scholarly journals ANALISIS SEGMENTASI PELANGGAN MENGGUNAKAN KOMBINASI RFM MODEL DAN TEKNIK CLUSTERING

2018 ◽  
Vol 2 (1) ◽  
pp. 23-32 ◽  
Author(s):  
Beta Estri Adiana ◽  
Indah Soesanti ◽  
Adhistya Erna Permanasari
Keyword(s):  
Small And Medium Enterprises ◽  
Cluster Formation ◽  
Optimal Number ◽  
Customer Segmentation ◽  
Marketing Strategies ◽  
Monetary Analysis ◽  
Data Mining Approach ◽  
Rfm Model ◽  
Customer Services ◽  
Medium Enterprises

Intense competition in the business field motivates a small and medium enterprises (SMEs) to manage customer services to the maximal. Improve of customer royalty by grouping cunstomers into some of groups and determining appropriate and effective marketing strategies for each group. Customer segmentation can be performed by data mining approach with clustering method. The main purpose of this paper is customer segmentation and measure their loyalty to a SME’s product. Using CRISP-DM method which consist of six phases, namely business understanding, data understanding, data preparatuin, modeling, evaluation and deployment. The K-Means algorithm is used for cluster formation and RapidMiner as a tool used to evaluate the result of clusters. Cluster formation is based on RFM (recency, frequency, monetary) analysis. Davies Bouldin Index (DBI) is used to find the optimal number of clusters (k). The customers are divided into 3 clusters, total of customer in first cluster is 30 customers who entered in typical customer category, the second cluster there are 8 customer whho entered in superstar customer and 89 customers in third cluster is dormant cluster category.

scholarly journals PENERAPAN METODE K-MEANS DENGAN METODE ELBOW UNTUK SEGMENTASI PELANGGAN MENGGUNAKAN MODEL RFM(Recency, Frequency, & Monetary)

Repositor ◽  
2020 ◽  
Vol 2 (7) ◽  
pp. 945
Author(s):  
Adnan Burhan Hidayat Kiat ◽  
Yufiz Azhar ◽  
Vinna Rahmayanti
Keyword(s):  
Euclidean Distance ◽  
Motor Vehicle ◽  
Cluster Formation ◽  
Optimal Number ◽  
Customer Segmentation ◽  
Manhattan Distance ◽  
Automotive Company ◽  
Rfm Model ◽  
Coefficient Method

Segmentasi pelanggan pada perusahaan merupakan tindakan yang dapat mempermudah perusahaan dalam mengambil keputusan ke depan. Pada penelitian ini data yang digunakan berasal dari perusahaan otomotif, PT Hasjrat Abadi Ambon. Data yang dipakai terdiri dari data transaksi dan pelanggan kendaraan bermotor. Penerapan model RFM dapat mengelompokkan pelanggan-pelanggan berdasarkan nilai variabel Recency, Frequency dan Monetary. Hasil dari model RFM akan memperoleh status baru pada tiap pelanggan dari skala terbaik sampai terburuk. Pelanggan yang telah memiliki status akan dikelompokkan menggunakan metode K-Means menjadi beberapa Cluster(kelompok). Dalam menentukan jumlah Cluster yang optimal maka diterapkan metode Elbow. Algoritma yang digunakan dalam pembentukan Cluster terdiri dari Euclidean Distance dan Manhattan Distance. Kedua algoritma akan dibandingkan kualitas pembentukan Clusternya menggunakan metode Silhoutte Coefficient. Hasil yang diberikan pada penelitian ini berupa data yang terbagi atas 5 kelompok dengan dilakukannya lima kali pengujian untuk menentukan centroid yang unggul. Cluster yang unggul akan dibuatkan visualisasi datanya untuk memudahkan perusahaan dalam mengambil keputusan. Berdasarkan penerapan Silhoutte Coefficient, algoritma yang lebih unggul yaitu Manhattan Distance dengan nilai s(i) sebesar 0.152695. Customer segmentation at the company is an action that can facilitate the company in making decisions going forward. In this study the data used came from an automotive company, PT Hasjrat Abadi Ambon. The data used consists of transaction data and motor vehicle customers. The application of the RFM model can classify customers based on the value of the Recency, Frequency and Monetary variables. The results of the RFM model will obtain a new status on each customer from the best to the worst scale. Customers who already have status will be grouped using the K-Means method into several Clusters (groups). In determining the optimal number of Clusters, the Elbow method is applied. The algorithm used in Cluster formation consists of Euclidean Distance and Manhattan Distance. The two algorithms will be compared the quality of the Cluster formation using the Silhoutte Coefficient method. The results given in this study are in the form of data divided into 5 groups by conducting five tests to determine superior centroids. Excellent clusters will be made of data visualization to facilitate the company in making decisions. Based on the application of Silhoutte Coefficient, a superior algorithm is Manhattan Distance with value s(i) : 0.152695.

