Membangun Taxonomy Riset Big Data Analytics dan Business Intelligence: Systematic Literature Review dalam Konteks Manajemen Informatika

Dhimas Tribuana; Andi Dewi Haryanti Agustan; Hidayat; Endang Halimah; Koas Dianah; Isiswanty

doi:10.64476/jtbc.v1i2.12

Penulis

Dhimas Tribuana Akademi Sekretari Manajemen Indonesia Publik, Makassar, Indonesia.
Andi Dewi Haryanti Agustan Akademi Sekretari Manajemen Indonesia Publik, Makassar, Indonesia.
Hidayat Akademi Sekretari Manajemen Indonesia Publik, Makassar, Indonesia.
Endang Halimah Akademi Sekretari Manajemen Indonesia Publik, Makassar, Indonesia.
Koas Dianah Akademi Sekretari Manajemen Indonesia Publik, Makassar, Indonesia.
Isiswanty Akademi Sekretari Manajemen Indonesia Publik, Makassar, Indonesia.

DOI:

https://doi.org/10.64476/jtbc.v1i2.12

Kata Kunci:

Business Intelligence, Big Data Analytics, Data Governance, Real-Time Processing, Artificial Intelligence, Generative AI, Taxonomy

Abstrak

Transformasi digital telah mendorong peran Business Intelligence (BI) berkembang dari sekadar sistem pelaporan menjadi platform strategis berbasis data. Penelitian ini bertujuan untuk memetakan state of the art BI melalui pendekatan Systematic Literature Review (SLR) dengan kerangka PRISMA 2020. Sebanyak 50 artikel ilmiah dari tahun 2010-2025 dikaji secara mendalam, dengan sumber dari basis data akademik terbuka dan standar (Scopus, Web of Science, Google Scholar, Semantic Scholar, dan DOAJ). Analisis menghasilkan sebuah taxonomy yang membagi literatur ke dalam lima domain utama: BI Foundations, Big Data Analytics, Data Governance & Quality, Real-Time & Stream Processing, dan BI-AI Integration. Hasil penelitian menunjukkan bahwa perkembangan BI mengikuti pola evolusi bertahap, mulai dari penguatan fondasi konseptual, pengembangan kapabilitas analitik, penguatan tata kelola data, akselerasi pemrosesan real-time, hingga integrasi dengan Artificial Intelligence (AI) dan Generative AI (GenAI). Studi ini memiliki implikasi teoretis berupa kontribusi terhadap kerangka konseptual riset BI, implikasi praktis berupa panduan strategi adopsi teknologi BI-AI di organisasi, serta implikasi kebijakan berupa kebutuhan regulasi adaptif dalam tata kelola data dan etika AI. Keterbatasan penelitian ini mencakup keterbatasan periode literatur dan dominasi artikel akademik. Penelitian mendatang disarankan mengintegrasikan grey literature dan studi kasus empiris untuk memperluas relevansi praktis.

Unduhan

Data unduhan belum tersedia.

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