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All Journal Teknika Jurnal Ilmiah Universitas Batanghari Jambi Seminar Nasional Teknologi Informasi Komunikasi dan Industri Edukasi Islami: Jurnal Pendidikan Islam INTECOMS: Journal of Information Technology and Computer Science Matrik : Jurnal Manajemen dan Teknik Industri Produksi Zonasi: Jurnal Sistem Informasi Jurnal Surya Teknika Indonesian Journal of Industrial Engineering & Management Industrika : Jurnal Ilmiah Teknik Industri Jurnal Testing dan Implementasi Sistem Informasi
Lubis, Fitriani Surayya
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Penerapan Metode Human Resource Scorecard (HRSC) dan Analytical Hierarchy Process (AHP) dalam Penilaian Kinerja Karyawan pada PT. Laundry Kotak Indonesia Kanwil Pekanbaru Pangestu, Bima Okta; Kusumanto, Ismu; Lubis, Fitriani Surayya; Yola, Melfa
Industrika : Jurnal Ilmiah Teknik Industri Vol. 10 No. 2 (2026): Industrika: Jurnal Ilmiah Teknik Industri
Publisher : Fakultas Teknik Universitas Tulang Bawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37090/ndvxsm13

Abstract

The rapid population growth in urban areas has increased the demand for Laundry services. PT. Laundry Kotak Indonesia, Pekanbaru Branch, plays a key role in managing and developing its workforce to ensure efficient operations and quality customer service. However, issues such as tardiness, safety negligence, lack of skills, and high employee turnover have negatively affected employee performance and overall productivity. Despite these challenges, no formal performance measurement system for employees has been implemented. This study aims to evaluate employee performance using the Human Resource Scorecard (HRSC) and Analytical Hierarchy Process (AHP) methods. The objective is to improve employee performance to support the company’s vision and competitiveness. The findings identify 14 strategic performance indicators, with the Financial perspective receiving the highest weight (0.437), providing a basis for more focused HR strategies, policy development, training resource allocation, and continuous performance evaluation. Keywords:, AHP, HRSC, Employee Performance Measurement, Performance
THE INFLUENCE OF MARKETING MIX ON CONSUMER PURCHASE PATTERNS USING THE APRIORI DATA MINING ALGORITHM Umam, Muhammad Isnaini Hadiyul; Kurniawan, Muhammad Ilham; Lubis, Fitriani Surayya; Rizki, Muhammad
Jurnal Testing dan Implementasi Sistem Informasi Vol. 3 No. 2 (2025): Jurnal Testing dan Implementasi Sistem Informasi
Publisher : Lembaga Riset dan Inovasi Almatani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55583/jtisi.v3i2.2357

Abstract

The increasing volume of sales transaction data in retail and marketplace environments presents an opportunity to extract valuable insights for decision-making; however, such data are often underutilized. This study aims to analyze consumer purchasing patterns using the Apriori algorithm and to examine the influence of the marketing mix (product, price, place, and promotion) on purchasing decisions that shape these patterns. This research employs a quantitative approach by integrating data mining and statistical analysis. Transaction data are processed using the Apriori algorithm through RapidMiner to generate association rules and identify frequent itemsets. In addition, questionnaire data are analyzed using multiple linear regression to evaluate the effect of marketing mix variables on purchasing decisions. The results show that product, price, place, and promotion simultaneously have a significant effect on purchasing decisions. Partially, product (t = 2.622; p = 0.011), price (t = 4.738; p = 0.000), and place/distribution (t = 2.239; p = 0.029) have a significant positive effect, while promotion does not have a significant effect (t = 1.486; p = 0.143). The Apriori analysis reveals dominant purchasing patterns that can be translated into practical marketing strategies, such as product bundling and layout optimization. This study contributes by integrating association rule mining with marketing mix analysis to provide both predictive patterns and explanatory insights. However, the findings should be interpreted with caution due to data limitations, including a relatively small sample size (n = 148) and a short observation period of three months during peak season, which may limit generalizability. Despite these constraints, the results offer practical implications for optimizing marketing strategies and contribute theoretically to interdisciplinary research in data mining and consumer behavior.
Co-Authors Aditama, Dhimas Al-As'ad, Faiz Al-Ghozy, Athaullah Ahmad Amanda, Suci anwardi, anwardi Burrahman, Habi Dharma, Satrio Arya Dwi Arini, Jean Retno Frenita Zurids, Adilla Gusti Fara Hitari, Belia Hadiyul Umam, Isnaini Hamdy, Muhammad Ihsan Handika, Puri Tri hanifah hanifah Harpito, Harpito Hartati, Misra Hidayat, Ferdi Gusman Ismu Kusumanto Kurniawan, Muhammad Ilham Lisnasari, Srie Faizah Mayuta, Fadhila Putra Mayuta, Fadhila Putri Melfa Yola, Melfa Muhammad Muhammad Nur Muhammad Rizki Muhammad Rizki N. Nazaruddin Nazaruddin Nofirza Nofirza Nofirza Pangestu, Bima Okta Rahmadini, Reny Rifki Alfarizi Rika Taslim Saputri, Anggi Lisa Sekar, Intan Ayu Sri Wahyuni, Annisa Suardi, Syafarudin Suherman, Suherman Syafnan Syafnan Syalsabila, Nadya Tengku Nurainun Umam, Muhammad Isnaini Hadiyul Vera Devani Wahab, Mohammad Ikbar Bin Abdul Wilda, Yulia Wulandari, Ayuni