scholarly journals Factors influencing location choice and cluster pattern of manufacturing small and medium enterprises in cities: evidence from Khulna City of Bangladesh

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
S. M. Towhidur Rahman ◽  
Ahsanul Kabir
Keyword(s):  
Small And Medium Enterprises ◽  
Location Choice ◽  
Cluster Formation ◽  
Personal Factors ◽  
Location Selection ◽  
Community Factors ◽  
Multiple Case ◽  
Specific Factors ◽  
Medium Enterprises ◽  
Cluster Pattern

AbstractThis study aims to identify the location and cluster pattern of manufacturing SMEs in Khulna City and the reasons behind such pattern since localisation of SMEs has significant impact on the economic development of cities and regions. A walking survey was conducted to identify the SME location pattern and a semi-structured personal interview was conducted to collect data from manufacturing SME entrepreneurs to find why such patterns exist. A cross section qualitative multiple case study design and pattern matching technique was applied to answer the research questions. The finding of the study shows SME location choice was influenced by a combination of location specific, personal, and community factors whereby personal factors are prioritised over other factors in location selection. While the cluster formation or localisation of SMEs depends on only location-specific factors. The study findings are expected to contribute in urban planning and regional development through providing useful insights relating allocation of spaces for industry development.

scholarly journals IMPACT OF COVID-19 ON MALAYSIAN E-COMMERCE

2021 ◽  
Vol 5 (4) ◽  
Author(s):  
Vinesh Raj S. ◽  
Meghna Gohain
Keyword(s):  
Small And Medium Enterprises ◽  
Annual Growth Rate ◽  
Potential Growth ◽  
Compound Annual Growth Rate ◽  
Market Outlook ◽  
Customer Services ◽  
The Government ◽  
Medium Enterprises ◽  
Almost All ◽  
Tremendous Impact

COVID-19 pandemic has made a tremendous impact all across the globe. It is clearly reflected in the ongoing lockdowns, closing down of almost all shops, restaurants and public transportations, surge of unemployment etc. all culminating into severe economic depression. Malaysia, also, has faced this hit of recession, depreciation, and unemployment to a great extent with the current pandemic situation. However, when everything seems to be crumbling, e-commerce appears to have found its golden break in raising its profit and contributing to the overall GDP growth of Malaysia. There are various factors that played into the booming of e-commerce owing to the current pandemic situation. Needless to say, the value of e-commerce in helping the depleting economy and just plain convenience for people to purchase essential commodities during lockdown cannot be denied. Even the government of Malaysia has been showing support by encouraging local Micro, Small and Medium Enterprises (MSMEs). E-commerce has the potential to become a major source of contribution to the country’s economy. However, it needs to ramp up their infrastructure regarding security, delivery, and customer services. Additionally, importance should be given to local businesses in order to empower the local e-commerce sector. This article aims to give an overview of the trend in the growth of e-commerce during the COVID era and its potential growth in the next four years based on Compound Annual Growth Rate (CAGR) and Statista Digital Market Outlook and the factors that have led to the boom in e-commerce in Malaysia.

