Analisis Segmentasi Pramurukti Menggunakan Integrasi Modifikasi Model Personal Strain, Role Strain, Dependency, Guilt (Prdg) Dan Fuzzy C-Means

Rahmayanti, Nabillah Annisa (2022) Analisis Segmentasi Pramurukti Menggunakan Integrasi Modifikasi Model Personal Strain, Role Strain, Dependency, Guilt (Prdg) Dan Fuzzy C-Means. Masters thesis, Institut Teknologi Sepuluh Nopember.

Text 6026201005-Master_Thesis.pdf Restricted to Repository staff only Download (3MB) | Request a copy

Abstract

Pasar tenaga kerja global menyebabkan permintaan pramurukti wanita asal Indonesia ke Taiwan meningkat. Namun peningkatan ini disertai dengan meningkatnya permasalahan terkait dengan beban kerja yang dirasakan oleh pramurukti selama merawat lansia. Dalam penelitian ini, analisis segmentasi pramurukti dilakukan untuk menemukan pola strategi seleksi calon pramurukti berdasarkan karakteristik pramurukti yang diperkirakan tangguh terhadap beban kerja. Analisis segmemtasi dilakukan terhadap data yang diperoleh dari hasil kuesioner kepada 299 responden. Kuesioner berisi 22 pertanyaan yang mewakili instrumen zarit burden interview (ZBI) dan memiliki empat dimensi, yaitu personal strain, role strain, dependency, dan guilt (PRDG). Karakteristik personal yang diperkirakan paling berpengaruh terhadap berban kerja diperoleh menggunakan confirmatory factor analysis (CFA) dan analisis regresi berganda. Hasil CFA mengindikasikan perlunya memisahkan dimensi social life dari dimensi personal strain sebagai dimensi baru yang merepresentasikan permasalahan sosial dari pramurukti. Sedang hasil analisis regresi berganda menghasilkan tiga karakteristik pramurukti yang paling berpengaruh, yaitu jumlah anak, tingkat pendidikan, dan lokasi kerja. Analisis segmemtasi dilakukan menggunakan algoritma fuzzy c-means terhadap model PRDG yang dimodifikasi dengan tambahan dimensi social life sebagai dimensi baru (S+PRDG). Dari analisis segmentasi diperoleh hasil berupa dua segmen terbaik yang memiliki nilai fuzzy silhouette index sebesar 0,61. Analisis terhadap kedua segmen ini dapat disimpulkan bahwa pramurukti yang diperkirakan tangguh terhadap beban kerja terdapat dalam segmen kedua dengan karateristik bahwa secara rata-rata mereka telah memiliki anak, mempunyai tingkat pendidikan hingga sekolah menengah pertama, dan mempunyai lokasi kerja di ibu kota Taiwan.
==============================================================================================================================
The global labor market has caused a surge in demands for Indonesian female caregivers in Taiwan. Unfortunately, this increase is accompanied by an increase in problems related to the workload of the caregivers while caring for the elderly. In this study, a segmentation analysis of 299 questionnaire data was conducted to find selection pattern strategies of prospective caregivers based on their characteristics to handle a heavy workload as caregivers. This questionnaire consisted of 22 questions representing the Zarit Burden Interview (ZBI) instrument and four dimensions, namely personal strain, role strain, dependency, and guilt (PRDG). Personal characteristics that were estimated to significantly influence the workload were obtained using confirmatory factor analysis (CFA) and multiple regression analysis. The results of the CFA indicated the need to separate the dimensions of social life from those of personal strain as a new dimension representing the caregivers’ social problems. The results of multiple regression analysis indicated three most influential characteristics of a caregiver: number of children, education level, and work location. The segmentation analysis was carried out using the fuzzy c-means algorithm on the modified PRDG model with the addition of the social life dimension as a new dimension (S+PRDG). The segmentation analysis resulted in two best segments that have a fuzzy silhouette index value of 0.61. From the analysis of these two segments, it could be concluded that the caregivers who were estimated to be able to handle a heavy burden were those in the second segment with the characteristics such as having children, having level of education up to junior high school, and working in the capital city of Taiwan.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	pramurukti wanita indonesia, segmentasi, modifikasi model PRDG, fuzzy c-means, silhouette index. indonesian female caregivers, segmentation, modification of PRDG model, fuzzy c-means, silhouette index.
Subjects:	T Technology > T Technology (General) > T58.6 Management information systems
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information System > 59101-(S2) Master Thesis
Depositing User:	Mr. Marsudiyana -
Date Deposited:	06 Jul 2026 08:40
Last Modified:	06 Jul 2026 08:40
URI:	http://repository.its.ac.id/id/eprint/134367

Actions (login required)

View Item