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All Journal Variance : Journal of Statistics and Its Applications Empiricism Journal
Rivaldo, Rendi
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Chemistry Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Estimasi Pengunjung Pontianak Interactive Center dengan Menggunakan Metode Double Exponential Smoothing Satyahadewi, Neva; Aprizkiyandari, Siti; Rivaldo, Rendi
Empiricism Journal Vol. 4 No. 2: December 2023
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/ej.v4i2.1517

Abstract

Pontianak Interactive Center (Pontive Center) adalah salah satu layanan publik yang disediakan pemerintah melalu Dinas Komunikasi dan Informatika Kota Pontianak. Pontive Center menyediakan layanan publik seperti pusat kendali CCTV dan berbagai sensor pengamatan, pengelolaan informasi, sistem TIK, dan sebagainya. Jumlah kunjungan setiap bulannya di Pontive Center cukup beragam sehingga diperlukan estimasi jumlah kunjungan agar Pontive Center dapat mempersiapkan segala alternatif yang dapat digunakan jika terjadi lonjakan jumlah kunjungan. Metode yang digunakan pada penelitian ini yaitu metode Double Exponential Smoothing (DES) dalam mengestimasikan jumlah kunjungan di Pontive Center. Data yang digunakan yaitu data jumlah kunjungan di Pontive Center dalam bulanan dari tahun 2019-2022. Data ini merupakan jumlah kunjungan di Pontive Center seperti kunjungan instansi, rapat kerja, seminar, sosialisasi dan sebagainya. Penelitian ini mengestimasikan jumlah kunjungan selama 12 bulan ke depan dan didapat rata-rata jumlah kunjungannya yaitu 11-12 kunjungan perbulannya. Perhitungan nilai Mean Absolut Percentage Error (MAPE) yang didapat yaitu sebesar 42%, sehingga model estimasi dengan Double Exponential Smoothing pada penelitian ini cukup layak digunakan. Estimated Visitors to the Pontianak Interactive Center Using the Double Exponential Smoothing Method Abstract Pontianak Interactive Center (Pontive Center) is one of the public services provided by the government through the Pontianak City Communication and Information Service. Pontive Center provides public services such as CCTV control centers and various observation sensors, information management, ICT systems, and so on. The number of visits each month at the Pontive Center is quite varied, so an estimate of the number of visits is needed so that the Pontive Center can prepare all alternatives that can be used if there is a spike in the number of visits. The method used in this research is the Double Exponential Smoothing (DES) method in estimating the number of visits to the Pontive Center. The data used is data on the number of visits to the Pontive Center monthly from 2019-2022. This data represents the number of visits to the Pontive Center such as agency visits, work meetings, seminars, socialization and so on. This study estimated the number of visits over the next 12 months and found that the average number of visits was 11-12 visits per month. The calculation of the Mean Absolute Percentage Error (MAPE) value obtained is 42%, so the estimation model with Double Exponential Smoothing in this research is quite suitable for use.
Implementasi K-Means Cluster untuk Menentukan Persebaran Tingkat Pengangguran Aprizkiyandari, Siti; Satyahadewi , Neva; Pratama, Aditya Nugraha; Rivaldo, Rendi; Nurdiansyah , Syarif Irwan; Helena, Shifa
Empiricism Journal Vol. 4 No. 2: December 2023
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/ej.v4i2.1518

Abstract

Tingkat pengangguran yang ada di Kalimantan Barat sangat bervariasi. Terdapat Kabupaten/ Kota dengan tingkat pengangguran tinggi dan ada yang rendah, namun belum terdapat pengelompokkannya. Pada penelitian ini, Kabupaten/ Kota di Kalimantan Barat dikelompokkan dengan analisis klaster menggunakan metode K-Means Cluster. Metode K-Means Cluster dapat digunakan dalam pengambilan keputusan dalam mengelompokkan tingkat pengangguran di Kalimantan Barat berdasarkan indikator yang digunakan. Indikator pada penelitian ini terdiri dari TPT, IPM, PDRB dan UMK, dimana data berasal dari BPS Provinsi Kalimantan Bartat. Diperoleh hasil yaitu terbentuknya 2 klaster. Klaster 1 mewakili  kabupaten/kota dengan tingkat pengangguran tinggi yang terdiri dari 4 anggota yaitu Kabupaten Kubu Raya, Kabupaten Ketapang, Kota Pontianak, dan Kota Singkawang dengan persentase TPT klaster 1 yaitu sebesar 8,87%. Sedangkan klaster 2 terdiri dari 10 Kabupaten, yaitu  Kayong Utara, Melawi, Sekadau, Kapuas Hulu, Sintang, Sanggau, Mempawah, Landak, Bengkayang dan Sambas dengan TPT klaster 2 yaitu sebesar 3,73%. Implementation of K-Means Cluster to Determine the Distribution of Unemployment Rate Abstract Unemployment rates in West Kalimantan vary widely. There are regencies/municipalities with high unemployment rates and some with low unemployment rates, but there is no grouping yet. In this research, regencies/municipalities in West Kalimantan are grouped by cluster analysis using the K-Means Cluster method. K-Means Cluster method can be used in decision-making in grouping the unemployment rate in West Kalimantan based on the indicators used. The indicators in this study consist of TPT, HDI, GRDP, and MSE, where the data comes from BPS of West Kalimantan Province. The result obtained is the formation of 2 clusters. Cluster 1 represents districts/cities with a high unemployment rate consisting of 4 members, namely Kubu Raya Regency, Ketapang Regency, Pontianak City, and Singkawang City with a TPT percentage of cluster 1 of 8.87%. Meanwhile, cluster 2 consists of 10 regencies, namely North Kayong, Melawi, Sekadau, Kapuas Hulu, Sintang, Sanggau, Mempawah, Landak, Bengkayang, and Sambas with a TPT cluster 2 of 3.73%.
GROSS PREMIUM VALUATION METHOD IN DETERMINING PREMIUM RESERVES IN LIFE INSURANCE Rivaldo, Rendi; Perdana, Hendra; Andani, Wirda
VARIANCE: Journal of Statistics and Its Applications Vol 6 No 2 (2024): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol6iss2page215-222

Abstract

Abstract: Life insurance companies maintain reserve funds to pay insurance policy claims, known as premium reserves. Premium reserves are calculated using two approaches: retrospective and prospective. The prospective approach involves calculating the present value of all future expenses minus the total future income for each policyholder, using the Gross Premium Valuation (GPV) method. The GPV method takes into account initial costs, maintenance costs, and administration costs. The case study results indicate that the premium reserve using the GPV method starts at zero in the first year, increases until the last payment year, and then decreases after the payment period until the end of the coverage period. For policyholders of different genders but the same age, the premium reserve for men is greater than for women. Additionally, for male policyholders of varying ages, the premium reserves required increase with age. Furthermore, for male policyholders of the same age but with different interest rates, a higher interest rate results in a smaller premium reserve requirement.
Co-Authors Andani, Wirda Aprizkiyandari, Siti Helena, Shifa Hendra Perdana Neva Satyahadewi Nurdiansyah , Syarif Irwan Pratama, Aditya Nugraha Satyahadewi , Neva