching speed, significantly relies on the number of journal articles stored in the databases. Some irrelevant search results also increase the speed of article searching process. To solve the problem, in this paper we propose vector space model (VSM) algorithm to search for relevant journal articles. The VSM algorithm considers a term frequency - inversed document frequency (TF-IDF). The VSM algorithm will be compared to the baseline algorithm namely traditional algorithm. Both algorithms will be evaluated using combination of keywords which can be a synonym, phrase, error typography, or suffix and prefix. By using the data consist of 635 journal articles, both algorithms are compared in terms of 11 evaluation criteria. The results show that VSM algorithm is able to obtain the intended journal at 5th rank on average as compared to the traditional algorithm which can obtain the intended journal at rank of 171st on average. Therefore, our proposed algorithm can improve the performance to accurately sort the journal articles based on the submitted keywords as compared to traditional algorithm.   
Analysis of Fuzzy Logic Modification for Student Assessment in e-Learning Wardoyo, Retantyo; Yuniarti, Wenty Dwi
IJID (International Journal on Informatics for Development) Vol. 9 No. 1 (2020): IJID June
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2020.09105

Abstract

The phenomenon of the rapid transfer of learning to online systems, such as e-Learning, has occurred massively. Institutions must ensure that student assessments run well. The characteristics of learning in e-Learning require an appropriate assessment method. The fuzzy logic method can be an option. Research shows that fuzzy logic is capable of providing flexible and objective performance evaluation. Fuzzy logic is a method that can overcome the uncertainty of transparency and objectivity of student assessments. In general, fuzzy logic applications are carried out by standards. Modification is an attempt to reveal the flexibility and to optimize the use of fuzzy logic. This study presents an analysis of fuzzy logic modification for the assessment of Algorithm and Data Structures courses held in e-Learning. These modifications include (i) modification of the parameter score with score compatibility, (ii) consequent modification of the fuzzy rules and (iii) modification of the implication process. The study results show that although the use of fuzzy logic requires more complicated procedures and tools, it can present various kinds of assessment as an option for educators to assess students in e-Learning.
Implementation of Web Scraping to Build a Web-Based Instagram Account Data Downloader Application Himawan, Arif; Priadana, Adri; Murdiyanto, Aris
IJID (International Journal on Informatics for Development) Vol. 9 No. 2 (2020): 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.2020.09201

Abstract

Instagram has been used by many groups, such as business people, academics, to politicians, to take advantage of the insights gained by processing and analyzing Instagram data for various purposes. However, before processing and analyzing data, users must first pass data collection or downloading from Instagram. The problem faced is that most data collection methods are still done manually as for many parties that offer Instagram account data download services with various price options. This research applied a web scraping method to automatically build a web-based Instagram account data download application so that several parties can use it. The web scraping method was chosen because by using this method, researchers do not need to use Instagram's Application Programming Interface (API), which has access restrictions in retrieving data on Instagram. In this study, application testing was conducted on 15 Instagram accounts with various publications, namely between 100 and 11000. Based on the download data analysis results, the application of the web scraping method to download Instagram account data can successfully download a maximum of 2412 account data. In this application, users can download Instagram account data to Data Collection and then manage it like deleting and exporting data collection in the form of CSV, Excel, or JSON.
Feature Selection Method to Improve the Accuracy of Diabetes Mellitus Detection Instrument Wulandari, Sari Ayu; Madnasri, Sutikno; Pramitasari, Ratih; Susilo, Susilo
IJID (International Journal on Informatics for Development) Vol. 9 No. 2 (2020): 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.2020.09203

Abstract

The need for aroma recognition devices or often known as enose (electronic nose), is increasing. In the health field, enose can detect early diabetes mellitus (DM) type 2 from the aroma of urine. Enose is an aroma recognition tool that uses a pattern recognition algorithm to recognize the urine aroma of diabetics based on input signals from an array of gas sensors. The need for portable enose devices is increasing due to the increasing need for real-time needs. Enose devices have an enormous impact on the choice of the gas sensor Array in the enose. This article discusses the effect of the number of sensor arrays used on the recognition results. Enose uses a maximum of 4 sensors, with a maximum feature matrix. After that, the feature matrix enters the PCA (Principal Component Analysis) feature extraction and clustering using the FCM (Fuzzy C Means) method. The number of sensors indicates the number of features. Enose using method for feature selection, it’s a variation from 4 sensors, where experiment 1 uses 4 sensors, experiment 2 uses a variation of 3 sensors and experiment 3 uses a variation of 2 sensors. Especially for sensors 3 and 4 using feature extraction method, PCA (Principal Component Analysis), to reduce features to only 2 best features. As for the variation of 2 sensors use primer feature matrix. After feature selection, the number of features is 2 out of 11 variations. Next, do the grouping using the FCM (Fuzzy C Means) method. The results show that using two sensors has a high accuracy rate of 92.5%.
Public Sentiments Analysis about Indonesian Social Insurance Administration Organization on Twitter Rahmawati, Siti; Habibi, Muhammad
IJID (International Journal on Informatics for Development) Vol. 9 No. 2 (2020): 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.2020.09205

Abstract

Insurance Administration Organization, which can be used by all people. However, this organization has received various criticisms from the public through social media, namely Twitter. This study aims to analyze public sentiment about the Indonesian Social Insurance Administration Organization on Twitter. The method used in this research is the Naive Bayes Classifier (NBC) method and uses the Support Vector Machine (SVM) method as a comparison. The amount of data used was 12,990 tweets with a data collection period from September 14, 2019 - February 18, 2020. The study compared the two classifier models built, namely the classifier model with two sentiment classes and four sentiment classes. The accuracy results show that the SVM method has a better accuracy value than the NBC method. SVM has an accuracy value of 63.60% and 82.77% for the two sentiment classes in the four sentiment classifier model. The tweet classification results show that the public's conversation about the Indonesian Social Insurance Administration Organization on Twitter has a negative polarity value tendency.
Cover and Table of Content ijid, Ijid
IJID (International Journal on Informatics for Development) Vol. 9 No. 1 (2020): IJID June
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2020.%x

