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All Journal Journal of Science and Applicative Technology Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Kalbiscientia Jurnal Sains dan Teknologi Journal of Science and Technology Journal of Fundamental Mathematics and Applications (JFMA) Jurnal Matematika Integratif Indonesian Journal of Applied Mathematics TeknoKreatif: Jurnal Pengabdian kepada Masyarakat
Fuji Lestari
Institut Teknologi Sumatera
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Transportation Other

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Prediksi Finansial Distress pada Salah Satu Bank Konvensional Menggunakan Machine Learning Fuji Lestari
Indonesian Journal of Applied Mathematics Vol 3 No 1 (2023): Indonesian Journal of Applied Mathematics Vol. 3 No. 1 July 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.v3i1.1284

Abstract

Financial distress is when a company experiences a shortage or insufficient funds to run the company. Prediction of financial distress is needed to prevent bankruptcy. In this study, financial distress predictions were made based on financial ratios obtained from monthly financial reports from a bank convention, after which the proportion that had the most influence on financial distress was determined. The models used in this study are several machine learning models, namely, Logistic Regression, Support Vector Machine, and Random Forest. Based on the analysis results, the best model for predicting financial pressure is the Random Forest Model, with an accuracy of 96.77%. Based on the best model obtained, namely the Random Forest, it can be determined that the ratio that is very influential on financial distress is the ratio of Total Asset Turnover.
Perbandingan Estimasi Premi Asuransi Jiwa Joint Life dengan Menggunakan Asumsi Kebebasan Mortalita dan Metode Copula Fuji Lestari; Azizah Dzakiya
Jurnal Matematika Integratif Vol 19, No 2: Oktober 2023
Publisher : Department of Matematics, Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jmi.v19.n2.49447.201-212

Abstract

Setiap perseorangan pasti mempunyai risiko yang ditanggungnya, baik itu risiko yang ditanggung pada masa kini ataupun masa depan. Risiko kematian adalah risiko yang pasti akan terjadi bagi perseorangan. Oleh karena itu, dibutuhkan salah satu jenis perlindungan agar bisa mengatasi risiko kematian. Salah satu jenis perlindungan yang biasa digunakan adalah mengikuti asuransi jiwa. Asuransi jiwa yang umumnya diikuti oleh pasangan suami istri adalah asuransi jiwa joint life. Pemegang polis dari asuransi tersebut umumnya adalah pasangan suami dan istri. Penelitian ini membandingkan estimasi premi asuransi jiwa joint life dengan menggunakan asumsi kebebasan mortalita dan metode copula Archimedean. Data penelitian ini menggunakan data Tabel Mortalitas Badan Penyelenggara Jaminan Sosial (BPJS) tahun 2022 dengan berbagai asumsi, yaitu asumsi usia pasangan suami istri, jangka waktu jenis asuransi, dan suku bunga yang dipakai sebesar 6\% per tahun. Premi yang dihitung menggunakan asumsi risiko kematian tidak saling bebas menggunakan metode copula clayton lebih rendah dibandingkan dengan menggunakan asumsi kebebasan mortalita, copula Frank, dan copula Gumbel. Selain itu, perbedaan umur antara suami dan istri juga mempengaruhi besarnya nilai premi. Semakin besar perbedaan umur dari suami dan istri, maka semakin besar pula nilai premi yang dibayarkan pertahun.
Recognition of Voronoi Cell Distribution in Earthquake Epicenter Data in the Sunda Strait Region, Indonesia Muliawati, Triyana; Lestari, Fuji; Harbowo, Danni Gathot; S, Mika Alvionita
JOSTECH Journal of Science and Technology Vol 4, No 2: September 2024
Publisher : UIN Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/jostech.v4i2.9830

