Modeling and Analysis of the Dynamic Model of Bali Starling (Leucopsar Rothschildi) Breeding in West Bali National Park

Antara, the official news agency of the state, reported a record-breaking population of 303 Bali starlings in the West Bali National Park (WBNP) in June 2020, attributing this achievement to the park's captive reproduction initiative. This paper presents a study on the dynamic equilibrium of Bali Starlings and proposes a mathematical model for analyzing this dynamic. The research also examines parameters ensuring the stability of the captive breeding model for Bali starlings in WBNP in a sustainable manner. The Bali starlings are categorized into two groups: those in the wild and those in captive breeding, with hatched eggs in captivity included in the latter. The dynamic model is analyzed for system stability around the endemic critical point using the Routh-Hurwitz stability criteria. As an illustrative example, a simulation is conducted to assess the model's suitability under real field conditions. The model analysis reveals that the existence of an endemic critical point can be maintained if the percentage of stolen Bali starlings or eggs reintroduced to the wild is less than the difference between the percentage of Bali starlings laying eggs and the population growth rate in WBNP. Furthermore, the stability of the endemic critical point is confirmed as long as the percentage of Bali starlings laying eggs exceeds the population growth rate. This dynamic model offers a valuable tool for evaluating the sustainability of Bali starling breeding programs and optimizing the benefits associated with their conservation efforts. 

Tourism Development Priorities in Lombok Eastern with Analytical Hierarchy Process

East Lombok is a regency that has tourism potential to be developed. In accelerating the pace of tourism development in East Lombok Regency, a decision support system is needed to make it easier to determine development priorities in the tourist sector. Analytical Hierarcy Process is a decision-making method that can solve the problem of multicriteria in the aspect of tourism in East Lombok. The data used are 50 data by prioritizing the opinions of experts and policy makers, namely the East Lombok Tourism Office, Head of tourism awareness groups and people involved in the tourism sector. The results showed that the value of index consistency was below 10% for each indicator and subindicator with infrastructure indicators as the highest priority with a value of 29.4545% and the highest subindicator was accessibility with a value of 17.8381%. The result of the calculation are expected to help policy makers in determining the strategy in the development of the tourism sector in Eaast Lombok district and in the future it can be developed by considering other factors

PENDUGAAN PROPORSI RUMAH TANGGA MISKIN TINGKAT DESA DI PROVINSI BALI DENGAN METODE EMPIRICAL BEST LINEAR UNBIASED PREDICTION DAN BAYESIAN

Kebijakan pengentasan kemiskinan pada pemerintahan presiden Ir. H. Joko Widodo dilakukan melalui empat strategi kunci yang salah satunya adalah pemberdayaan kelompok masyarakat miskin. Ketersediaan informasi mengenai kemiskinan sangatlah minim padahal untuk menerapkan strategi kebijakan tersebut seharusnya dimulai pada kelompok masyarakat terkecil yakni masyarakat desa. Guna memperoleh informasi kemiskinan pada tingkat desa, penelitian ini menerapkan metode pendugaan area kecil sebagai akibat kurang efektifnya pendugaan langsung pada area kecil. Metode pendugaan area kecil yang umum digunakan yakni metode empirical best linear unbiased prediction (EBLUP), empirical Bayes (EB), dan metode hierarchical Bayes (HB). Hasil yang diperoleh pada pendugaan area kecil pada tingkat desa di Provinsi Bali menujukkan bahwa dugaan proporsi rumah tangga miskin di tingkat desa di Provinsi Bali berada di antara 0,00423 dan 0,03910 serta nilai mean square error yang berada di antara 0,0013 dan 0,1291 diperoleh melalui metode hierarchical Bayes, kemudian untuk metode empirical Bayes diperoleh dugaan proporsi rumah tangga miskin di antara 0,00423 dan 0,03909 serta nilai mean square error di antara 0,0011 dan 0,1288 dan metode empirical best linear unbiased prediction diperoleh dugaan proporsi rumah tangga miskin berada di antara 0,00425 dan 0,03910 serta nilai mean square error di antara 0,00010 dan 0,1291. Secara umum nilai mean square error berada di kisaran yang sama. Sehingga ketiga metode pendugaan tidak dapat disimpulkan yang lebih baik satu dengan yang lainnya

