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All Journal International Journal of Management Science and Information Technology (IJMSIT) Journal Of Computer Science And Technology
Jeperson Hutahaean
Universitas Royal
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Application of the KNN Algorithm to Assess Customer Satisfaction at A2 Collection Sei Silau Timur Lutfi Anniswa Sitorus; Jeperson Hutahaean; Cecep Maulana
International Journal of Management Science and Information Technology Vol. 6 No. 1 (2026): January - June 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i1.6813

Abstract

The development of information technology and data mining in recent years has changed the way retail businesses, including small and medium-scale fashion businesses, collect, analyze, and utilize customer data to improve services and marketing strategies. In addition, through the main discussion carried out in this study, it aims to be able to analyze the factors that influence the level of customer satisfaction at Amel Fashion Prapat Janji based on the attributes of product quality, price, comfort of use, and service. In addition, this study develops and applies the K-Nearest Neighbor (K-NN) algorithm to classify the level of customer satisfaction more objectively, measurably and data-based. And in addition, for the Research Method section used in this study, a qualitative approach was chosen because the focus of this study is to explore the meaning, perception, and direct experience of business actors in the marketing and distribution process. So based on that, this study shows the results that the application of the K-Nearest Neighbor (KNN) algorithm in the customer satisfaction classification system at A2 Collection Sei Silau Timur is able to provide an effective solution in managing and analyzing customer evaluation data. This website-based system has succeeded in changing the assessment process that was previously carried out manually to be more structured, systematic, and easily accessible. Based on the system's calculations, the resulting distance values, such as 2.354, categorized as "Satisfied" and 2.325, categorized as "Dissatisfied," indicate that the proximity of attribute values significantly influences the classification results. Although the difference in distance values is relatively small, the system is still able to determine the class based on the dominance of the nearest neighbor data.
Model Hybrid Fuzzy-Weighted Product Evaluasi Kinerja Honorer Lia Umbari Putri; Rolly Yesputra; Jeperson Hutahaean
Journal of Computer Science and Technology (JOCSTEC) Vol 4 No 2 (2026): JOCSTEC - Mei
Publisher : PT. Padang Tekno Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59435/jocstec.v4i2.726

Abstract

Evaluasi kinerja pegawai honorer di instansi publik seringkali bergantung pada penilaian linguistik yang subjektif, sehingga memicu bias penilai dan keterbatasan akuntabilitas. Untuk mengatasi masalah tersebut, penelitian ini mengusulkan model hibrida Fuzzy-Weighted Product. Logika Fuzzy diterapkan untuk mentransformasikan istilah linguistik menjadi Triangular Fuzzy Numbers (TFN) dan skor tegas (crisp), sementara metode Weighted Product digunakan untuk mengagregasikan skor tersebut berdasarkan bobot multi-kriteria. Model ini dievaluasi melalui studi kasus yang melibatkan sepuluh pegawai honorer berdasarkan lima kriteria: disiplin, tanggung jawab, kualitas kerja, kerja sama, dan inisiatif. Hasil eksperimen menunjukkan bahwa model hibrida ini berhasil meminimalkan subjektivitas penilai dan menghasilkan perengkingan yang dapat direproduksi secara matematis. Analisis sensitivitas mengonfirmasi stabilitas hasil peringkat akhir, sehingga model Hibrida Fuzzy Weighted Product yang diusulkan ini sangat sesuai untuk digunakan sebagai kerangka kerja utama dalam sistem pendukung keputusan untuk penilaian kinerja di sektor publik.   Performance evaluation of honorary employees in public institutions often relies on subjective linguistic assessments, leading to evaluator bias and limited accountability. To address this, this paper proposes a Hybrid Fuzzy-Weighted Product (Fuzzy-Weighted Product) model. Fuzzy Logic is adopted to transform linguistic terms into Triangular Fuzzy Numbers (TFN) and crisp scores, while the Weighted Product method aggregates these scores based on multi-criteria weights. The model was evaluated using a case study of ten honorary employees across five criteria: discipline, responsibility, work quality, cooperation, and initiative. The experimental results demonstrate that the hybrid model successfully minimizes evaluator subjectivity and delivers mathematically reproducible rankings. A sensitivity analysis confirms the stability of the final rankings, making the proposed Hybrid Fuzzy–Weighted Product model highly suitable as a core framework for decision-support systems in public sector performance appraisal.
Co-Authors Cecep Maulana Lia Umbari Putri Lutfi Anniswa Sitorus Rolly Yesputra