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All Journal Jurnal Matematika BIMASTER Epsilon: Jurnal Matematika Murni dan Terapan CESS (Journal of Computer Engineering, System and Science) Indonesian Journal of Applied Statistics BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) KABILAH : Journal of Social Community Jurnal Pendidikan Sejarah dan Riset Sosial Humaniora (KAGANGA) BULETIN AL-RIBAATH Jambura Journal of Mathematics GERVASI: Jurnal Pengabdian kepada Masyarakat Sarwahita : Jurnal Pengabdian Kepada Masyarakat M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika Transformasi : Jurnal Pendidikan Matematika dan Matematika Variance : Journal of Statistics and Its Applications International Journal of Economics, Business and Accounting Research (IJEBAR) Insan Cita Jurnal Pengabdian Kepada Masyarakat Jurnal Pendidikan Dasar Perkhasa Jurnal Pengabdian kepada Masyarakat Nusantara Journal of Mathematics Education and Science AR-RIAYAH : Jurnal Pendidikan Dasar Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi CENDEKIA : Jurnal Ilmu Pengetahuan Journal of Community Development Empiricism Journal Jurnal Eurekamatika Jurnal Forum Analisis Statistik Pattimura International Journal of Mathematics (PIJMath) STATISTIKA Bina Bahari : Jurnal Pengabdian Kepada Masyarakat Equiva Jurnal Pengabdian pada Masyarakat
Neva Satyahadewi
Program Studi Statistika Fakultas MIPA Universitas Tanjungpura, Indonesia
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FORECASTING THE COMBINED STOCK PRICE INDEX (IHSG) USING THE RADIAL BASIS FUNCTION NEURAL NETWORK METHOD Fitriawan, Della; Satyahadewi, Neva; Andani, Wirda
VARIANCE: Journal of Statistics and Its Applications Vol 7 No 1 (2025): 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/variancevol7iss1page83-92

Abstract

The capital market is one of the most critical factors in national economic development in Indonesia, as many industries and companies have previously used the capital market as a medium to absorb investment so that their financial position can be strengthened. The main indicator that can reflect the performance of the capital market is the Composite Stock Price Index (IHSG). The IHSG can be used to assess the general situation occurring in the market. Data IHSG is data obtained from the past and used to predict the future, also called time series data. Predictions on IHSG data need to be made so that investors can easily see capital market movements and know the policies that will be taken in the future. The Radial Basis Function Neural Network (RBFNN) method is used. RBFNN aims to get more efficient results because this method does not need to make the data stationary. The analysis results were carried out on a secondary data sample size of 1114 data, which obtained the highest forecasting price of Rp6157,619 on August 2, 2023. Meanwhile, the lowest forecast price on August 5, 2023, is IDR 5564,828 from August 1, 2023, to August 5, 2023.
SOSIALISASI DAN PENDAMPINGAN MASYARAKAT DALAM MEMAJUKAN EKOWISATA PANTAI BATU BURUNG KOTA SINGKAWANG KALIMANTAN BARAT Satyahadewi, Neva
Bina Bahari Vol 2, No 1 (2023): FEBRUARI 2023
Publisher : Program Studi Ilmu Kelautan, FMIPA Universitas Tanjungp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/binabahari.v2i1.28

Abstract

Pantai Batu Burung Singkawang is one of the tourist destinations that is visited by local tourists from the Singkawang and surrounding areas, especially on Sundays and school holidays or Eid holidays. With the characteristic distribution of granite along the coast, it adds to the natural beauty of the beach. The Community Service Activities (PKM) which are carried out in September-November in the area aim to advance Pantai Batu Burung tourism through assisting the local community in terms of maintaining the cleanliness of the beach including the tidiness and order of the street vendors, being friendly to visitors and promoting the beauty of ecotourism Pantai Batu Burung through social media. This activity was attended by 20 residents of the Sedau Village community, 15 of whom were culinary business owners in the coastal area. Based on the evaluation and monitoring during the activity, it shows that the business community on this beach has carried out a beach cleaning program regularly so that the beach and its surroundings always look clean, always maintain hospitality to visitors and have participated in promoting the Pantai Batu Burung tourist destination through social media with share beach profile videos and infographics.Keywords : Pantai Batu Burung, ecotourism, granite, infographics, Sedau
Perbandingan Kinerja Algoritma K-Means dan K-Medoids Pada Pengelompokan Usaha Pertanian Perorangan Tanaman Pangan di Provinsi Kalimantan Barat Margareta, Tiara; Satyahadewi, Neva; Pertiwi, Retno
Jurnal Forum Analisis Statistik Vol. 5 No. 1 (2025): Jurnal Forum Analisis Statistik (FORMASI)
Publisher : Badan Pusat Statistik Provinsi Kalimantan Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57059/formasi.v5i1.91

