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Factor Analysis on Poverty in Kalimantan Island with Geographically Weighted Negative Binomial Regression Alvin Octavianus Halim; Neva Satyahadewi; Preatin Preatin
Pattimura International Journal of Mathematics (PIJMath) Vol 4 No 1 (2025): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol4iss1pp41-52

Abstract

Poverty is one of the problems still faced by Indonesia. The problem of poverty is a development priority because poverty is a complex and multidimensional problem. Therefore, to reduce poverty, it is necessary to know the factors that influence the number of people living in poverty. The influencing factors in each region are different due to the effects of spatial heterogeneity between regions such as geographical, economic, and socio-cultural conditions. This research considers spatial factors by using the Geographically Weighted Negative Binomial Regression (GWNBR) method on poverty-based regions in Kalimantan Island. This research uses eleven independent variables. The weighting function used is the Adaptive gaussian kernel because the adaptive kernel can produce the number of weights that adjust to the distribution of observations. The stage starts with descriptive statistics and checking multicollinearity. Then proceed with the formation of Poisson Regression, because the data used is enumerated data. Then check for overdispersion. If overdispersion is detected where the variance is bigger than the mean, then Negative Binomial Regression is continued. After that, it is tested for the presence or absence of spatial heterogeneity. If there is, proceed to find the bandwidth and Euclidean distance. After that, the graphical weighting matrix is searched. Then proceed with GWNBR modeling. The results of the analysis show that there are seven significant variables, including the percentage of households with the main source of lighting is non-state electricity company (PLN), average monthly net income of informal workers, population density for every square kilometer, monthly per capita expense on food and non-food essentials, percentage of people who have a health complaint and do not treat it because there is no money and percentage of population 15 years and above who do not have a diploma. Based on the categories of significant variables, six groups were formed in 56 districts/cities in Kalimantan Island.
Implementasi Pendekatan Behavioral Mapping pada Seting Ruang Berkumpul di Area Tepian Sungai Kapuas R Puspito Harimurti; Muhammad Radhi; Wahyudin Ciptadi; Neva Satyahadewi; Agus Yuliono
Kaganga:Jurnal Pendidikan Sejarah dan Riset Sosial Humaniora Vol. 7 No. 1 (2024): Kaganga: Jurnal Pendidikan Sejarah dan Riset Sosial Humaniora
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/kaganga.v7i1.8277

Abstract

Penelitian ini bertujuan untuk mengimplementasikan pendekatan behavioral mapping terhadap model seting ruang berkumpul informal pada kampung Budaya Tambelan Sampit yang mendukung aktifitas wisata budaya di Kota Pontianak, Kalimantan Barat. Penelitian ini menggunakan pendekatan rasionalistik-kualitatif dengan pendekatan deskriptif-kualitatif terhadap fenomena lingkungan perilaku yang ada pada ruang berkumpul informal masyarakat di Tambelan Sampit, Pontianak. Hasil penelitian menemukan lima karakteristik setting ruang berkumpul informal masyarakat ditepian sungai. Simpulan penelitian ini adalah: (a). Terdapat 6 (enam) model bentuk ruang berkumpul informal disepanjang area tepian Sungai, (b). Aktifitas informal masyarakat pada ruang-ruang berkumpul informal-nya, berlangsung dalam dua periode waktu, yaitu siang dan malam hari, (c). Area-area ruang berkumpul di tepian Sungai, digunakan selain untuk kegiatan berkumpul, juga merupakan bagian pendukung kegiatan wisata Budaya di Tambelan Sampit. Kata Kunci: Behavioral Mapping, Deskriptif-Kualitatif, Setting Ruang Berkumpul.
Conditional Value at Risk Portfolio With Monte Carlo Control Variates Maga, Fahmi Giovani; Sulistianingsih, Evy; Satyahadewi, Neva
Jambura Journal of Mathematics Vol 7, No 2: August 2025
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjom.v7i2.30952

