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All Journal Economic Reviews Journal Innovative: Journal Of Social Science Research
Nur Aulia, Reza
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Humanities Computer Science & IT Economics, Econometrics & Finance Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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Analisis Evaluasi Efektivitas Metode Forecasting Moving Avarage Naive Approach, Simple Moving Average, Exponential Smoothing terhadap Supply Chain Management PT XYZ Taufiqillah, Rizal; Nur Aulia, Reza; Dewi, Puspita; Heikal, Jerry
Innovative: Journal Of Social Science Research Vol. 4 No. 5 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i5.15167

Abstract

Pada PT XYZ sering kali mengalami persoalan dalam memastikan stock bahan baku sesuai dengan permintaan, yang berakibat timbulnya biaya tidak efisien dan risiko kekurangan / kelebihan stok. Permasalahan supply chain management pada PT XYZ terindikasi bahwa ketidak efektivenya pola kerja metode forecasting simple moving average 3 bulan yang diterapkan. Hal itu dapat terlihat pada data yang disampaikan penulis bahwa kebutuhan bahan baku setiap periodenya tidak tetap atau tidak stabil, hal ini tidak sesuai dengan kriteria dalam memaximalkan penggunaan metode forecasting moving average 3 bulan. Sehingga penelitian ini bertujuan untuk melihat efektifitas atas metode peramalan dalam supply chain management pada PT XYZ. Pada penelitian ini peneliti membandingkan 3 metode forecastin yaitu Moving average naïve approach, simple moving average 3 bulan, dan exponential smoothing. Hasil analisis penelitian memberikan gambaran bahwa exponential smoothing adalah model forecasting paling akurat dan minim eror dalam membuat prediksi kebutuhan bahan baku logam baja. Dalam menggunakan metode exponential smoothing, bisa membantu lebih cepat dalam merespon perubahan permintaan pasar. Penelitian ini merekomendasikan dalam menggunakan exponential smoothing harus memperhatikan peningkatan koordinasi antar departemen, menggunakan data yang real time, serta pelatihan komprehensif tentang metode forecasting exponential smoothing yang dapat memberikan support optimal terhadap aktivitas supply chain management (SCM) pada PT XYZ.
Analysis Customer Segmentation on Individual Life Insurance in Kalimantan Province Using K-Means Clustering with SPSS Nur Aulia, Reza; Taufiqillah, Rizal; Dewi, Puspita
Innovative: Journal Of Social Science Research Vol. 4 No. 5 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i5.15169

Abstract

The Indonesian life insurance industry has witnessed remarkable growth in recent years, fueled by a rising awareness among the populace regarding the significance of safeguarding oneself and their families. However, the industry also faces a multitude of challenges, including intense competition, low market penetration, and evolving consumer behavior. Customer segmentation emerges as a crucial strategy to address these challenges effectively. Market segmentation holds immense value as it empowers companies to tailor their products and services to specific customer groups. Implementing K-Means Clustering to categorize life insurance customers based on their profiles and behaviors proves to be an effective approach for developing a successful marketing strategy. Understanding the profiles and behaviors of life insurance customers can serve as a powerful tool for attracting new customers. This case study delves into the practices of a prominent life insurance company in Indonesia, referred to as PT. XYZ to maintain data privacy. Customer data was extracted from the company's internal database in April 2024, and the analysis focused exclusively on customers in Kalimantan Island. The study's findings reveal significant differences in characteristics and preferences among the three identified customer segments. Life insurance products emerged as the most sought-after across all segments. While the Agency channel dominated in all segments, Bancassurance also held a notable market share. Bundling life insurance products with additional accident insurance benefits presents a compelling value proposition. Expanding hospital coverage to encompass the ASEAN region can further enhance the value proposition. The 7P framework serves as a valuable tool for achieving the company's strategic objectives.
Customer Churn Prediction for Life Insurance Using Binary Logistic Regression Dewi, Puspita; Nur Aulia, Reza; Taufiqillah, Rizal
Economic Reviews Journal Vol. 3 No. 3 (2024): Economic Reviews Journal
Publisher : Masyarakat Ekonomi Syariah Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56709/mrj.v3i3.353

Abstract

One of a major problem for many industries including life insurance is customer churn. Because insurance contracts are often renewed every year, insurance businesses have a much harder time retaining customers than other businesses. The main objective of this research is to mitigate expected customer loss and retain potentially lost customers by increasing incentive product and service offerings on behalf of PT. XYZ Insurance, one of the life insurance companies in Indonesia which was founded in 2008. With a total of 123,982 policyholder data were included in the data set for this research, which covers a one-year data period as of December 2022. These data include details about the insurance holder, age of the insured, payment frequency, tenor, premium, and the product chosen by the policyholder of customers at PT. XYZ Insurance. In this research, the data is processed based on binary logistic regression in SPSS, where the data is processed in such a way as to produce output that meets the researchers' expectations. From the results of this research, there are around 16,951 insurance customers who have the potential to churn customers. So, company must implement customized value propositions based on research findings to help retain customers and reduce churn rates effectively in the competitive insurance market. Then the results of this research can also be used to target identified customers in marketing campaigns aimed at reducing churn rates while increasing profitability
Co-Authors Heikal, Jerry Puspita Dewi, Puspita Taufiqillah, Rizal