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All Journal Jurnal Sains dan Teknologi Elkom: Jurnal Elektronika dan Komputer JOURNAL OF APPLIED INFORMATICS AND COMPUTING JKIE (Journal Knowledge Industrial Engineering) Jurnal Informasi dan Komputer Jurnal Cendikia TEKNOKOM : Jurnal Teknologi dan Rekayasa Sistem Komputer JATI (Jurnal Mahasiswa Teknik Informatika) Madani : Indonesian Journal of Civil Society GANESHA: Jurnal Pengabdian Masyarakat Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat SUBSERVE: Community Service and Empowerment Journal Jurnal Intelek Insan Cendikia Prosiding SeNTIK STI&K Jurnal Pendidikan Teknologi Informasi (J-Diteksi)
Wati, Vera
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Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

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Computational Analysis of IT Governance Audit Using COBIT 4.1 Framework: A Customer Perspective Wati, Vera; Febriani, Siska; Sari, Eka Yulia
Journal of Applied Informatics and Computing Vol. 8 No. 1 (2024): July 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v8i1.8135

Abstract

A company's performance can be measured by the number and satisfaction of customers, which helps in maintaining customer relationships. Indicators such as customer satisfaction, perception of service, and loyalty can be derived from the Customer Perspective of the Balance Scorecard (BSC). Conducting an IT governance audit is essential to understand how customers perceive a service. The use of the COBIT 4.1 Framework for IT governance audits is recognized for its detailed process, both for business and governance purposes, to avoid vulnerabilities and threats, thereby increasing customer satisfaction. Effective IT governance plays a crucial role in enhancing customer satisfaction and achieving organizational success. This research aims to analyze IT governance audits from a customer perspective using the COBIT 4.1 framework, with a focus on aligning IT strategy with business goals to meet customer expectations. The research method involves key processes in PO8 (Manage Quality) and PO10 (Manage Project) to determine quality standards and influential budgets. Integration with computational techniques for data analysis and IT audit algorithms is carried out to build strong IT governance practices. The computational audit results show maturity levels of 2.59 for PO8 and 3.02 for PO10, indicating areas needing improvement in product quality management and project execution to better meet customer needs. These findings underscore the importance of integrating computational insights to optimize IT governance frameworks and improve organizational performance, especially in customer retention through enhanced project quality management.
Twitter Sentiment Analysis on Digital Payment in Indonesia Using Artificial Neural Network Febriani, Siska; wati, Vera; Wijayanti, Yuli; Siswanto, Irwan
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.8988

Abstract

In the rapid development of technology, the need for big data processing is increasingly important, especially in the context of digital transactions such as e- wallets in Indonesia. On the other hand, sentiment analysis of digital payment platforms via Twitter requires fast and accurate data processing, but often faces challenges in managing big data and optimal classification quality. This study uses the Term TF-IDF method for text preprocessing and Artificial Neural Network (ANN) for sentiment classification. The preprocessing process includes case folding, removing numbers and punctuation, tokenization, filtering, and stemming. For classification, ANN is used which is optimized with the Backpropagation and K-fold Cross Validation algorithms to improve the accuracy of the model in grouping positive and negative sentiments from tweets about digital payment platforms. Through this approach, the study produces a sentiment classification model in analyzing big data. The results in this study are Gopay gets a positive value and gets the first value in sentiment assessment with an accuracy rate of 72% using ANN. Of the 5 digital payments that received a negative value and ranked last, namely Link Aja with an achievement rate of 43%. Based on these results, it shows that this approach contributes to identifying consumer sentiment towards e-wallet platforms, which is useful for developing digital marketing strategies. The contribution given is in improving sentiment analysis of digital payment platforms by utilizing Big Data processing technology and machine learning, so that it can be used to improve services and marketing strategies based on user data.
Co-Authors Achmad Nugrahantoro Anggraini, Mari Arif Maulana Yusuf Azhari Pohan, Ahmad Barori, Ahda Danarti Karsono david Eka Yulia Sari Erni Widarti Febriani, Siska herpratiwi Himawan, Salamet Nur Husnul Khatimah Irawan, Joko Irwan Budiman Iswanto, Muhammad Edi Khofid, Adi Nur lutfi bangun lestari Masfuha, Ilmi Moh. Erkamim Moh. Yani Mukti Prabowo, Gilang Mustamiin, Muhamad Nayla Alviani , Permatasary Nirhahim, Rahma Tia Nursya , Fathin Nurwahidin, Muhammad Pamungkas, Muh. Rizal F. Pamungkas, Muhammad Rizal Fernandita Permana, Mohammad Rizky Pratama, Ifo Wahyu Radhwa, Gusti Ayu Azzah Ramadhani, Muhammad Reza Rendi Rendi, Rendi Rundi, Allesandro U.B. Rundi, Allesandro Umbu Balla Sapto Priyadi Seftiani, Tia Setyanti, Putri Widanti Setyawati, Nisrina Yulia Siswanto, Irwan Sohiburoyyan, Robieth Suhaimi Wartono Wartono Wilda, Siti YULI WIJAYANTI