Abstract

Online Integrated Development Environment (IDE) in Supporting Computer Programming Learning Process during COVID-19 Pandemic: A Comparative Analysis Kusumaningtyas, Kartikadyota; Nugroho, Eko Dwi; Priadana, Adri
IJID (International Journal on Informatics for Development) Vol. 9 No. 2 (2020): 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.2020.09202

Abstract

COVID-19 has spread to various countries and affected many sectors, including education. New challenges arise in universities with study programs related to computer programming, which require a lot of practice. Difficulties encountered when students should setting up the environment needed to carry out programming practices. Furthermore, they should install a text editor called Integrated Development Environment (IDE) to support it. There is various online IDE that supports computer programming. However, students must have an internet connection to use it. After all, many students cannot afford to buy internet quotas to access online learning material during the COVID-19 pandemic. According to these problems, this study compares several online IDEs based on internet data usage and the necessary supporting libraries' availability. In this study, we only compared eleven online IDEs that support the Python programming language, free to access, and do not require logging in. Based on the comparative analysis, three online IDEs have most libraries supported. They are REPL.IT, CODECHEF, and IDEONE. Based on internet data usage, REPL.IT is an online IDE that requires the least transferred data. Moreover, this online IDE also has a user-friendly interface to place the left and right sides' code and output positions. It prevents the user from scrolling to see the results of the code that has been executed. The absence of advertisements also makes this online IDE a more focused appearance. Therefore, REPL.IT is highly recommended for users who have a limited internet quota, primarily to support the learning phase of computer programming during the COVID-19 pandemic.
Implementation Improvement Analysis of M-Library Application and Related Business Processes at XYZ University Khoiriyah, Rizqiyatul; Handayani, Devi; Bhimadi, Tungga
IJID (International Journal on Informatics for Development) Vol. 9 No. 2 (2020): 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.2020.09204

Abstract

XYZ University library provides offline and online book loan services. The library's online service uses the m-library application. This study aims to see the  implementation of the m-library application and see the extent of the evaluation of the application. The m-library application is used for the process of borrowing books, viewing catalogs, and reading book online. The method used in this research is qualitative descriptive through interviewing interviewees and observing applications. The results of this study are that there are several benefits and weaknesses to the m-library application. From these shortcomings, it can be recommended to increase the implementation of the m-library application, namely the need for application development towards menu flexibility and application services, ease of online membership registration process, compatibility of online and offline book catalogs and more effective use of application features according to the University library business process. This application also requires broader socialization to the university academic community so that its use is more optimum.
Online Public Access Catalogue: Factors Affecting Use E-Catalog Ardiani, Farida
IJID (International Journal on Informatics for Development) Vol. 9 No. 2 (2020): 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.2020.09206

Abstract

Online Public Access Catalog (OPAC) is one of the e-catalog information technologies applied in libraries. OPAC is a library information retrieval system that can be accessed online. State Islamic University of Sunan Kalijaga Yogyakarta has been using OPAC since 2012 and OPAC users are increasing from year to year. An information system will be used by users if it suits their needs. The successful implementation of OPAC raises questions about the factors that influence this success. For this reason, this study aims to determine the factors that influence users to use OPAC. Structural Equation Modeling (SEM) is a multivariate statistical technique which is a combination of factor analysis and regression analysis (correlation) which aims to examine the relationships between variables in a model. Processing using SEM will be carried out to find the relationship between the variables to be tested, which variables are interconnected, and are there any unrelated variables. The results of processing the variables using SEM can show what variables attract users to use the e-catalog. Acceptance of information systems can be measured by several evaluation models that have been developed at this time. There are many evaluation models used to measure. Technology Acceptance Model (TAM) is the appropriate model to use for this study, because this study is about the acceptance of a system. In addition, several previous studies used by researchers as references also used TAM as their study method to assess user acceptance of a system. This study modifies TAM, which is used to determine user acceptance of an information system, by adding three exogenous variables, information quality, perceived enjoyment, and user interface. Results of this study proved that information quality, user interface, perceived usefulness, perceived ease of use, and behavioral intention to use, are all factors that influence the actual use of OPAC. Perceived enjoyment is a variable that cannot be proved affects the actual use of OPAC.
Research Trend of Causal Machine Learning Method: A Literature Review Arti, Shindy; Hidayah, Indriana; Kusumawardani, Sri Suning
IJID (International Journal on Informatics for Development) Vol. 9 No. 2 (2020): 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.2020.09208

Abstract

Machine learning is commonly used to predict and implement  pattern recognition and the relationship between variables. Causal machine learning combines approaches for analyzing the causal impact of intervention on the result, asumming a considerably ambigous variables. The combination technique of causality and machine learning is adequate for predicting and understanding the cause and effect of the results. The aim of this study is a systematic review to identify which causal machine learning approaches are generally used. This paper focuses on what data characteristics are applied to causal machine learning research and how to assess the output of algorithms used in the context of causal machine learning research. The review paper analyzes 20 papers with various approaches. This study categorizes data characteristics based on the type of data, attribute value, and the data dimension. The Bayesian Network (BN) commonly used in the context of causality. Meanwhile, the propensity score is the most extensively used in causality research. The variable value will affect algorithm performance. This review can be as a guide in the selection of a causal machine learning system.

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