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All Journal Semesta Teknika Jurnal Pengabdian Masyarakat IPTEKS DedikasiMU: Journal of Community Service Emerging Information Science and Technology Prosiding Seminar Nasional Program Pengabdian Masyarakat Prosiding University Research Colloquium
Haris Setyawan
Universitas Muhammadiyah Yogyakarta
Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Social Sciences

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Web-Based Data Information System for Students and Teachers at Al-Qur’an Education Parks in Kasihan, Bantul Teuku Syauqi Maulana; Haris Setyawan; Asroni Asroni
Emerging Information Science and Technology Vol 2, No 1: May 2021
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v2i1.16870

Abstract

Al-Qur’an Kindergarten (TKA) and Al-Qur’an Education Park (TPA) are non-formal religious education institutions emphasizing studying Islamic values. The development of society necessitates institutions that hold TKA/TPA-related information promptly and correctly. Currently, technology is required to aid an institution in maintaining data and providing TKA/TPA-related information. The data information system aims to provide data for the TKA/TPA coordination agency and ensure the implementation of the administrative order to assure the operational and development sustainability of the IT-based TKA/TPA operating regions. This research intends to develop a web-based information system that can handle the data of students and teachers to reduce the number of errors due to manual data management. A web-based application system for student and teacher data information in TPA in Kasihan was developed utilizing the CodeIgniter framework, the Hypertext Preprocessor (PHP) programming language, the MySQL database, the SDLC method, and the Prototype model. Due to its superiority, the website was selected as the application’s foundation since it is lightweight and could be accessed rapidly using a web browser and an internet or intranet connection to the server. This study has produced a web-based application constructed successfully and could be utilized as a data information system for TPA students and teachers in Bantul.
Sentiment Analysis of Public Responses on Indonesia Government Using Naïve Bayes and Support Vector Machine Haris Setyawan; Laila Ma’rifatul Azizah; Alvira Yusnia Pradani
Emerging Information Science and Technology Vol 4, No 1 (2023): May
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v4i1.18681

Abstract

Many people are interested in knowing how the public views President Joko Widodo's administration. Text Mining analysis can be one way to collect and analyze text data about Joko Widodo's administration and extract relevant information from the data. Data was obtained by collecting tweet data about Joko Widodo's government in 2022 on Twitter using Netlyitic. Then the Text Mining analysis of Joko Widodo's government was carried out using the Navie Bayes (NVB) classification and Support Vector Machine (SVM). This classification can be used to predict sentiment or public views of the government based on the tweets collected.  Based on a case study of the classification results of President Joko Widodo using Naive Bayesian classification, we obtained a precision value of 79%, a recall value of 91% and a precision value of 82%. And by using SVM, we get 85% precision, 95% recall, and 83% precision. Due to the high accuracy, recall, and precision, it can be said that SVM classification is more accurate than NVB.
Co-Authors Adiatsa Putra Santika Alvira Yusnia Pradani Arditya Nur Rokhim Asroni Asroni Asroni Asroni Bhaskara Satrya Priwandhana Deka Desilawati Elvan Diano Fahmi Azhar Iskandar Fidelia Farahi Irya Wisnubhadra Kurnianti, Apriliya Laila Ma’rifatul Azizah Muhammad Fadlun Subarkah Pascal Pahlevi Pasha Radityo Anindito Arighi Reza Giga Isnanda Risang Prakosa Teuku Syauqi Maulana