Abstract

Kalimantan Barat province as the third largest province in Indonesia, has diverse and promising potential, especially in agriculture. It is known based on the result of the 2023 Agricultural Census, 354.503 people in Kalimantan Barat are food crop subsector agricultural business (contributing 48,58 percent of the total individual agricultural holdings). It is necessary to classify the commodity of food crop to identify the potential commodities in each regencies/cities. The method used in this analysis are the K-Means and K-Medoids algorithms. The use of both methods aims to compare and determine the most suitable algorithm for this analysis. The data used is sourced from the result of the complete enumeration of the 2023 agricultural census with the variable is the number of individual agricultural holdings of food crop commodities (rice and secondary food crops). The purpose of this study is to classify the number of food crop agricultural holdings in Kalimantan Barat Province by regency/municipality. The analysis results showed that K-Means was the best algorithm used for this data, with a DBI of 0,637. Smaller than the K-Medoids algorithm, which had a DBI of 0,683. The result of the K-Means analysis identified four clusters of food crop commodity areas. The first cluster consist of five regencies/municipalities, the second cluster contains one, the third cluster includes six, the fourth cluster comprise two regencies/municipalities.
MULTI-STATE MODEL FOR CALCULATION OF LONG-TERM CARE INSURANCE PRODUCT PREMIUM IN INDONESIA Perdana, Hendra; Satyahadewi, Neva; Kusnandar, Dadan; Tamtama, Ray
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 4 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (487.771 KB) | DOI: 10.30598/barekengvol16iss4pp1293-1302

Abstract

Long Term Care (LTC) insurance is a type of health insurance. One of the LTC products is Annuity as A Rider Benefit. This insurance provides benefits for medical care costs during the term and death benefits if the insured dies. This insurance product can be modeled with a multi-state model. The multi-state model is a stochastic process in which the subject can switch states at a specified number of states. This paper discusses the calculation of LTC insurance premiums with the Annuity as A Rider Benefit product using a multi-state model for critically ill patients in Indonesia. The state used consisted of eight states, namely healthy, cancer, heart disease, stroke, died from the illness from each disease, and died from others. The premium calculation also utilized Markov chain transition probabilities. The data used were data on Indonesia's population in 2018, data on the prevalence of cancer, heart disease, stroke, and Indonesia's 2019 mortality table. The stages of this study were calculating the net single premium value, benefit annuity value, and insurance premium value. The case study was conducted on a 25 years old male in good health following LTC insurance with a coverage period of 5 years. It was known that the compensation value for someone who dies was IDR 100,000,000 and the interest rate used was 5%. The calculation results obtained an annual premium of IDR 5,308,915 which was then varied based on gender and varied interest. Insurance premiums for men were more expensive than for women since men had a greater chance of dying. Then, the higher the interest rate taken; the lower premium paid. This was because the interest rate is a discount variable.
APPLICATION OF THE BLACK SCHOLES METHOD FOR COUNTING AGRICULTURAL INSURANCE PREMIUM PRICE BASED ON RAINFALL INDEX IN KAPUAS HULU REGENCY Marola, Geby; Satyahadewi, Neva; Andani, Wirda
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0819-0826

