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Pembelajaran Matematika Melalui Pendekatan Open-Ended dengan Bantuan Power Point untuk Meningkatkan Kemampuan Pemecahan Masalah di Masa Pandemi Tiara Yulita; Hardi Suyitno; Sugiman Sugiman
Jurnal Cendekia : Jurnal Pendidikan Matematika Vol 5 No 2 (2021): Jurnal Cendekia: Jurnal Pendidikan Matematika: Volume 5 Nomor 2, In press
Publisher : Mathematics Education Study Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cendekia.v5i2.660

Di masa pandemi, seluruh kegiatan pembelajaran khususnya pembelajaran matematika tidak dilaksanakan di sekolah melainkan dirumah masing-masing atau secara daring. Salah satu keterampilan matematika yang perlu dikuasai peserta didik adalah kemampuan pemecahan masalah. Kurikulum 2013 revisi 2018 juga menerapkan bahwa peserta didik harus terlibat secara aktif dalam pemecahan masalah serta dapat menafsirkan dan memahami kompetensi yang dibimbing oleh guru. Hasil UN peserta didik SMP/MTs/SMPT menunjukan bahwa kemampuan pemecahan masalah peserta didik masih tergolong rendah padahal soal tersebut merupakan soal rutin, sedangkan soal non rutin (open-ended problems) sudah jarang digunakan pada saat penyajian soal. Salah satu upaya untuk mengatasi hal tersebut yaitu menggunakan pendekatan open-ended dengan bantuan power point sebagai media penunjang dalam pembelajaran daring di masa pandemi. Populasi yang diambil adalah peserta didik kelas VII SMP Negeri 1 Comal, sedangkan metode yang digunakan adalah quasi experimental design dengan rancangan penelitian berupa pre-test post-test control group dimana terdapat dua kelompok uji coba yaitu kelompok eksperimen dan kontrol yang dipilih secara random sampling. Dari uji kesamaan rata-rata pihak kanan dan uji gain ternormalisasi menunjukan hasil bahwa pembelajaran dengan pendekatan open-ended dan power point efektif untuk meningkatkan kemampuan pemecahan masalah peserta didik dan lebih baik dibanding model pembelajaran ekspositori.

PERBANDINGAN TABEL MORTALITA TASPEN 2012 (TMT 2012) DAN TABEL MORTALITA INDONESIA 2011 (TMI 2011) MENGGUNAKAN UJI MANN-WHITNEY Tiara Yulita Lita
Binawan Student Journal Vol. 4 No. 1 (2022)
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Binawan (LPPM Universitas Binawan)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54771/bsj.v4i1.188

Tabel Mortalita Indonesia digunakan sebagai referensi perusahaan asuransi di Indonesia dalam menentukan premi. Tabel Mortalita Indonesia menggunakan data yang diperoleh dari perusahaan-perusahaan asuransi di Indonesia. Namun, terdapat kemungkinan perbedaan distribusi agen pada setiap asuransi jiwa di Indonesia yang mengakibatkan perbedaan karakteristik nasabah asuransi jiwa di Indonesia. Oleh sebab itu, setiap perusahaan asuransi jiwa di Indonesia diharapkan memiliki tabel mortalitas yang menggambarkan karakteristik dari nasabah perusahaan asuransi jiwa itu sendiri. Tabel Mortalita Taspen 2012 adalah tabel mortalita yang dibuat oleh PT. Taspen (Persero). Paper ini menguji apakah TMT 2012 dengan TMI 2011 menunjukkan perbedaan yang nyata pada rata-rata tingkat kematian. Data tingkat kematian pada TMT 2012 dan TMI 2011 tidak mengikuti distribusi normal dan distribusi lainnya sehingga lebih tepat menggunakan uji nonparametrik Mann-Whitney dan diperoleh kesimpulan kedua tabel mortalita tersebut tidak menunjukkan perbedaan yang nyata pada rata-rata tingkat kematian.