Abstract

The Sunda Strait is currently one of the busiest transportation hubs. However, this area has a significant history of geological disasters caused by the dynamic tectonic activity of the Eurasian and Indo-Australian tectonic plates. These disasters include the supervolcanic eruption of Krakatoa in 1883, the Sunda Strait tsunami in 2018, and decades of frequent earthquakes. To address these challenges, this study analyzes the frequency and distribution of seismic activity in the Sunda Strait region based on epicenter data recorded in the United States Geological Survey (USGS) Earthquake Catalog. We collected 440 multivariate earthquake data points between 1990 and 2023 (over three decades). The results of this study show that a machine learning approach accurately identified four relevant parameters for k-means clustering, followed by a silhouette value analysis to recognize the distribution of Voronoi cells. Based on earthquake data from the Sunda Strait from 1990 to 2023, the two highest silhouette analysis values, 0.40 and 0.39, are located at k=3 and k=5 in k-means clustering. This approach has recognized and identified the cell area of earthquake activity in the Sunda Strait, particularly around Anak Krakatoa. This study provides new insights into the spatiotemporal characteristics and identifies clusters of earthquake-prone areas. The information generated in this study facilitates the evaluation of future earthquake disaster risks, especially those with epicenters in the Sunda Strait region.
PENERAPAN MODEL RANTAI MARKOV DALAM PERHITUNGAN PREMI ASURANSI LONG TERM CARE UNTUK PENYAKIT JANTUNG DI PULAU SUMATERA Lestari, Fuji; Sumarna, Nur Alvyanti
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 3 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i3.750

Abstract

Health insurance is insurance that provides health benefits in the form of cash compensation for medical and treatment costs. One of the health insurance products is Long Term Care (LTC) insurance. Long Term Care insurance provides compensation for the insured who requires medical care or for those suffering from chronic illnesses or physical disabilities that cannot be covered by other insurance. This study discusses the calculation of premiums for heart disease, including hypertension and diabetes, for the LTC insurance product Annuity as a Rider Benefit using a multi-state model application from the Markov Chain model. The multi-state model used includes healthy, sick, and deceased states, with the assumption that there is no transition from sick to healthy. The premium calculation is based on the Markov chain with a transition probability matrix using heart disease prevalence data in Sumatra Island in 2018. The case study in this research includes males and females aged 25, 35, and 45 years, with premium payment periods of 5, 10, and 15 years. The death benefit is IDR 500,000,000.00, the care benefit is IDR 100,000,000.00, and the interest rate is 6.25%. Based on age, the calculation of the annual net premium for Long Term Care insurance, the Annuity as a Rider Benefit product for heart disease in Sumatra Island, shows that men generally have higher premiums compared to women, with a range of 0.9598 to 1.0028 times. Meanwhile, based on the premium payment period, men also have higher premiums than women.
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

Abstract

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.
Recognizing the Spatial Distribution and Voronoi Patterns of the Recorded Earthquake Epicenters in Sunda Strait, Indonesia Muliawati, Triyana; Lestari, Fuji; Alvionita, Mika; Satria, Ardika; Harbowo, DG
Journal of Fundamental Mathematics and Applications (JFMA) Vol 7, No 2 (2024)
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jfma.v7i2.21931

Abstract

Currently, Sunda Strait is one of the most active transportation hubs. However, this region also bears a notable history of geohazards associated with the dynamics of tectonic activity of the Eurasian and Indo-Australian tectonic plates, such as the super-eruption of Krakatoa volcano in 1883, the Sunda Strait tsunami in 2018, and decades of frequent earthquakes. To address these challenges, this study conducted a statistical analysis of the frequency and distribution of seismic activities in the Sunda Strait region based on recorded epicenter data in the United States Geological Survey's (USGS) Earthquake catalog. We assembled 440 multivariate earthquake data points between 1990 and 2023 (over three decades). The results of this study indicate that the machine learning approach precisely identifies four relevant parameters for -means clustering, followed by an analysis of silhouette values to recognize Voronoi patterns. These statistical patterns also have significant implications for the number of epicenter clusters and recognizing their spatial distribution. It provides a new understanding of the spatial-temporal characteristics and locates the list of frequent earthquake regions. Having all the necessary information would help to comprehensively evaluate geohazard risks in Sunda Strait region.
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