Abstract

High-intensity rainfall is one of the factors that can interfere with the state of agriculture. Agricultural insurance is an insurance that can be used to reduce risks related to agricultural losses such as rice production. Climate-based agricultural insurance is a management of climate-related risks. This study aims to determine the rainfall index and calculate the value of agricultural insurance premiums based on the climate index (rainfall) in Kapuas Hulu Regency using the Black Scholes method. In calculating the value of agricultural insurance premiums based on the rainfall index, it starts by calculating the value of the correlation coefficient between rainfall and rice production. Then the value of the rainfall index is obtained, which then the value of the index is tested for lognormality to meet the assumptions on the Black Scholes method, after which it calculates the ln return value of the index value obtained, the last step is to calculate the value of agricultural insurance premiums. Based on case studies, the results obtained are when the risk-free interest rate is 3.5% and rainfall is 54.23 mm the premium paid is Rp 2,386,824 and when the rainfall is 75.39 mm the premium paid is Rp 3,898,142. If the risk-free interest rate is 4% and the bulk is 54.23 mm, the premium paid is IDR 2,383,842, and when the rainfall is 75.39 mm the premium paid is IDR 3,893,272. When the risk-free interest rate is 5% and rainfall is 54.23 mm the premium paid is Rp 2,377,890 and if the rainfall is 75.39 mm the premium paid is Rp 3,883,551. So, the higher the rainfall, the greater the premium value payment. If the risk-free interest rate gets bigger then the premium payment will be smaller.
PREMIUMS CALCULATION OF TERMINAL ILLNESS INSURANCE Satyahadewi, Neva; Retnani, Hani Dwi; Perdana, Hendra; Tamtama, Ray; Aprizkiyandari, Siti
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0913-0918

Abstract

One related type of critical illness insurance is Long Term Care (LTC) Insurance. This study discusses the calculation of LTC insurance premiums with an annuity as a rider benefit. The benefit is included the cost of insurance care when diagnosed with a critical illness with a terminal condition or death because of any reason. The types of critical illnesses used in this study are cancer, heart disease, stroke, and diabetes mellitus. The data used are in the form of Indonesia's mortality table, and data on the prevalence of critical illness patients with terminal illness conditions. The net annual premium value in this study was obtained through the results of the multiple-state model determination of the transition probabilities of 10 states. The transition probability of an insured candidate is obtained from the prevalence of critical illness patients and the prevalence of mortality. Based on the case study, the amount of net annual premium that must be paid by an insured female aged years in good health is for the protection period and the payment period is years. The cost of insurance premiums for the male insured is greater than for the female insured. The higher the interest rate used, the smaller the net single premium that must be paid. The younger the age when registering the policy, the smaller the premium that must be paid. The longer the coverage period, the greater the premium that must be paid. This result is expected to be a recommendation for the prospective insured to adjust the suitable premium.
NET SINGLE PREMIUM ON CRITICAL ILLNESS INSURANCE WITH MULTI-STATE MODEL Taraly, Inggriani Millennia; Satyahadewi, Neva; Perdana, Hendra; Tamtama, Ray; Aprizkiyandari, Siti
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0989-0994

Abstract

The chances of someone getting a disease or suffering from a critical illness are very large, especially when they get older, the chances of getting a critical illness will be higher. A guarantee of the future is indispensable if a person suffers from a critical illness at any time and requires considerable costs to undergo treatment. Insurance is one of the right choices and is beneficial for people with critical illnesses. In this study, the calculation of Critical Illness insurance premiums was carried out to determine the value of premiums that must be paid by a person when suffering from a critical illness. The types of critical illnesses used include cancer, heart disease, stroke, kidney failure, diabetes mellitus, and hypertension. Health insurance that protects insureds suffering from critical illnesses is Long Term Care insurance with the Annuity as A Rider Benefit product. The multi-state model is used to determine the probability of a person suffering from a critical illness. The benefits obtained are in the form of death compensation, and treatment costs when the insured is diagnosed with a critical illness. The data used are data on the prevalence of critical illnesses and the percentage of deaths due to critical illnesses. In this study, we will compare the amount of premium that must be paid by the insured with different interest rates, gender, coverage period, and age. The higher the age at the beginning of following the insurance, the higher the premium. The higher the interest rate during the payer's period, the lower the premium.
APPLICATION OF EXTREME LEARNING MACHINE METHOD ON STOCK CLOSING PRICE FORECASTING PT ANEKA TAMBANG (PERSERO) TBK Apriliyanti, Rita; Satyahadewi, Neva; Andani, Wirda
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp1057-1068