ESTIMATION OF IBNR AND RBNS RESERVES USING RDC METHOD AND GAMMA GENERALIZED LINEAR MODEL Tiara Yulita; Adhitya Ronnie Effendie
MEDIA STATISTIKA Vol 15, No 1 (2022): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.15.1.24-35

Estimation of claims reserves is a very important role for insurance companies because the information will be used to assess the insurance company’s ability to meet future claim payment obligations. In practice, claims reserves are divided into two Incurred but Not Reported (IBNR) and Reported but Not Settled (RBNS). Reserving by Detailed Conditioning (RDC) is one of the individual methods that can estimate claims reserves of both the IBNR and RBNS, which involves detailed condition so-called claim characteristics, and some information else so-called background variable. The result of estimating claims reserves using RDC with background variable is not stable because many combinate of calculation from each background variable. The purpose of this study is to overcome these problems, which we can combine RDC and Gamma Generalized Linear Model (GLM) as an effective method for estimating claims reserves. By using Bootstrapping Individual Claims Histories (BICH) method, the results show that estimation of claims reserves using RDC and Gamma GLM gives the fewest value of Mean Square Error of Prediction (MSEP) rather than RDC with Poisson GLM, RDC, and Chain Ladder. Where the smaller the value of the resulting MSEP estimate, the closer to the actual claim reserve value.

PENENTUAN PREMI MURNI DI KABUPATEN KEPAHIANG PROVINSI BENGKULU DENGAN MEMPERHITUNGKAN PELUANG KEJADIAN GEMPA BUMI DAN RASIO KERUSAKAN BANGUNAN Tiara Yulita; Chaterine Theresia Lubis; Agus Sofian Eka Hidayat
VARIANCE: Journal of Statistics and Its Applications Vol 5 No 2 (2023): 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/variancevol5iss2page147-158

Indonesia is a country that is very vulnerable to earthquakes, one of which is in Bengkulu Province, especially Kepahiang Regency. To deal with risks or losses caused by earthquakes, insurance can be purchased. Therefore, in this study, earthquake insurance premiums will be determined by taking into account the probability of an earthquake occurring and the ratio of damage to buildings in Kepahiang Regency. The PSHA (Probabilistic Seismic Hazard Analysis) method is used to determine the probability of an earthquake occurring. In the PSHA process, earthquake data will be collected and analyzed to identify earthquake sources, characterize earthquake sources, and calculate earthquake hazard (the probability of an earthquake). Damage data on buildings will be processed to obtain a ratio of building damage. After that, a pure premium will be obtained, by multiplying the EADR (Expected Annual Damage Ratio) value with the sum insured of the building, where EADR is the estimated level of annual damage due to earthquakes in an area

ESTIMASI CADANGAN KLAIM MENGGUNAKAN METODE KALMAN FILTER DENGAN STATE SPACE MODEL SCALAR PADA PRODUK ASURANSI UMUM Manurung, Chintya Carissa; Yulita, Tiara; Listiani, Amalia
KUBIK Vol 9, No 2 (2024): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar

Usually, there is a delay in reporting claims from the time of the incident which results in the insurance company having a responsibility or debt. Therefore, insurance companies need to prepare funds to cover these debts, namely with claims reserves. There are two types of claim reserves, namely Incurred But Not Reported (IBNR) and Reported But Not Settled (RBNS). This research focuses on determining the estimation of aggregate claim reserves using the Kalman Filter method with scalar State Space Models (SSMs) which is a model resulting from the development of the Chain Ladder (CL) method. The Kalman Filter method with SSMs is a stochastic method that takes into account the time series model so that it can predict the temporal dynamics of a system more accurately. The results of forecasting claim reserves using the Kalman Filter method with SSMs will be compared with the CL method. Variational Of Coefficient (VOC) is an error predictor to determine the best method. The calculation results using the Kalman Filter method with SSMs produce a smaller VOC value than the CL method, proving that the Kalman Filter method with SSMs is better than CL.