Abstract

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.
Perhitungan Cadangan Premi Asuransi Jiwa Dwiguna Menggunakan Metode Premium Sufficiency dengan Asumsi Usia Pecahan Rafli Ramadhan; Fuji Lestari
KALBISCIENTIA Jurnal Sains dan Teknologi Vol. 12 No. 01 (2025): Jurnal Sains dan Teknologi
Publisher : Research and Community Service UNIVERSITAS KALBIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53008/kalbiscientia.v12i01.4522

Abstract

Risk is a part of human life that can cause financial losses, so insurance is needed to deal with these risks. Insurance is an agreement between an insurance company and a policyholder, with the company required to provide compensation for financial losses experienced by the policyholder. As an imbalance, the policyholder needs to pay a certain amount of premium. This study aims to analyze the calculation of premium reserves using the Premium Sufficiency method with the assumption of fractional age. The Premium Sufficiency method is one of the prospective premium reserve calculations using gross premiums. In reality, insurance participants do not always register at an integer age, but at a fractional age, so a fractional age assumption is needed. The results of the premium reserve calculation using Premium Sufficiency for the fractional age assumption increase every year, with the premium reserve value at the end of the insurance period increasing the same as the amount of insurance. In addition, the difference in the premium reserve value between the case of a premium payment period of 5 years and 10 years in the first year for the fractional age assumption is Rp 21,498,124,302.
PERHITUNGAN PREMI ASURANSI PERTANIAN BERDASARKAN INDEKS IKLIM CURAH HUJAN DENGAN MENGGUNAKAN METODE BLACK-SCHOLES DI PROVINSI LAMPUNG Vikarti, Maulida Magdalena; Lestari, Fuji
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 6 No. 1 (2025): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v6i1.956

Abstract

Agriculture plays an important role in national economic development, but has the highest risk of loss due to its dependence on climatic conditions. One of the efforts to reduce the risk of crop failure is through an agricultural insurance program. The agricultural insurance used in this study is rainfall climate index-based agricultural insurance. This study aims to analyze the value of the rainfall climate index to be used and analyze the calculation of agricultural insurance premiums based on the rainfall climate index. The method used to determine the rainfall climate index is the Historical Burn Analysis method and the method used to calculate agricultural insurance premiums is the Black-Scholes method. The results showed variations in trigger and exit values at each BMKG station, with North Lampung Geophysical Station having the highest trigger and exit of 36,87 mm and 49,64 mm, while the highest premium was recorded at Panjang Maritime Meteorological Station at Rp 3.025.887,38. This is due to the risk of extreme events below the trigger value occurring more frequently
Statistical Pattern Recognition of Lithosphere Anomalous Activity Along the Indonesian Ring of Fire S, Mika Alvionita; Satria, Ardika; Muliawati, Triyana; Lestari, Fuji; Harbowo, Danni Gathot
Journal of Science and Applicative Technology Vol. 9 No. 1 (2025): Journal of Science and Applicative Technology June 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/jsat.v9i1.1850

Abstract

The introduction of statistical pattern recognition becomes highly important for assessing disaster threats such as earthquakes. This approach is significantly more comprehensive and suitable for long-term event forecasting. Therefore, in the future, efforts can be promptly made to reduce the risk of disasters resulting from anomalies in lithospheric activity, especially frequent earthquakes in the Sumatra Island region, Indonesia. Statistical pattern analysis of lithospheric activity anomalies can be categorized through classification. Earthquake classification is performed based on magnitude scale and mathematical calculations of earthquake parameter unit conversion. The classification method employed in this research includes machine learning methods like k-nearest neighbor and support vector machine. The evaluation metrics used for machine learning models are model accuracy and confusion matrix tables.
Co-Authors Andirasdini, Indah Gumala Azizah Dzakiya Danni Gathot Harbowo Dila Tirta Julianty Haninda Bharata Listiani, Amalia Mika Alvionita Sitinjak Muliawati Muliawati, Triyana Rafli Ramadhan Rini Asnawati Rivai, Muklas Satria, Ardika Sitorus, Kristiani Sofia, Ayu Sumarna, Nur Alvyanti Vikarti, Maulida Magdalena Yulita, Tiara