Abstract

Artificial neural networks are modeling methods that can capture complex input and output relationships. This method is widely used in forecasting and classification. However, in its application, there are some disadvantages in terms of low learning rate resulting in computational delay. Extreme Learning Machine (ELM) was introduced to overcome these problems. This method is believed to be able to produce more accurate forecasting results with a low level of forecasting error. In Indonesia, stocks are one of the most popular investments for investors. Stock prices tend to be volatile which is influenced by the amount of market supply and demand, so forecasting analysis is needed to minimize the risks that may occur. This research applies the ELM method to forecast the closing price of PT ANTM Tbk shares from January 1, 2018 - October 31, 2022. The data used is secondary data obtained from the official website https://id.investing.com. The ELM method is applied by dividing training data for ELM modeling and testing data used in the forecasting process. The model architecture of the ELM method uses a combination of inputs obtained from the PACF plot, hidden nodes with a range of 5-50, and one output layer. The results of this study show excellent forecasting accuracy in terms of forecasting. This is measured by the MAPE value of 0.0358. The architecture formed in the ELM process is one input, 31 hidden nodes, and one output. Forecasting the closing price of PT ANTM Tbk shares with 1-31-1 architecture produces a forecasting value that shows a low decline, but is quite stable.
HIERARCHICAL CLUSTER ANALYSIS OF DISTRICTS/CITIES IN NORTH SUMATRA PROVINCE BASED ON HUMAN DEVELOPMENT INDEX INDICATORS USING PSEUDO-F Satyahadewi, Neva; Sinaga, Steven Jansen; Perdana, Hendra
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1429-1438

Abstract

Human development is needed to create prosperity and assist development in a country. In realising this, it is necessary to first look at the quality of human resources in the country, so that its use is more targeted. The measure used as a standard for the success of human development in a country is the Human Development Index (HDI). HDI figure are calculated from the aggregation of three dimensions, namely longevity and healthy living, knowledge, and decent standard of living. The longevity and healthy living dimension is represented by the Life Expectancy. Average Years of Schooling (AYS) and Expected Years of Schooling (EYS) are indicators representing the knowledge dimension. Meanwhile, the decent standard of living dimension is represented by the Expenditure per Capita indicator. The purpose of this study is to explain the characteristics of each cluster obtained from Hierarchical Cluster Analysis of districts/cities in North Sumatra Province based on HDI indicators in 2022 using Pseudo-F. The methods used are Hierarchical Cluster Analysis and Calinski-Harabasz Pseudo-F Statistic. The main concept of this method is to determine the optimum number of groups. This research uses secondary data obtained from BPS. The sample size in this study are 33 districts/cities and the number of variables are 4 variables. The results of the analysis of this study are the formation of 4 clusters with the best method is Ward. Cluster 1 consists of four members, namely Medan City, Pematang Siantar City, Binjai City, and Padang Sidempuan City, where this cluster has a very high HDI level. Meanwhile, Cluster 4 is a cluster that has a very low HDI level with four cluster members, namely Nias District, South Nias District, North Nias District, and West Nias District. Thus, it can be seen that there is a gap between regions in North Sumatra Province.
VALUE AT RISK ANALYSIS ON BLUE CHIP STOCKS PORTFOLIO WITH GAUSSIAN COPULA Ardhitha, Tiffany; Sulistianingsih, Evy; Satyahadewi, Neva
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1739-1748

