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All Journal IJID (International Journal on Informatics for Development)
Minati, Sekar
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Computer Science & IT

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Self-Evaluation of Jurnal Informatika Sunan Kalijaga (JISKa): Perspectives of Reviewers and Authors Gunawan, Eko Hadi; Wonoseto, Muhammad Galih; Minati, Sekar; Nuruzzaman, Muhammad Taufiq
IJID (International Journal on Informatics for Development) Vol. 10 No. 1 (2021): 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.2021.2265

Abstract

The success of JISKa is inseparable from the role of reviewers and authors. Unfortunately, JISKa had never been assessed or evaluated by reviewers and authors despite the fact that assessment from the reviewers and authors would be valuable feedback for JISKa’s self-evaluation. Therefore, survey-based research has recently been conducted to assess JISKa’s performance using the User Acceptance Test of OJS version 2.4.8.0. This study used a survey method to obtain an assessment and evaluation from reviewers and authors related to JISKa.The respondents in this study consist of 68 authors and 26 reviewers. The result of this study stated that 91.2% of the authors and 84.6% of reviewers are satisfied with JISKa. A percentage number of 100% of writers and reviewers wants JISKa to raise its level of Sinta accreditation. This accreditation is awarded in 2018 and will end in 2023. JISKa is now on Sinta 4.The JISKa website appearance looks good and easy to use. The dashboard on the JISKa page is user-friendly for the author. However, the current version of JISKa OJS 2.4.8.0 needs to be upgraded to OJS version 3. There are some points for the future consideration of JISKa: JISKa needs to promote itself more, upgrade the OJS version, and provide the reviewers with certificates of appreciation for future consideration.
Comparative Analysis of Text Mining Classification Algorithms for English and Indonesian Qur’an Translation Hidayat, Rahmat; Minati, Sekar
IJID (International Journal on Informatics for Development) Vol. 8 No. 1 (2019): IJID June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2019.08108

Abstract

Qur'an, As-Sunnah, and Islamic old book have become the sources for Islam followers as sources of knowledge, wisdom, and law. But in daily life, there are still many Muslims who do not understand the meaning of the sentence in the Qur'an even though they read it every day. It becomes a challenge for Science and Engineering field academicians especially Informatics to explore and represent knowledge through intelligent system computing to answer various questions based on knowledge from the Qur'an. This research is creating an enabling computational environment for text mining the Qur'an, of which purpose is to facilitate people to understand each verse in the Qur'an. The classification experiment uses Support Vector Machine (SVM), Naive Bayes, k-Nearest Neighbor (kNN), and J48 Decision Tree classifier algorithms with Al-Baqarah verses translated to English and Indonesian as the dataset which was labeled by three most fundamental aspects of Islam: 'Iman' (faith), 'Ibadah' (worship), and 'Akhlaq' (virtues). Indonesian translation was processed by using the sastrawi package in Python to do the pre-processing and StringToWord Vector in WEKA with the TF-IDF method to implement the algorithms. The classification experiments are determined to measure accuracy, and f-measure, it tested with a percentage split 66% as the data training and the rest as the data testing. The decision from an experiment that was carried out by the classification results, SVM classifier algorithms have the overall best accuracy performance for the Indonesian translation of 81.443% and the Naïve Bayes classifier has the best accuracy for the English translation, which achieved 78.35%.
Co-Authors Gunawan, Eko Hadi Muhammad Taufiq Nuruzzaman Rahmat Hidayat Wonoseto, Muhammad Galih