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All Journal Jurnal Manajemen Strategi dan Aplikasi Bisnis JOURNAL OF SCIENCE AND SOCIAL RESEARCH
Firdaus, Akbar
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Social Sciences

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PENERAPAN METODE K-MEANS CLUSTERING UNTUK STOK PENJUALAN SPAREPART SEPEDA MOTOR Firdaus, Akbar; Sriani, Sriani; Darta, Ali
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 4 (2025): November 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i4.4792

Abstract

Abstract: Availability of motorcycle spare parts in CV. Solid Mandiri Cemerlang must be monitored to avoid product shortages. The problem that occurs in reporting regarding Most of the items purchased by Most of the customers is under control. Processing incoming and outgoing goods that are not processed by the system requires goods management techniques. The more complete the types of spare parts, customer needs will be met. The collection of available spare parts will be divided into several groups to get the spare parts that customers have purchased the most for each transaction. Data mining is sourced from raw database. This causes problems in databases which tend to be dynamic, complete and large. The K-means Clustering algorithm is capable and effective for finding clusters in data. This calculation will determine the number of clusters at the calculation center and the maximum iteration of data that has been entered into the system. The purpose of implementing the K-means algorithm is to find the value of the goods purchased by the majority of customers so that it makes it easier to provide spare parts. The results of the k-means calculation: C1 (high) has 9 items, C2 (low) has 1 items.Keyword: Motorcycle Parts, K-Means, ClusterAbstrak: Ketersediaan suku cadang sepeda motor di CV. Solid Mitra Cemerlang harus dimonitor untuk menghindari kekosongan barang. Masalah yang terjadi dalam pelaporan mengenai Sebagian besar barang yang dibeli oleh Sebagian besar pelanggan menjadi kendali. Mengolah barang masuk dan keluar yang tidak diproses dengan sistem membutuhkan teknik mengelola barang. Semakin lengkap jenis-jenis suku cadang, kebutuhan pelanggan akan terpenuhi. Pengumpulan suku cadang yang tersedia akan dibagi menjadi beberapa kelompok untuk mendapatkan suku cadang yang paling banyak dibeli pelanggan untuk setiap transaksi. Penambangan data bersumber dari basis data mentah. Hal ini menyebabkan masalah dalam database yang cenderung dinamis, lengkap dan besar. Algoritma K-means Clustering mampu dan efektif untuk menemukan cluster dalam data. Pada perhitungan ini akan menentukan jumlah cluster pada pusat perhitungan dan iterasi maksimum data yang telah dimasukkan kedalam sistem. Tujuan dari penerapan algoritma K-means adalah untuk menemukan nilai dari barang yang dibeli oleh Sebagian besar pelanggan sehingga memudahkan untuk menyediakan suku cadang. Hasil perhitungan k-means: C1 (tinggi) ada 9 barang, C2 (rendah) ada 1 barang.Kata kunci: Suku Cadang Sepeda Motor, K-Means, Cluster
Strategic HR framework for startups: Building sustainable organizations in the digital era Winasis, Shinta; Firdaus, Akbar; Terminanto, Agung
Jurnal Manajemen Strategi dan Aplikasi Bisnis Vol 8 No 2 (2025)
Publisher : Lembaga Pengembangan Manajemen dan Publikasi Imperium

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36407/jmsab.v8i2.1765

Abstract

Startups play a crucial role in Indonesia's economy, particularly in driving innovation and creating employment opportunities. With flexible and agile business models, startups offer significant opportunities for young entrepreneurs and the younger generation to develop their careers while contributing to economic growth, especially in the technology sector. However, startups face challenges in organizational governance, particularly in human resource management, leading to significant obstacles in employee retention policies and HR management. This research analyzes strategic challenges in startup HR management and formulates a practical solution framework. Through a systematic literature review of recent publications, the study identifies critical issues, including excessive multi-tasking workloads, unsystematic recruitment processes, limited employee development programs, and high turnover rates. The findings highlight the importance of a holistic, integrative approach that encompasses culture-based recruitment, innovative reward systems, structured mentorship programs, and flexible work environments. Implementing this strategy is expected to build solid, creative teams, laying the foundation for long-term startup sustainability.
Co-Authors Ali Darta Terminanto, Agung Winasis, Shinta