Innovative Marketing Strategies for Small and Medium Enterprises of Western Madhya Pradesh (India): An Analytical Study

2020 ◽  
Vol 47 (2) ◽  
pp. 146-162
Author(s):  
Pragya Keshari
Keyword(s):  
Small And Medium Enterprises ◽  
Decisive Role ◽  
Industrial Sector ◽  
Marketing Strategies ◽  
Madhya Pradesh ◽  
Primary Data ◽  
Review Of Literature ◽  
Chi Square ◽  
Chi Square Test ◽  
Medium Enterprises

The micro, small and medium enterprises are an essential part of the Indian industrial sector. It plays a decisive role in growth and development of Indian economy. The review of literature on various aspects of small and medium enterprises (SMEs) showed that the SMEs, both in the country and other parts of the world, still rely on conventional marketing practices and, more or less, face the same types of challenges. Therefore, the present study is undertaken to examine the marketing strategies of SMEs in western Madhya Pradesh, India, and to suggest some innovative marketing practices for them to prosper. The sample consists of 439 SMEs drawn on a random basis from Indore and Dhar districts of Madhya Pradesh. The primary data are collected through a self-designed instrument with 40 items/statements, developed thorough a review of literature on the topic and personal interviews of managers of SMEs. The data are analysed using statistical tools like factor analysis and chi-square test applied with the help of Statistical Package for Social Sciences (SPSS) 20 Software. The study findings reveal that SME managers still rely on age-old practices of marketing. The article recommends some innovative marketing practices for SMEs.

Service Marketing Strategies for Small and Medium Enterprises

2019 ◽  
Author(s):  
Muhammad Sabbir Rahman ◽  
Mahmud Habib Zaman ◽  
Md Afnan Hossain
Keyword(s):  
Small And Medium Enterprises ◽  
Service Marketing ◽  
Marketing Strategies ◽  
Medium Enterprises

scholarly journals International Marketing Strategies in the Jewellery Industry: Are They Standardised, Adapted or Both?

2018 ◽  
Vol 10 (1) ◽  
pp. 1
Author(s):  
Diego Matricano ◽  
Giorgio Vitagliano
Keyword(s):  
Small And Medium Enterprises ◽  
Single Case ◽  
International Marketing ◽  
Marketing Strategies ◽  
Fast Fashion ◽  
Market Growth ◽  
Contingency Perspective ◽  
International Marketing Strategy ◽  
Medium Enterprises ◽  
Adaptation Processes

According to analysts and practitioners, five main trends characterise the future of the jewellery industry: internalisation and consolidation; market growth; a new channel landscape; hybrid consumption; and fast fashion. Among these, the process of internalisation, which is started and managed by local jewellery brands, seems of great interest. These brands, generally small and medium enterprises (SMEs), have to plan their international marketing strategies in order to face the biggest jewellery groups and compete worldwide.In the present paper, through the methodology of a single case study of leBebè, an Italian brand, the standardisation and adaptation processes of international marketing strategies are rebuilt and investigated in reference to the jewellery industry. From the analysis, it emerges that the jewellery industry has specific dynamics that force companies to implement an international marketing strategy that falls halfway between standardisation and adaptation and is generally known as a contingency perspective. The achieved results strengthen the contingency perspective on the standardisation/adaptation debate and, above all, allow for speculating that international marketing strategies partly depend on the brand and mostly depend on the prominence of the brands and on factors characterising each industry. 

scholarly journals DESAIN TAMAN KULINER UNTUK PEDAGANG KAKI LIMA YANG INOVATIF DI TEPI SUNGAI, SURABAYA

2015 ◽  
Vol 3 (1) ◽  
pp. 28-34
Author(s):  
Gunawan Tanuwidjaja ◽  
El Sadday A. Oktovianto ◽  
Joyie Joyie ◽  
Felicia Lisandra S.
Keyword(s):  
Human Resources ◽  
Architectural Design ◽  
Small And Medium Enterprises ◽  
Marketing Strategies ◽  
Traditional Food ◽  
Physical Effort ◽  
Street Vendors ◽  
Visual Research ◽  
Food Center ◽  
Medium Enterprises

Nowadays, the owners of Small and Medium Enterprises (SMEs), especially food street vendors (PKL) faced difficulty to increase the operational scale and productivity. Besides that, the street vendors are still not able to compete, because of limited architectural design, human resources, and marketing strategies. Therefore, street-food center design, which integrated with Urban Park was needed with attention of cleanliness, comfort, neatness aspects and producing positive image. In the paper, design process street-hawker kiosk was started with exploration into traditional food restaurants and traditional food vendors using visual research. The design was based on the principles of inclusive design such as: User Centered, Equitable use but Reasonable, Simple and Intuitive Use, Low Physical Effort, and Prohibition of Usage Error.