Pelatihan Pengolahan dan Analisa Data Statistik Untuk Meningkatkan Kompetensi Guru SMPN di Kalianda, Lampung Selatan Andirasdini, Indah Gumala; Sofia, Ayu; Lestari, Fuji; Listiani, Amalia; Yulita, Tiara; Julianty, Dila Tirta; Rivai, Muklas
TeknoKreatif: Jurnal Pengabdian kepada Masyarakat Vol 4 No 2 (2024): TEKNOKREATIF : Jurnal Pengabdian kepada Masyarakat Volume 4 No 2
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LP2M), Institut Teknologi Sumatera, Lampung, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35472/teknokreatif.v4i2.1875

Salah satu wujud pengembangan diri seorang guru adalah dengan melakukan dan menulis laporan penelitian. Penelitian dan penulisan laporan hasil penelitian terkait kinerja pembelajaran seorang guru merupakan salah satu upaya evaluasi (refleksi) terhadap kinerja seorang guru di dalam kelas. Evaluasi ini dilakukan dengan melaksanakan Penelitian Tindakan Kelas (PTK). Permasalahan yang terjadi pada PTK adalah kurangnya kompetensi guru dalam melakukan pengolahan data, menggunakan tools, dan menerapkan model-model statistika yang cocok untuk kasus-kasus yang terjadi di kelas. Pada jurnal ini membahas peningkatan kompetensi guru-guru SMPN melalui pelatihan olah data dan analisis data statistik menggunakan JASP. Tingkat pemahaman dan kompetensi guru diukur menggunakan kuesioner yang diberikan pada sebelum dan setelah melakukan pelatihan. Pelatihan ini memberikan perubahan tingkat pemahaman dan kompetensi yang signifikan berdasarkan bidang kompetensi yang ditanyakan. Hal ini dapat dilihat dari gap responden yang diperoleh saat sebelum pelatihan dan setelah pelatihan dilakukan.

Perhitungan Cadangan Premi Asuransi Jiwa Berjangka dengan Menggunakan Metode Zillmer dan Fackler Sitorus, Kristiani; Yulita, Tiara; Lestari, Fuji
Indonesian Journal of Applied Mathematics Vol. 4 No. 2 (2024): Indonesian Journal of Applied Mathematics Vol. 4 No. 2 October Chapter
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM), Institut Teknologi Sumatera, Lampung Selatan, Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35472/indojam.v4i2.1944

Human life is never free from risk. Along with the development of the era, humans began to realize the importance of protecting themselves in the event of a risk, including the risk of death. To overcome this, many individuals transfer the risk by registering themselves or their families with life insurance. The life insurance that is focused on is term life insurance, which is a form of protection with a certain period of time that has been set. In order to run its operations properly, insurance companies need to prepare premium reserves with accurate calculations. These calculations can be done through two actuarial methods, namely prospective and retrospective methods. This study uses the Zillmer method (prospective) and the Fackler method (retrospective) for calculating premium reserves. The purpose of this study was to determine the analysis of the results of calculating the premium reserve value from the two methods. The premium reserve values calculated using the Zillmer and Fackler methods were different. At an interest rate of 6.25%, the Fackler method produces a higher premium reserve compared to the Zillmer method. This difference is because the Zillmer method includes other costs such as acquisition costs, administration, and agent commissions in calculating premium reserves. In contrast, the Fackler method does not take these costs into account in its calculations.

ESTIMASI CADANGAN KLAIM MENGGUNAKAN METODE KALMAN FILTER DENGAN STATE SPACE MODEL SCALAR PADA PRODUK ASURANSI UMUM Manurung, Chintya Carissa; Yulita, Tiara; Listiani, Amalia
KUBIK Vol 9, No 2 (2024): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar

Usually, there is a delay in reporting claims from the time of the incident which results in the insurance company having a responsibility or debt. Therefore, insurance companies need to prepare funds to cover these debts, namely with claims reserves. There are two types of claim reserves, namely Incurred But Not Reported (IBNR) and Reported But Not Settled (RBNS). This research focuses on determining the estimation of aggregate claim reserves using the Kalman Filter method with scalar State Space Models (SSMs) which is a model resulting from the development of the Chain Ladder (CL) method. The Kalman Filter method with SSMs is a stochastic method that takes into account the time series model so that it can predict the temporal dynamics of a system more accurately. The results of forecasting claim reserves using the Kalman Filter method with SSMs will be compared with the CL method. Variational Of Coefficient (VOC) is an error predictor to determine the best method. The calculation results using the Kalman Filter method with SSMs produce a smaller VOC value than the CL method, proving that the Kalman Filter method with SSMs is better than CL.

