Article Per Year (5 Year)
p-Index From 2021 - 2026
0.92
P-Index
This Author published in this journals
All Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JOURNAL OF APPLIED INFORMATICS AND COMPUTING Community Empowerment Informasi interaktif : jurnal informatika dan teknologi informasi
Febriani, Siska
Unknown Affiliation
Arts Humanities Computer Science & IT Education Engineering Public Health Social Sciences

Published : 5 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 5 Documents
Search

 1 
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.
Analisis perancangan sistem penerimaan santri berprestasi menggunakan kombinasi metode AHP-WP Febriani, Siska; Bahri, Saiful; Dewantara, Rizki
Informasi Interaktif : Jurnal Informatika dan Teknologi Informasi Vol 9 No 1 (2024): JII Volume 9, Number 1, Januari 2024
Publisher : Program Studi Informatika Fakultas Teknik Universitas Janabadra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37159/jii.v9i1.58

Abstract

Sekolah merupakan komunitas belajar yang mendukung siswa dan lulusan untuk mengembangkan keterampilan, pengetahuan, dan sikap yang diperlukan untuk mencapai tujuan pendidikan. Bangsa ini mempunyai tujuan yang sangat penting bagi pesantren.Santri yang berhasil mencapai prestasi tinggi sesuai dengan kriteria yang ditentukan adalah setelah tahunnya pemilihan santri berprestasi program beasantri. Beberapa kriteria yang dijadikan kriteria pemilihan rumah prefabrikasi seperti, Menghafal jus 1-3, hafalan jus 30, dan Membaca Kitab Gundul. Metode dalam entri data menggunakan hasil nilai tes dan untuk menguji keakuratan pengukuran menggunakan metode kombinasi AHP-WP. Tujuan dari penelitian ini adalah untuk meningkatkan sistem pengambilan keputusan di Pondok Pesantren Salafiyah sehingga lebih mudah dalam mengidentifikasi bangunan prefabrikasi. Hasil dari penelitian ini adalah sebuah sistem pendukung keputusan bagi pemilik properti dengan beberapa pilihan menu yang memudahkan pekerjaannya dan dapat mengurutkan data sesuai kriteria dalam proses penilaian properti. Pada kasus Pondok Pesantren Salafiyah, Metode AHP-WP mencapai persentase sebesar 92,3%.
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.
Sentiment Analysis of Public Opinion on Online Gambling Through Social Media Using Convolutional Neural Network D. Diffran Nur Cahyo; Handayani, Rizky; Budhi Lestari, Verra; Febriani, Siska
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 9 No. 1 (2025): Issues July 2025
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v9i1.15024

Abstract

Online gambling has become a serious social issue due to its easy accessibility through digital platforms, requiring effective policy interventions. This study analyzes public sentiment toward online gambling by examining 10,000 YouTube comments using a Convolutional Neural Network (CNN) algorithm. Data were collected via the YouTube API and underwent preprocessing steps including text cleaning, normalization, tokenization, stopword removal, and stemming. Sentiment labeling was performed using a lexicon-based approach, with data transformed through Word2Vec embedding and balanced using oversampling techniques. The CNN model, consisting of embedding, convolutional, pooling, and dense layers, achieved an impressive accuracy of 99.10%, outperforming traditional machine learning methods. Sentiment was categorized into positive, neutral, and negative, with the majority of comments reflecting positive sentiment, indicating public support for efforts to combat online gambling. WordCloud visualizations highlighted dominant themes and frequently used terms. This study demonstrates the effectiveness of CNN in analyzing unstructured social media data and offers valuable insights for policymakers. Future research should explore hybrid architectures such as CNN-LSTM and expand datasets by including other platforms like Twitter, Instagram, and TikTok to enhance generalization and address broader social challenges.
Management capacity building and digital market access expansion strategy for BUMDes clustering optimization Rusmiyatun, Rusmiyatun; Arini, Anes; Febriani, Siska; Hafizhuddin, Abid; Tri W, Talita Erina
Community Empowerment Vol 10 No 11 (2025)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ce.14912

Abstract

BUMDes Dadirejo possesses significant economic potential through its four business units, yet its development is hindered by limited marketing access and low human resource capacity in financial management. This community service project aims to elevate the BUMDes clustering status from the "developing" (berkembang) category to "independent" (mandiri) through workshops and continuous mentoring. The interventions include digital marketing management training (Instagram and TikTok), e-catalog registration for market expansion, and the standardization of financial reports, covering balance sheets, income statements, statements of changes in equity, and cash flow statements. Results show that the BUMDes management achieved an 85% mastery level in financial reporting. Furthermore, the provision of marketing equipment grants successfully encouraged the formation of new business units and strengthened the sales infrastructure. This strategy proved effective in enhancing accountability and market reach, serving as a key step toward achieving the criteria for an Independent BUMDes.
Co-Authors Arini, Anes Budhi Lestari, Verra D. Diffran Nur Cahyo Dewantara, Rizki Eka Yulia Sari Hafizhuddin, Abid Handayani, Rizky Rusmiyatun Rusmiyatun Saiful Bahri Siswanto, Irwan Tri W, Talita Erina Wati, Vera YULI WIJAYANTI