scholarly journals STRATEGI DIGITAL BRANDING UNTUK MENINGKATKAN PENJUALAN UMKM INDONESIA

2021 ◽  
Vol 1 (1) ◽  
pp. 202-214
Author(s):  
Sonny Santosa ◽  
Rini Novianti ◽  
Tri Anggraeni ◽  
Elizabeth Elizabeth ◽  
Andre Gustriandi
Keyword(s):  
Factor Analysis ◽  
Small And Medium Enterprises ◽  
Marketing Strategies ◽  
Creative Economy ◽  
Positive Side ◽  
The World ◽  
Two Factors ◽  
Main Factors ◽  
Digital Branding ◽  
Medium Enterprises

This is the time for us to see the positive side caused by pandemic. Even though not everybody agrees to this, the pandemic going on not only in Indonesia but also in all over the world has given us a chance for ‘adaptation’ over changes in business. Nowadays, business concept is not only affected by markets, companies, competitors but also by changes. Every individual, even a big company must acknowledge this. In order to maintain the side of people’s ‘economy’, various studies reviewing alternatives for good marketing strategies have been carried out. These studies are especially aimed at Small and Medium Enterprises (SMEs). This is because SMEs have been the part of creative economy. Based on these circumstances, the researcher was encouraged to study which strategy of digital branding dominantly carried out by the SME players. This research applied factor analysis to find out the basic attribute grounding SME players to survive their businesses, which were initiated either before or after pandemic. The method used was non-probability sampling. Here the questionnaires were distributed in order to find answers from five determined spots. There were 169 respondents as samples in this research. In the pre-test, before questionnaires distributed, there were at least 9 attributes used as references for the main players of SMEs in applying digital branding. Results of factor analysis test showed that there were at least two main factors developed. In these two factors, it is agreed that strategy of Search Engine Optimization was the most ideal to apply in order to survive their business. This is because it has big dominant value, which was 0.823 (82% for first group) and 0.790 (79% for the second group).

scholarly journals COMPARATIVE STUDY OF FUZZY C-MEANS AND K-MEANS ALGORITHM FOR GROUPING CUSTOMER POTENTIAL IN BRAND LIMBACK

2021 ◽  
Vol 3 (4) ◽  
pp. 327-334
Author(s):  
Difa Lazuardi Aditya ◽  
Devi Fitrianah
Keyword(s):  
Optimal Number ◽  
Customer Segmentation ◽  
Cluster Validation ◽  
Fuzzy C Means ◽  
Monetary Analysis ◽  
A Value ◽  
Silhouette Coefficient ◽  
Potential Customers ◽  
Cluster 2 ◽  
Optimal Number Of Clusters

The customer is a stakeholder for a business, to maintain and increase customer enthusiasm and develop it for the company's performance, it is necessary to do customer segmentation which aims to find out potential customers. This study uses purchase transaction data from Brand Limback customers in the period 2020. The use of RFM (Recency, Frecuency, Monetary) analysis helps in determining the attributes used for customer segmentation. To determine the optimal number of clusters from the RFM dataset, the Elbow method is applied. The datasets generated from RFM are grouped using the Fuzzy C-Means and K-Means algorithms, the two algorithms will compare the quality in the formation of clusters using the Silhoutte Coefficient and Davies-Bouldin Index methods. Customer segmentation from the RFM dataset that has been clustered produces 7 optimal clusters, namely Cluster 0 is a bronze customer. Cluster 1 is a silver customer. Cluster 2 is a gold customer. Cluster 3 is a platinum customer. Cluster 4 is a diamond customer. Cluster 5 is a super customer, and cluster 6 is a superstar customer. The cluster validation of k-means using the silhouette coefficient produces a value of 0.934 while the Davies bouldin index produces a value of 0.155 and the validation results of the fuzzy c-means algorithm using the silhouette coefficient produces a value of 0.921 while the Davies bouldin index produces a value of 0.145.

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