Analysis of Scooter Spare Parts Sales at Harapan Indah Scooter Using the K-Means Algorithm

: K-means clustering algorithm has been used in this study to analyze the sales performance of scooter spare parts at Harapan Indah Scooter. By using the K-means method, researchers can classify products into 3 categories according to their sales volume. The purpose of this analysis is to identify patterns in sales data and compare the characteristics of each product group. Researchers can see the output from the previous step shows three clusters: Low, Medium, and High Sales. Associating products with these categories Empowers improved tracking of sales movements and fluctuation trends in product options. The findings of this study can be useful in the field of inventory management and to develop marketing strategies to increase product sales. Companies can find out which products fall into which categories and therefore can make better decisions on how to manage stock and promotional efforts. These findings are the first step to maintain and improve sales performance and optimize Harapan Indah Scooter business

Authors

Publication Details

Journal
International Journal Software Engineering and Computer Science (IJSECS)
Published
2024-12-01
DOI
https://doi.org/10.35870/ijsecs.v4i3.3026
Primary Topic
Forecasting Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of Scooter Spare Parts Sales at Harapan Indah Scooter Using the K-Means Algorithm

Frencis Matheos Sarimole, Tracy Olivera Lingga
International Journal Software Engineering and Computer Science (IJSECS)
Forecasting Techniques and Applications
article

Analysis of Scooter Spare Parts Sales at Harapan Indah Scooter Using the K-Means Algorithm

Frencis Matheos Sarimole, Tracy Olivera Lingga
article en

Abstract

: K-means clustering algorithm has been used in this study to analyze the sales performance of scooter spare parts at Harapan Indah Scooter. By using the K-means method, researchers can classify products into 3 categories according to their sales volume. The purpose of this analysis is to identify patterns in sales data and compare the characteristics of each product group. Researchers can see the output from the previous step shows three clusters: Low, Medium, and High Sales. Associating products with these categories Empowers improved tracking of sales movements and fluctuation trends in product options. The findings of this study can be useful in the field of inventory management and to develop marketing strategies to increase product sales. Companies can find out which products fall into which categories and therefore can make better decisions on how to manage stock and promotional efforts. These findings are the first step to maintain and improve sales performance and optimize Harapan Indah Scooter business

International Journal Software Engineering and Computer Science (IJSECS)Vol. 4(3)
Openalex Percentile: Top 73%
Forecasting Techniques and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Analysis of Scooter Spare Parts Sales at Harapan Indah Scooter Using the K-Means Algorithm — Frencis Matheos Sarimole, Tracy Olivera Lingga · International Journal Software Engineering and Computer Science (IJSECS) (2024) | TGRS Research Map | TGRS