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All Journal Takuana: Jurnal Pendidikan, Sains, dan Humaniora Jurnal Ilmiah Informatika dan Ilmu Komputer Jurnal Ilmu Komputer dan Informatika
Mahendra Dewantoro
Universitas Teknokrat Indonesia
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Mathematics Social Sciences

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Peran Big Data dalam Inovasi Bisnis Digital: Pendekatan Tinjauan Literatur Sistematis Muhammad Fadli; Mugi Prasetio; Ival Sanjaya; Muhammad Surono; Mahendra Dewantoro; Ryan Randy Suryono
Jurnal Ilmiah Informatika dan Ilmu Komputer (JIMA-ILKOM) Vol. 4 No. 1 (2025): Volume 4 Nomor 1 March 2025
Publisher : PT. SNN MEDIA TECH PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jima-ilkom.v4i1.48

Abstract

Penelitian ini meninjau bagaimana Big Data berperan dalam inovasi bisnis digital, terutama dalam membantu pengambilan keputusan strategis, memperbaiki efisiensi operasional, serta menciptakan Produk dan layanan digital yang benar-benar pas dengan kebutuhan pengguna. Dengan menggunakan pendekatan tinjauan literatur sistematis, penelitian ini mengidentifikasi manfaat signifikan Big Data, termasuk kemampuannya untuk menyediakan analisis mendalam, memprediksi tren pasar, dan personalisasi layanan pelanggan. Namun, penelitian ini juga mengungkap berbagai tantangan dan kendala dalam implementasi Big Data, seperti keterbatasan infrastruktur teknologi, kualitas data yang rendah, serta isu privasi dan keamanan data. Hasil penelitian menunjukkan bahwa pemanfaatan Big Data yang optimal dapat meningkatkan daya saing bisnis digital, tetapi membutuhkan dukungan infrastruktur yang memadai dan kepatuhan terhadap regulasi yang berlaku. Studi ini berkontribusi pada pengembangan pemahaman tentang bagaimana Big Data dapat diintegrasikan ke dalam strategi inovasi bisnis digital untuk mendorong pertumbuhan dan keberlanjutan bisnis di era digital.
Analisis Komparatif Teknik Quantization (INT4 vs INT8 vs FP16) terhadap Kualitas Output Large Language Model Berbasis Instruksi Ridwan Mahenra; Mahendra Dewantoro
Jurnal Ilmu Komputer dan Informatika | E-ISSN : 3063-9026 Vol. 3 No. 1 (2026): Juli - September
Publisher : GLOBAL SCIENTS PUBLISHER

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Abstract

Quantization is a model compression technique that reduces the numerical precision of Large Language Model (LLM) weights to lower memory requirements and accelerate inference. This study presents a comparative analysis of three widely used quantization schemes—INT4, INT8, and FP16—using the Mistral-7B-Instruct-v0.2 model as the subject of study. Evaluation was conducted across five output quality dimensions: BLEU score, ROUGE-L score, perplexity, BERTScore, and average inference latency. Testing utilized 200 instruction prompts covering four task categories: text summarization, factual question answering, code generation, and logical reasoning. The analysis results indicate that INT8 offers the best balance between computational efficiency and output quality, showing an average performance degradation of 2.3% compared to FP16 while achieving a 48% reduction in memory requirements. INT4 exhibited a more significant degradation of 7.8% in logical reasoning tasks, despite successfully reducing memory usage by 74%. These findings provide practical guidance for researchers and practitioners in selecting a quantization scheme suited to available computational resources.
Perancangan Sistem Inventarisasi Aset Terpadu Berbasis Web di Lingkungan Perguruan Tinggi Fakihah Farhah Faridaashri; Mahendra Dewantoro; Damayanti Damayanti
Takuana: Jurnal Pendidikan, Sains, dan Humaniora Vol. 4 No. 4 (2026): Takuana (January-March)
Publisher : MAN 4 Kota Pekanbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56113/takuana.v4i4.379

Abstract

Asset management in higher education institutions is essential to ensure efficiency, transparency, and accountability in the use of resources. However, many institutions still rely on manual or semi-digital systems, leading to data duplication, information inconsistency, and difficulties in reporting. This study aims to develop an Integrated Web-Based Asset Inventory System to address these issues. The research methodology follows a Research and Development (R&D) approach, combining Prototype and Waterfall methods. The system is designed through stages including needs analysis, UML design, implementation using technologies such as PHP/CodeIgniter, MySQL, and Bootstrap, followed by functional and usability testing. Key features of the system include asset data input and updating, categorization by type and location, periodic notifications, automated reporting, role-based access control, and activity logs. The results show that the system provides an accurate, real-time, and integrated solution for asset management. With the appropriate use of information technology, this system is expected to improve operational efficiency and serve as a reference for other educational institutions in implementing digital-based asset management.
Co-Authors Damayanti, Damayanti Fadli, Muhammad Fakihah Farhah Faridaashri Ival Sanjaya Mugi Prasetio Muhammad Surono Ridwan Mahenra Ryan Randy Suryono