Abstract

Stock investment is one of the instruments investors favor due to its potential for high returns, but the risks stemming from stock price volatility cannot be overlooked. Value at Risk (VaR) is commonly used as a standard approach to measure and manage these risks. However, VaR has limitations in handling extreme risks, making Conditional Value at Risk (CVaR) is a more effective choice. This research measures the application of CVaR to a portfolio of banking sector stocks in Indonesia using the Monte Carlo Control Variates (MCCV) technique, with the Indonesia Composite Index (ICI) as the control variable. The portfolio consists of stock of PT Bank Rakyat Indonesia Tbk (BBRI) and PT Bank Negara Indonesia Tbk (BBNI). The purpose of this research is to compare CVaR calculation results using Standard Monte Carlo Simulation (MCS) and MCCV simulations. The data used includes the daily closing prices of BBRI, BBNI, and ICI stocks for the period from March 1, 2023, to February 29, 2024. The VaR and CVaR calculated in this study are for one day. The results of the analysis show that the MCS CVaR values at 90%, 95%, and 99% confidence levels are 1.730%, 2.050%, and 2.569%, respectively, while the MCCV CVaR values at 90%, 95%, and 99% confidence levels are 1.400%, 1.662%, and 2.084%, respectively. These values indicate that using the ICI as a control variable has successfully improved risk estimation by utilizing the ICI as a control variable.
ANALYSIS OF FOOD SECURITY FACTORS WITH PATH MODELING SEGMENTATION TREE (PATHMOX) METHOD IN PARTIAL LEAST SQUARES IN WEST KALIMANTAN Harnanta, Nabila Izza; Perdana, Hendra; Satyahadewi, Neva
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp2229-2242

Abstract

Food security is essential for ensuring community well-being by guaranteeing sufficient, safe, and nutritious food, particularly in regions with complex socio-economic conditions. This study analyzes food security in West Kalimantan Province by identifying key influencing factors, constructing a structural equation model, and segmenting regions based on their food security characteristics. Utilizing secondary data from the 2023 Food Security and Vulnerability Atlas (FSVA), the research employs the Partial Least Squares Structural Equation Modeling (PLS-SEM) method with the Path Modeling Segmentation Tree (PATHMOX) approach. The study incorporates ten indicators across four latent variables: food availability, food access, food absorption, and overall food security. The results reveal that regional segmentation using the PATHMOX approach effectively identifies data heterogeneity, categorizing West Kalimantan’s 14 districts/cities into two distinct groups based on the Human Development Index (HDI). The first group (10 regions) exhibits higher food consumption despite socio-economic challenges, whereas the second group (4 areas) demonstrates better food security yet lower intake levels. These findings highlight that food security is influenced by access, distribution, and policy implementation rather than solely by the Normative Consumption Production Ratio (NCPR). The insights from this study provide a foundation for developing targeted policies to enhance food security strategies in West Kalimantan Province, ensuring a more sustainable and equitable food system. By applying PATHMOX segmentation, policymakers can address regional disparities more effectively, fostering strategic interventions that improve food availability, accessibility, and utilization across different population groups.
Peningkatan Keterampilan Analisis Data Bagi Fungsional BPS di Kalimantan Barat Melalui Pelatihan SEM dengan AMOS Martha, Shantika; Andani, Wirda; Sulistianingsih, Evy; Debataraja, Naomi Nessyana; Imro'ah, Nurfitri; Satyahadewi, Neva; Tamtama, Ray; Perdana, Hendra; Kusnandar, Dadan
Bahasa Indonesia Vol 22 No 01 (2025): Sarwahita : Jurnal Pengabdian Kepada Masyarakat
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/sarwahita.221.9

