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All Journal Prosiding Seminar Nasional Sains dan Teknologi Terapan JENIUS (Jurnal Ilmiah Manajemen Sumber Daya Manusia) Smatika Jurnal : STIKI Informatika Jurnal
Kartika, Intan Dina
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Computer Science & IT Economics, Econometrics & Finance

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Excellent Service with the 3A Concept (Attitude, Attention, Action) at LPPP State University of Malang Kartika, Intan Dina; Hardika; Baskara, Dwi Soca
Jurnal Ilmiah Sumber Daya Manusia Vol 7 No 3 (2024): JENIUS (Jurnal Ilmiah Sumber Daya Manusia)
Publisher : Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/JJSDM.v7i3.41921

Abstract

This research aims to obtain information about excellent service with the concept of Attitude, Attention, and Action carried out at the Malang State University Education and Learning Development Institute (LPPP UM) office. The research method used is descriptive qualitative. Data collection was carried out through interviews with educational staff, observation, and documentation. The data obtained were analyzed using the Miles & Huberman model. The results showed that excellent service carried out by academic staff at LPPP UM has implemented the 3A concept well. Excellent service provided with the idea of Attitude has three main things, namely a polite and physically harmonious appearance, serving with a positive and logical attitude, and serving with an attitude of respect. Excellent service with the concept of Attention also has three main things, understanding sincerely, respecting behavior, and devoting full attention to guests. Excellent service with the Action concept has five main things, including always noting what guests want, recording guest needs, confirming and summarizing guest needs, trying to realize guest wishes as expected, and thanking guests.
Pengembangan Financial Documentation System Berbasis Artificial Intelligence Untuk Meningkatkan Self Service Dan Layanan Prima Bidang Keuangan Kartika, Intan Dina; Baskara, Dwi Soca
Prosiding Seminar Nasional Sains dan Teknologi Terapan 2024: Menjembatani Energi Berkelanjutan dan Ekonomi Hijau melalui Transformasi Riset dan Teknologi T
Publisher : Institut Teknologi Adhi Tama Surabaya

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Abstract

Penelitian ini bertujuan untuk mengembangkan Financial Documentation System Berbasis Artificial Intelligence untuk meningkatkan efisiensi dan akurasi dalam pengelolaan dokumen keuangan. Sistem yang diusulkan dirancang untuk mempercepat proses pelaporan, meminimalkan kesalahan manusia, dan meningkatkan layanan pelanggan di sektor keuangan. Sistem ini akan mengotomatisasi pembuatan dan pengelolaan dokumen keuangan, mengurangi beban kerja manual, dan memberikan layanan yang lebih cepat dan responsif kepada pengguna. Penelitian ini menggunakan pendekatan prototipe, yang melibatkan tahapan komunikasi, perencanaan cepat, desain cepat, konstruksi prototipe, penerapan, dan umpan balik. Hasil yang diharapkan dari sistem ini termasuk peningkatan efisiensi operasional dan kualitas layanan, memungkinkan pengguna untuk mengakses layanan mandiri dengan cepat dan akurat, dan meningkatkan kepuasan pelanggan melalui pemberian layanan yang unggul dan responsif.
Design and Development of a Multi-Agent Artificial Intelligence-Based Financial Planner for Institutional Financial Management Optimization Kartika, Intan Dina; Baskara, Dwi Soca; Hardika
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 01 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i01.2167

Abstract

Institutional financial management often faces optimization challenges due to limited understanding of influencing factors, difficulties in data integration, and the lack of human expertise. These constraints hinder the identification of opportunities, risk management, and sustainability. An adaptive and automated financial planning system is required. This study proposes the design of an Artificial Intelligence (AI)-based system for automated financial planning aligned with institutional standards. The system addresses these challenges by integrating financial needs analysis, standardized cost references, and automated budget summary preparation. Using a prototyping approach, the system employs AI agents to conduct in-depth analysis and produce comprehensive budgets. The proposed system leverages RAGflow, an open-source Retrieval-Augmented Generation (RAG) engine that uses deep document understanding to provide truthful question-answering from complex data.
Co-Authors Dwi Soca Baskara Hardika