Literasi Pemanfaatan Software JASP Untuk Meningkatkan Keterampilan Statistik Guru di MAN 1 Bandar Lampung Andirasdini, Indah Gumala; Sofia, Ayu; Rivai, Muklas; Mahrani, Dwi; Yulita, Tiara; Irwan, Sri Efrinita; Berliana Ratam, Aldila Nur Indah; Gustina K.S., Annisa Hevita; Dewi, Karina Sylfia; Marisa, Marisa; Azzanina, Nanda; Baiti, Putri Isnaini Cahyaning; Rosni, Rosni
RENATA: Jurnal Pengabdian Masyarakat Kita Semua Vol. 3 No. 1 (2025): Renata - April 2025
Publisher : PT Berkah Tematik Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61124/1.renata.147

Guru sebagai agen perubahan memiliki peran strategis dalam mengembangkan literasi digital di lingkungan kerja. Salah satu aspek penting dalam literasi digital adalah kemampuan dalam memanfaatkan teknologi dan aplikasi digital untuk mendukung proses pembelajaran dan pengolahan data. Pemanfaatan software JASP (Jeffreys's Amazing Statistics Program) menjadi salah satu cara efektif bagi guru untuk meningkatkan keterampilan statistik seperti mengolah dan menganalisis data. Dengan memanfaatkan JASP, guru dapat melakukan analisis statistik secara intuitif dan efisien, sehingga memudahkan dalam mengajarkan konsep-konsep statistik kepada siswa. Pengabdian dalam bentuk literasi pemanfaatan software JASP ini didasari oleh kebutuhan mendesak akan kemampuan memahami analisis data yang efektif di kalangan pendidik, mengingat pentingnya pengolahan data dalam proses pembelajaran dan evaluasi. Metode yang digunakan dalam pengabdian ini meliputi pelatihan intensif dan workshop yang dirancang untuk memperkenalkan fitur-fitur utama JASP, termasuk analisis statistik dasar hingga lanjutan. Peserta diberikan kesempatan untuk langsung mempraktikkan penggunaan software sehingga diharapkan dapat meningkatkan pemahaman dan keterampilan. Hasil dari kegiatan ini menunjukkan peningkatan kemampuan guru yang signifikan dalam mengolah dan menganalisis data. Hal ini ditunjukkan dari hasil pre-test dan post-test yang dilakukan sebelum dan sesudah kegiatan. Kegiatan pengabdian ini tidak hanya memberikan pengetahuan baru, tetapi juga membangun kepercayaan diri para guru dalam menggunakan teknologi untuk mendukung pengajaran. Kesimpulan dari pengabdian ini menekankan pentingnya pelatihan berkelanjutan dalam literasi data untuk meningkatkan kualitas pendidikan

Penentuan Premi Menggunakan Metode Limited Fluctuation Credibility Pada Produk Health Insurance Reasuransi Di Indonesia Yulita, Tiara; Agus Sofian Eka Hidayat; Gilang Primajati
Griya Journal of Mathematics Education and Application Vol. 5 No. 2 (2025): Juni 2025
Publisher : Pendidikan Matematika FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/griya.v5i2.604

A reinsurance company is a company that provides reinsurance services against the risks faced by the insurance company (the insured). An insured is obliged to pay an amount of money in accordance with the agreement as a form of obligation from the insured for his participation in reinsurance which is called a premium. One method that can be used to determine future premiums based on past experience is limited fluctuation credibility which can predict the value of pure premiums in the future based on current data and insurance manual rates. Using the help of the limited fluctuation credibility method, this study will calculate the estimated value of claim frequency, claim size, aggregate losses and pure health insurance premiums using reinsurance claim experience data. The results of these calculations will be analyzed for differences in value with the value given by reinsurance companies in Indonesia. With this research it is hoped that it can become a standard reference for the credibility of reinsurance companies in determining premiums in the future.

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