Abstract

Value at Risk (VaR) is a risk measurement tool to calculate the estimated maximum investment loss with a certain confidence level and period. VaR calculations using financial data are often not normally distributed, so the copula method is used, which is flexible on the assumption of normality on stock return data. Previous research discussed Gaussian copula using stocks from the telecommunications sector. In this research, using Gaussian copula on Blue Chip stocks. Blue Chip stocks have a good reputation and have a stable growth rate so they have a lower risk. Therefore, the research objective is to analyze the VaR portfolio of Blue Chip stock with Gaussian copula. This research uses the daily stock closing prices of BBNI and BBTN from November 2, 2020 to October 27, 2022. The analysis results suggested that a VaR portfolio using Gaussian copula with a confidence level of 90%, 95%, and 99%, respectively are 2.24%, 2.88%, and 4.02%. The value shows the percentage of investment risk that may be obtained in the next one-day period. This result also indicates that the higher the confidence level, the greater the VaR.
Co-Authors . Apriansyah Aditya Handayani Afghani Jayuska Afghany Jayuska Alvin Octavianus Halim Amriani Amir Amriani Amir Amriani Amir Andani, Wirda Annisa Auliarahmi Antoni, Frans Xavier Natalius Apriliyanti, Rita Aprizkiyandari, Siti Ardhitha, Tiffany Ari Hepi Yanti Arsyi, Fritzgerald Muhammad Arti, Reyana Hilda Ashari, Asri Mulya Asri Mulya Ashari Asty Fistia Ningrum Atikasari, Awang Aulia Puteri Amari Bambang Kurniadi Banu, Syarifah Syahr ciptadi, wahyudin Citra Cipta Maharani Cornellia, Amanda Dadan Kusnandar Dadan Kusnandar Dadan Kusnandar David Jordy Dhandio Debataraja, Naomi Nessyana Della Zaria Desriani Lestari Desriani Lestari Desriani Lestari Dhandio, David Jordy Dinda Lestari Dwi Nining Indrasari Dwinanda, Maria Welita Eka Febrianti, Eka Esta Br Tarigan Evy Sulistianingsih Ewaldus Okta Febrant Alfariz Ferdina Ferdina Feriliani Maria Nani Fitriawan, Della Fransisca Febrianti Sundari Fransiska Fransiska Grikus Romi Gusti Eva Tavita Gusti Eva Tavita Hairil Al-Ham Hamzah, Erwin Rizal Hanin, Noerul Harimurti, Puspito Harnanta, Nabila Izza Helena, Shifa Hendra Perdana Hendrianto, El Herina Marlisa Huda, Nur'ainul Miftahul Huriyah, Syifa Khansa Ibnur Rusi Ikha Safitri Ilhan Nail Nabil Imro'ah, Nurfitri IMRO’AH, NURFITRI Imtiyaz, Widad Isra’ Sagita Jawani Jawani Jessica Audrey Valeria Khairina Auliannisa Kusnandar, Dadan Tonny Leona Idilla Louis Putra Jaya Lucky Hartanti Lucky Hartanti Lucky Hartanti M. Deny Hafizzul Muttaqin Maga, Fahmi Giovani Margareta, Tiara Margaretha, Ledy Claudia Marlisa, Herina Marola, Geby Martha, Shantika Maulidya, Gita Arinda Mega Sari Juane Sofiana Mega Sari Juane Sofiana Mega Tri Junika Millennia Taraly Misrawi Misrawi Muhammad Ahyar Muhammad Fikri Muhammad Radhi Muhammad Rizki Muliadi Muliadi Muslimah (F54210032) Nabil, Ilhan Nail Nanda Shalsadilla Naomi Nessyana Debataraja Naomi Nessyana Debataraja Nazwa Nursyifa Noerul Hanin Nona Lusia Novi Novi Nugrahaeni, Indah Nur Asih Kurniawati Nur Asiska Nurfadilah, Kori’ah Nurfitri Imro'ah Nurfitri Imro’ah Nurhalita Nurhalita Nurmaulia Ningsih Oktaviani, Indah Ovi Indah Afriani Paisal Paisal Pertiwi, Retno Pitriani Pratama, Aditya Nugraha Preatin Preatin Putri Putri Putri, Aulia Nabila Qalbi Aliklas R Puspito Harimurti Radhi, Muhammad Radinasari, Nur Ismi Rafdinal Rafdinal Rahadi Ramlan Rahmadanti, Putri Rahmanita Febrianti Rusmaningtyas Rahmawati, Fenti Nurdiana Ramadhan, Nanda Ramadhania, Wahida Regita, Luna Amara Reni Unaeni Resti Arsanti Retnani, Hani Dwi Ria Andini Ria Fuji Astuti Rina Rina Risky Oprasianti Rita Kurnia Apindiati Rivaldo, Rendi Riza Linda Rizki Nur Rahmalita Rizki, Setyo Wira Rosi Kismonika Roslina Rosi Tamara Rovi Christova Safira, Shafa Alya Salsabilla, Arla Santika Santika Sary, Rifkah Alfiyyah Savitri, Dini Dwi Seftiani, Seftiani Sela Karlina Selvy Putri Agustianto Setyo Wir Rizki Setyo Wira Rizki Setyo Wira Rizki Setyo Wira Rizki Shantika Martha Shantika Martha Sinaga, Steven Jansen Sintia Margun Sista, Sekar Aulia Siti Aprizkiyandari Siti Aprizkiyandari, Nurul Qomariyah, Shantika Martha, Siti Hardianti Suci Angriani Sukal Minsas Sukal Minsas Syahida, Murni Syuradi syuradi Tamtama, Ray Taraly, Inggriani Millennia Tiara, Dinda Trifaiza, Fadhela Wahyu Diyan Ramadana Wahyudin Ciptadi Warsidah Warsidah Wilda Ariani Wirda Andani Yohanna Gabriel Richsita Yopi Saputra Yudhi Yuliono, Agus Yumna Siska Fitriyani Yundari Yundari Yundari, Yundari Yuveinsiana Crismayella Yuyun Eka Pratiwi Zakiah, Ainun