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ITS » Undergraduate Theses » Teknik Industri
Posted by eny at 04/02/2009 16:24:13  •  3060 Views


EVALUASI DAN SELEKSI SEGMENTASI PASAR PRODUCT FAMILY DENGAN MENGGUNAKAN METODE FUZZY CLUSTERING (STUDI KASUS : PT. MEGACAHAYA TEKNIKATAMA)

EVALUATION AND SELECTION MARKET SEGMENTATION FOR PRODUCT FAMILY BASED ON FUZZY CLUSTERING (CASE STUDY : PT. MEGACAHAYA TEKNIKATAMA SURABAYA)

Created by :
PUJIASTUTI, HENING 



SubjectMarketing
KeywordProduct family
Segmentasi pasar
Fuzzy clustering

Description:

Segmentasi pasar merupakan hal yang penting bagi suatu perusahaan (industri). Hal ini didasari oleh perusahaan yang tidak dapat berhubungan dengan semua pelanggan di pasar yang besar, luas dan beraneka ragam. Dengan segmentasi pasar yang baik maka perusahaan mampu melayani target strategisnya yang sempit secara efektif dan efisien ketimbang pesaing yang bersaing lebih luas. Penelitian ini menggunakan metode fuzzy clustering yang dikembangkan oleh Zhang et al. (2006) dan diterapkan pada PT. Megacahaya Teknikatama yang merupakan distributor lampu PEUR (Product End User and Replacement). Product Family yang diamati adalah lampu fluorescent. Tujuan dari penelitian adalah merumuskan strategi produksi dan pemasaran yang tepat bagi perusahaan. Tools yang digunakan dalam penyelesaian penelitian adalah SPSS 14.0. Hasil dari clustering adalah 3 buah klaster. Klaster pertama terdiri dari 30 produk dengan mean value 10,4 (watt), WW (Colour designation), ES (cap base), 57,5 cm (diameter ulir), 81,9 Ra (rendering index), 2700 K (colour temperature) dan 556 lm (lamp luminous flux) dan kontribusi penjualannya sebesar 25,9%. Dimana produk berpasangan dengan konsumen. Sedangkan klaster kedua terdiri atas 7 produk dengan kontribusi penjualan 6 %. Mean value klaster kedua adalah 58,4 (watt), CDL (Colour designation), ES (cap base), 70 cm (diameter ulir), 80,5 Ra (rendering index), 6500 K (colour temperature) dan 3857,1 lm (lamp luminous flux). Dan klaster ketiga terdiri atas 79 buah produk dengan prosentase penjualan tertinggi yakni 68,1 %. Mean value dari klaster ketiga adalah 15,4 (watt), CDL (colour designation), ES (cap base), 66,1 cm (diameter ulir), 79,6 Ra (rendering index), 6451,9 K (colour temperature) dan 906,9 lm (lamp luminous flux). Setelah dilakukan fuzzy clustering, hasil yang diperoleh dibandingkan dengan K-Means. Berdasarkan hasil pengolahan K-Means diperoleh 3 klaster. Klaster pertama terdiri dari 79 produk, klaster kedua terdiri atas 6 produk dan klaster ketiga 30 produk. Jumlah produk yang terdapat di klaster 1 dan 3 antara fuzzy clustering dan K-Means berbeda, tetapi hal itu tidak mempengaruhi membership. Selain itu pada produk 43 dan 103 ada beda klaster yang menunjukkan kesamaran dari produk, produk 43 merupakan lampu genie dan produk 103 adalah lampu tornado. Untuk ketiga klaster hasil pengolahan fuzzy clustering, dirumuskan strategi produksi yang sesuai. Strategi produksi tersebut berupa prioritasisasi alokasi resource dan penjadwalan produksi, yakni klaster ketiga, klaster pertama dan klaster kedua. Alokasi resource yang diberikan berupa peralatan/mesin, bahan baku, waktu dan tenaga kerja. Ketiga klaster tersebut dapat meningkatkan efisiensi produksi karena merupakan representasi dari tujuh jenis lampu fluorescent yang memiliki kontribusi penjualan tinggi. Sedangkan strategi pemasaran berupa 4P (Product, Price, Place and Promotion) dan PDB (Positioning, Differentiation and Branding).


Alt. Description

Market segmentation is very essential for a company (industry). since company that can’t connect with all customers in large, broad and diverse market. Good market segmentation will bring company to their target segment effectively and efficiently rather than competitor that compete in wide market. This research uses fuzzy clustering method that developed by Zhang et al. (2006) and implemented in PT. Megacahaya Teknikatama which is distributor of PEUR (Product End User and Replacement) lamp. This research develop production and marketing strategy for company. SPSS 14.0 is used for this research. The result of clustering are 3 clusters. The first cluster consist of 30 products with mean value 10,4 (watt), WW (Colour designation), ES (cap base), 57,5 cm (screw thickness), 81,9 Ra (rendering index), 2700 K (colour temperature) and 556 lm (lamp luminous flux). This cluster donate 25,9 % of sales. In this case, product and customers are pairs. While the second cluster consist of 7 products and give 6 % of sales. Mean value of second cluster are 58,4 watt, CDL (Colour designation), ES (cap base), 70 cm (screw thickness), 80,5 Ra (rendering index), 6500 K (colour temperature) and 3857,1 lm (lamp luminous flux). And the last cluster consist of 79 products with the highest percentage of sales which is 68,1 %. Mean value of the third cluster are 15,4 (watt), CDL (colour designation), ES (cap base), 66,1 cm (screw thickness), 79,6 Ra (rendering index), 6451,9 K (colour temperature) and 906,9 lm (lamp luminous flux). After fuzzy clustering has finished, the result compares with K-Means. From K-Means method, we get 3 clusters, the first consist of 79 products, second cluster consist of 6 products and the last cluster consist of 30 products. Total products from the first and last cluster between fuzzy clustering and K-Means are different, but that doesn’t affect membership. Besides, product 43 and 103 have different clusters, that show fuzziness of products. Product 43 is genie and product 103 is tornado lamp. Production strategy are propsed based on fuzzy clustering, which is doing by prioritize resource allocation which is the third cluster, followed by the first and second cluster. Resource allocation by allocate machine, raw material, time and workers. Those clusters can raise production efficency. It cause of those clusters represent 7 type of fluorescent lamp. And marketing strategy develop based on 4P and PDB.

Contributor:
  1. Dr. Ir. Patdono Suwignjo M.Eng, Sc.
    Ir. Budi Santosa, M.S.,Ph.D
Date Create:04/02/2009
Type:Text
Format:pdf
Language:Indonesian
Identifier:ITS-Undergraduate-3100009034081
Collection ID:3100009034081
Call Number:RSI 658.8 Puj e


Source :
Undergraduate Theses, Industrial Engineering, RSI 658.8 Puj e, 2008

Coverage :
ITS Community Only

Rights :
Copyright @2008 by ITS Library. This publication is protected by copyright and permission should be obtained from the ITS Library prior to any prohibited reproduction, storage in a retrievel system, or transmission in any form or by any means, electronic, mechanical, photocopying, recording, or likewise. For information regarding permission(s), write to ITS Library.


Publication URL :
http://digilib.its.ac.id/evaluasi-dan-seleksi-segmentasi-pasar-product-family-dengan-menggunakan-metode-fuzzy-clustering-studi-kasus--pt-megacahaya-teknikatama-3509.html




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