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Sumarsono
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Jurnal Kajian Ilmiah Jl. Perjuangan No.81, Marga Mulya, Kec. Bekasi Utara, Kota Bks, Jawa Barat 17143
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Jurnal Kajian Ilmiah
Published by Universitas Bhayangkara Jakarta Raya
ISSN : 14109794     EISSN : 2597792X     DOI : https://doi.org/10.31599/jki
Core Subject : Economy, Humanities, Science, Education, Social,
Humanities Computer Science & IT Economics, Econometrics & Finance Education Social Sciences
Jurnal Kajian Ilmiah mempublikasikan artikel dengan Fokus dan Ruang Lingkup pada bidang ilmu yang telah dikaji secara empiris dan teori. Adapun Fokus dan Ruang Lingkup penelitian pada: 1. Ilmu Komputer 2. Ilmu Sosial 3. Ilmu Manajemen 4. Ilmu Hukum 5. Ilmu Komunikasi dan Humaniora 6. Ilmu Kimia 7. Ilmu Alam Beserta ilmu lain yang berhubungan dan dapat dipertanggungjawabkan.
Arjuna Subject : Umum - Umum
Articles 353 Documents
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Systematic Literature Review: Teknik Visualisasi Data Untuk Komunikasi Informasi Yang Efektif Di Berbagai Bidang Erlangga, Satrio Adhiyatama; Assifaa, Rr Nur; Tundjungsari, Vitri
Jurnal Kajian Ilmiah Vol. 26 No. 1 (2026): Januari 2026
Publisher : Lembaga Penelitian, Pengabdian Kepada Masyarakat dan Publikasi (LPPMP)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/z0az9n16

Abstract

Data visualization (DV) has emerged as a vital mechanism for transforming complex data into comprehensible visual narratives. It has become an indispensable tool for effective information communication across various disciplines, including science, education, journalism, business, `healthcare, and public policy. This paper presents a Systematic Literature Review (SLR) analyzing 24 peer-reviewed publications sourced from Google Scholar (2015–2025). The synthesis indicates that well-designed visualizations, ranging from traditional charts to sophisticated interactive dashboards and narrative displays, significantly enhance user understanding, information retention, and interpretive accuracy. Nonetheless, challenges remain concerning cognitive overload, accessibility issues, and the lack of standardized measures for visualization literacy. The review introduces an integrative framework that categorizes visualization methods, tools, and contextual applications, providing insights and recommendations for future research aimed at advancing inclusivity, interpretability, and communicative efficacy across a variety of disciplines.
Dampak Digitalisasi Sistem Manajemen Pabrik Garmen Skala Menengah Terhadap Kinerja Keuangan: Evaluasi Akurasi Pembukuan Dan Ketepatan RAB (Rencana Anggaran Belanja) Muflih, Rizky; Julio Arky Aquino Reyaan; Vitri Tundjungsari; Mulyanto, Erwan
Jurnal Kajian Ilmiah Vol. 26 No. 1 (2026): Januari 2026
Publisher : Lembaga Penelitian, Pengabdian Kepada Masyarakat dan Publikasi (LPPMP)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/ckyfte69

Abstract

Medium-scale garment factories often rely on paper records that are prone to errors, slow processes, and hinder accurate project cost tracking. This affects the accuracy of financial record-keeping and the precision of the Bill of Quantities (BOQ). This study assesses the impact of digitalisation through an integrated application in the garment industry on these key metrics. Using a pre-and-post approach on a single case (action research), the study examines a factory transitioning from a manual to a digital system. The intervention includes: linking attendance and payroll with projects; tracking monthly and project-specific expenses; managing stock (in/out) with automatic cost recording; calculating BOQ per project; comparing BOQ with actuals based on proportional overhead allocation; and calculating profit per project. The main indicators include: (i) financial record accuracy—ensuring consistency across modules (Attendance–Payroll–Expenses–Stock), accurate material cost recording, and easy export for summaries; (ii) BOQ accuracy—the difference between planned and actual costs in categories such as Materials, Labour, Overheads, and total project costs. Data from application logs and reports show that after implementation, errors and duplicate payments decreased; labour cost transparency increased; stock discrepancies and material cost variances reduced due to linking outgoing transactions with project costs; and the gap between BOQ and actuals narrowed. The digital system integrating BOQ, Production, Stock, Expenses, Attendance/Payroll, and Profit improves data quality and cost management, thereby enhancing the accuracy of financial records and BOQ in medium-scale garment factories. These findings support the development of standardised processes and data-driven decision-making for cost control.
Pengolahan Data Menggunakan Algoritma Untuk Sistem Pendukung Keputusan Karyawan Terbaik Bawiling, Hendry; Saputra, Indra; Nasir, Alfian; Tundjungsari, Vitri
Jurnal Kajian Ilmiah Vol. 26 No. 1 (2026): Januari 2026
Publisher : Lembaga Penelitian, Pengabdian Kepada Masyarakat dan Publikasi (LPPMP)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/pesfvt11

Abstract

Identifying high-performing employees is a critical component of human resource management, as it directly influences organizational productivity, work climate, service quality, and strategic goal achievement. However, conventional employee performance assessments often rely on subjective managerial judgment, making them vulnerable to personal bias and inconsistencies that can lead to dissatisfaction, decreased morale, and internal conflict. To address these challenges, Decision Support Systems (DSS) that employ data-processing algorithms have been increasingly adopted to enhance objectivity and accuracy in employee evaluation. This study conducts a Systematic Literature Review (SLR) of 25 scholarly publications published between 2017 and 2025 and indexed in nationally and internationally recognized databases. The analysis focuses on the types of algorithms applied, system development methodologies, and their relevance to optimizing the identification of top-performing employees. The findings indicate that multi-criteria decision-making methods, particularly the Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW), are the most frequently used algorithms, followed by TOPSIS, PROMETHEE, MABAC, ELECTRE, Weighted Product, SMART, and hybrid approaches. In terms of system development, several studies did not explicitly specify their methodology, while others adopted structured approaches such as the System Development Life Cycle (SDLC) and Waterfall models. This review highlights methodological trends, identifies research gaps, and proposes potential directions for future studies on algorithm-based DSS applications in employee performance evaluation

Page 36 of 36 | Total Record : 353

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