Abstract

This Community Service activity is a form of cooperation between Statistics Study Program FMIPA UNTAN and BPS through training activities. The purpose of this PKM is to provide knowledge and insight to BPS functional employees about SEM (Structural Equation Modeling) using AMOS. This activities were carried out on Monday, August 14, 2023 in the Vicon room of the West Kalimantan provincial BPS office with 32 participants attending. The results of this training activity are expected to be applied by BPS functional employees in processing and analyzing data as research needs and work related to statistical data. The level of success in this training was measured through pre-test, post-test and participant satisfaction survey. A wilcoxon test was conducted with α = 0.05 and the result was p-value smaller than 0.01. So that the p-value < α which means rejecting H0 and it can be concluded that the average pretest score < average posttest score. In other words, the post-test results increased significantly, which means that the participants' abilities increased after the training. Based on the participant satisfaction survey, the results showed that all participants (100%) had never used AMOS software before. Overall, participants were satisfied (61.5%) and very satisfied (38.5%) with the training because they could increase their knowledge and the training materials delivered were in accordance with their needs, easy to understand and interesting, could be applied easily, and were delivered in order and systematically.   Abstrak Kegiatan Pengabdian Kepada Masyarakat (PKM) ini merupakan salah satu wujud kerjasama Prodi Statistika FMIPA UNTAN dengan BPS melalui kegiatan pelatihan. Adapun tujuan PKM ini yaitu memberikan pengetahuan dan wawasan kepada pegawai fungsional BPS tentang teknik pengolahan dan analisis data SEM (Structural Equation Modelling) dengan menggunakan AMOS. Kegiatan PKM dilaksanakan pada hari Senin, 14 Agustus 2023 di ruang Vicon kantor BPS prov Kalbar dengan jumlah peserta yang hadir 32 orang. Hasil dari kegiatan pelatihan ini diharapkan dapat diterapkan oleh pegawai fungsional BPS dalam mengolah dan menganalisis data sebagai kebutuhan penelitian maupun pekerjaan yang berhubungan dengan data statistika. Tingkat keberhasilan pada pelatihan ini diukur melalui pemberian pretest, posttest dan survey kepuasan peserta. Dilakukan uji beda menggunakan uji wilcoxon dengan α = 0.05 dan didapatkan hasil yaitu berupa p-value lebih kecil dari 0.01. Sehingga p-value < α yang berarti tolak H0 dan dapat disimpulkan rata-rata nilai pretest < rata-rata nilai posttest. Dengan kata lain hasil posttest meningkat secara signifikan yang artinya kemampuan peserta meningkat setelah dilaksanakan pelatihan. Berdasarkan survey kepuasan peserta didapatkan hasil ternyata semua peserta (100%) belum pernah menggunakan software AMOS sebelum pelatihan. Secara keseluruhan peserta merasa puas (61,5%) dan sangat puas (38,5%) mengikuti pelatihan karena dapat menambah pengetahuan serta materi pelatihan yang disampaikan sesuai dengan kebutuhan, mudah dipahami dan menarik, dapat diterapkan dengan mudah, dan disampaikan dengan urut dan sistematis.
Estimation of Tail Value at Risk for Bivariate Portfolio using Gumbel Copula Fransiska, Fransiska; Sulistianingsih, Evy; Satyahadewi, Neva
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 2 (2025): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i2.29952

