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Journal : Journal of Software Engineering, Information and Communication Technology

TADAKU: Application of Research Questionnaire Collection as an Effort to Increase the Quantity and Quality of Research in Indonesia Fuji Rahmannisa; Inggo Iwan Kurniawan; Muhammad Fadhli Taqdirul Jabbar; Indira Syawanodya
Journal of Software Engineering, Information and Communication Technology (SEICT) Vol 2, No 2: December 2021
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (236.665 KB) | DOI: 10.17509/seict.v2i2.40290

Abstract

Data is crucial in today's modern society. One of the most effective ways to obtain data is through online surveys using online questionnaires. However, there is a lack of online questionnaire creation applications that can motivate respondents to participate in surveys. As a result, survey creators often face difficulties in obtaining responses from respondents. The Tadaku application is designed to address this issue by providing a platform for survey creators to create questionnaires and helping them to reach targeted respondents quickly and accurately by implementing a reward system for participants who are willing to complete the questionnaires. Thus, the Tadaku application provides motivation and benefits for respondents. The questionnaire app system is developed using the waterfall method, which consists of four stages: needs analysis, system design, coding, system testing, and maintenance. The features available in the Tadaku questionnaire application include registration, creating new questionnaires, questionnaire completion, and point redemption for cash rewards.
Design and Implementation of REST API for Predicting the Recitation of the Qur'an using Machine Learning Santosa, Krisna; Rofifah, Rifdah Hansya; Riani, Alfia April; Syawanodya, Indira; Tawakal, Iqbal
Journal of Software Engineering, Information and Communication Technology (SEICT) Vol 5, No 1: June 2024
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/seict.v5i1.70600

Abstract

The Qur'an is the Muslim holy book, consisting of 30 juz and 114 surahs of varying length and number of verses. Reading the Qur'an involves special techniques to understand and read with similarity or consistency to the verse being read. In the digital era, technology enables the development of applications that support the learning and analysis of Qur'anic recitation. This research aims to design and implement a REST API to predict Qur'an recitation using a machine learning (ML) model. This API accepts voice recordings from users and provides output in the form of an assessment of the similarity of their recitation to the desired verse. Using FastAPI and pre-trained models such as Wav2Vec2, the system can translate audio into text with fairly good accuracy. Experimental results show a word error rate (WER) of 30%, which indicates the need for further improvement but is sufficient in the experimental context. The technology is useful as a self-learning tool for the Qur'an, but it does not replace the role of the teacher. Future research should focus on improving model accuracy and integrating more user-friendly features. 
Comparison Towards Different Methods of Software Debugging Tajimalela, Akwan Cakra; Suryahadi, Ramandha Putra; Alfadilla, Rizka; Syawanodya, Indira; Tawakal, Iqbal
Journal of Software Engineering, Information and Communication Technology (SEICT) Vol 5, No 2: December 2024
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/seict.v5i2.70590

Abstract

To ensure that software works as expected, debugging is essential. This article discusses several types of debugging, focusing on Visual Studio Code Debugger, print statement debugging, and static code analysis. Each method is demonstrated through a simple yet comprehensive program that determines whether a selected number is a prime number. We conclude that the Visual Studio Code Debugger offers powerful features but requires prior experience with Visual Studio Code. Print statement debugging is straightforward but can become cumbersome in more complex programs. Static code analysis, particularly with ESLint, does not directly uncover "bugs" in the traditional sense but evaluates code style, security, and good programming practices. Combining these three methods can yield optimal results in the debugging and inspection process, depending on the specific needs and context of the project.