Abstract

Investing in the stock market involves complex risks, especially under extreme and unpredictable conditions. While Value at Risk (VaR) is a widely used risk measure, it has limitations in capturing tail-end risks. This study employs Tail Value at Risk (TVaR) using the Gumbel Copula approach, which effectively models upper-tail dependence in return distributions—an aspect often overlooked by traditional linear correlation methods. This quantitative research utilizes copula-based Monte Carlo simulation. The data consists of daily closing prices of PT Adaro Energy Indonesia Tbk (ADRO) and PT Indo Tambangraya Megah Tbk (ITMG) from July 3, 2023, to July 30, 2024. The analysis begins with return calculation and tests for autocorrelation and homoskedasticity. The Gumbel Copula parameter is estimated using Kendall’s Tau, resulting in a dependence parameter of 1.7791. Based on this, 1,000 simulations are conducted to generate new return data that reflect extreme dependencies between the two stocks. An optimal portfolio is constructed using the Mean-Variance Efficient Portfolio (MVEP) method, assigning weights of 31.61% to ADRO and 68.39% to ITMG. TVaR is then calculated from the simulated portfolio returns. The results show increasing TVaR values at higher confidence levels: 2.08%, 2.64%, 3.14%, and 4.11% for 80%, 90%, 95%, and 99%, respectively. These findings demonstrate that TVaR provides more accurate insights into potential losses in extreme market conditions, supporting investors in developing more informed and risk-sensitive portfolio strategies.
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.
Co-Authors . Apriansyah Aditya Handayani Afghani Jayuska Afghany Jayuska Alqaida Yusril Alvin Octavianus Halim Amriani Amir Amriani Amir Amriani Amir Amriani Amir Andani, Wirda Anisa Putri Ayuni Apriliyanti, Rita Aprizkiyandari, Siti Ardhitha, Tiffany Ari Hepi Yanti Arsyi, Fritzgerald Muhammad Ashari, Asri Mulya Asri Mulya Ashari Asty Fistia Ningrum Atikasari, Awang Aulia Puteri Amari Bambang Kurniadi Banu, Syarifah Syahr ciptadi, wahyudin 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 Esta Br Tarigan Evy Sulistianingsih Ewaldus Okta Ezra Amarya Aipassa Ferdina Ferdina Feriliani Maria Nani Fitriawan, Della Frans Xavier Natalius Antoni Fransisca Febrianti Sundari Fransiska Fransiska Giovani Parasta Riswanda Grikus Romi Gusti Eva Tavita Gusti Eva Tavita Hairil Al-Ham Hamzah, Erwin Rizal Hanin, Noerul Harimurti, Puspito Harnanta, Nabila Izza Hastri Sastia Wuri Helena, Shifa Hendra Perdana Hendrianto, El Herina Marlisa Huda, Nur'ainul Miftahul Huriyah, Syifa Khansa Ibnur Rusi Ikha Safitri Imro'ah, Nurfitri Imro’ah, Nurfitri Imtiyaz, Widad Indry Handayany Isra’ Sagita Jawani Jawani Karlina, Sela Kusnandar, Dadan Tonny Lucky Hartanti Lucky Hartanti Lucky Hartanti M. Deny Hafizzul Muttaqin Maga, Fahmi Giovani Margareta, Tiara Margaretha, Ledy Claudia Marlisa, Herina Marola, Geby Martha, Shantika Mega Sari Juane Sofiana Mega Sari Juane Sofiana Mega Tri Junika Millennia Taraly Misrawi Misrawi Muhammad Ahyar Muhammad Radhi Muliadi Muliadi Muslimah (F54210032) Nabil, Ilhan Nail Nanda Shalsadilla Naomi Nessyana Debataraja Naomi Nessyana Debataraja Noerul Hanin Nona Lusia Nugrahaeni, Indah Nur Asih Kurniawati Nur Asiska Nur&#039;ainul Miftahul Huda Nurfitri Imro'ah Nurfitri Imro’ah Nurhalita Nurhalita Nurmaulia Ningsih NUR’AINUL MIFTAHUL HUDA Oktaviani, Indah Ovi Indah Afriani Paisal Paisal Pertiwi, Retno Pratama, Aditya Nugraha Preatin Preatin Putri Putri Putri, Aulia Nabila Qalbi Aliklas R Puspito Harimurti Radhi, Muhammad Rafdinal Rafdinal Rahadi Ramlan Rahmadanti, Putri Rahmanita Febrianti Rusmaningtyas Rahmawati, Fenti Nurdiana Rahmi Fadhillah Ramadhan, Nanda Ramadhania, Wahida Reni Unaeni Retnani, Hani Dwi Ria Andini Ria Fuji Astuti Rina Rina Risky Oprasianti Rita Kurnia Apindiati Rivaldo, Rendi Riza Linda Rizki Nur Rahmalita Rosi Kismonika Roslina Rosi Tamara Rovi Christova Safira, Shafa Alya Salsabilla, Arla Santika Santika Sary, Rifkah Alfiyyah Seftiani Seftiani 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 Steven Jansen Sinaga Suci Angriani Sukal Minsas Sukal Minsas Syuradi syuradi Tamtama, Ray Taraly, Inggriani Millennia Tiara, Dinda Wahyu Diyan Ramadana Wahyudin Ciptadi Warsidah Warsidah Warsidah, Warsidah Wilda Ariani Wirda Andani Yopi Saputra Yudhi Yuliono, Agus Yumna Siska Fitriyani Yundari, Yundari Yuveinsiana Crismayella Zakiah, Ainun