PENGELOMPOKKAN KABUPATEN DI PROVINSI JAWA TENGAH BERDASARKAN KARAKTERISTIK IKLIM MENGGUNAKAN FUZZY CLUSTERING

There are many factors affecting human life, one of which is climate. Differences in climatic conditions in each region result in differences in the environment in society. The differences are referred to as potential natural resources, livelihoods, and social cultural conditions. The climate has an impact on culture in terms of how people dress, the shape of houses, and so on. The regency group in Central Java Province is based on similarities in climate characteristics using fuzzy clustering. The data used were taken from Central Java Provincial Statistical Office in 2022.The results of district grouping in Central Java Province are based on similarities in climate characteristics using fuzzy clustering with 4 different number of clusters and the validity tests of the Partition Coefficient and Classification Entropy indices. Based on the results of the index validity test, the optimal grouping results are 2 clusters with a Partition Coefficient value of 0.911233 and a Classification Entropy value of 0.07979. The 1st cluster consists of 13 districts with a cluster center at 27.9°C for air temperature, 2418mm for rainfall, and 804% for keelThe 2nd cluster and airbase consist of 22 cluster central districts at 26.6 °C for air temperature, 4087 mm for rainfall, and 81.3% for humidity

A Non-hydrostatic Model for Simulating Dam-Break Flow Through Various Obstacles

In this paper, we develop a mathematical model for modelling and simulation of the dam-break flow through various obstacles. The model used here is an extension of one-layer non-hydrostatic (NH-1L) model by considering varying channel width (Saint Venant). The capability of our proposed scheme to simulate free surface wave generated by dam-break flow through various obstacles is demonstrated, by performing two types of simulation with various obstacles, such as; bottom obstacle and channel wall contraction. It is shown that our numerical scheme can produce the correct surface wave profile, comparable with existing experimental data. We found that our scheme demonstrates the evolution of a negative wave displacement followed by an oscillating dispersive wave train. These well-captured dispersive phenomena, indicated both the appropriate numerical treatment of the dispersive term in our model and the performance of our model

Pendugaan Proporsi Rumah Tangga Miskin Tingkat Desa di Provinsi Bali dengan Metode Empirical Best Linear Unbiased Prediction dan Bayesian

Kebijakan pengentasan kemiskinan pada pemerintahan presiden Ir. H. Joko Widodo dilakukan melalui empat strategi kunci yang salah satunya adalah pemberdayaan kelompok masyarakat miskin. Ketersediaan informasi mengenai kemiskinan sangatlah minim padahal untuk menerapkan strategi kebijakan tersebut seharusnya dimulai pada kelompok masyarakat terkecil yakni masyarakat desa. Guna memperoleh informasi kemiskinan pada tingkat desa, penelitian ini menerapkan metode pendugaan area kecil sebagai akibat kurang efektifnya pendugaan langsung pada area kecil. Metode pendugaan area kecil yang umum digunakan yakni metode empirical best linear unbiased prediction (EBLUP), empirical Bayes (EB), dan metode hierarchical Bayes (HB). Hasil yang diperoleh pada pendugaan area kecil pada tingkat desa di Provinsi Bali menujukkan bahwa dugaan proporsi rumah tangga miskin di tingkat desa di Provinsi Bali berada di antara 0,00423 dan 0,03910 serta nilai mean square error yang berada di antara 0,0013 dan 0,1291 diperoleh melalui metode hierarchical Bayes, kemudian untuk metode empirical Bayes diperoleh dugaan proporsi rumah tangga miskin di antara 0,00423 dan 0,03909 serta nilai mean square error di antara 0,0011 dan 0,1288 dan metode empirical best linear unbiased prediction diperoleh dugaan proporsi rumah tangga miskin berada di antara 0,00425 dan 0,03910 serta nilai mean square error di antara 0,00010 dan 0,1291. Secara umum nilai mean square error berada di kisaran yang sama. Sehingga ketiga metode pendugaan tidak dapat disimpulkan yang lebih baik satu dengan yang lainnya

PENENTUAN HARGA OPSI DAN NILAI HEDGE MENGGUNAKAN PERSAMAAN NON-LINEAR BLACK-SCHOLES

Option are contracts that give the right to sell and buy the asset at a price and a certain period of time. In addition investors use option as a means of hedge against asset owned. Many methods are used to determine the price of option, one of them by using the Black-Scholes equation. But its use these in the assumption that the value for the constant volatility. On market assumption are not appropriates, so many researchers proposed using a volatility calculation option that is non-constant Black-Scholes equation modelled using the volatility is not constant in the range so as to produce a non-linear equation of  Black-Scholes. In addition to determine the value of hedge ratio. On completions of this study, for the numerical solution of non-linear Black-Scholes equation using method of explicit finite difference scheme. Option use in research us a stock YAHOO!inc. as the underlying asset. The result showed that the price of the option is calculated using non-linear Black-Scholes equation price close on the market. Therefore, it can produce hedge ration for a risk-free portfolio containing of the option and stock

Optimalisasi Harga Penjualan Perumahan dengan Metode Goal Programming (Studi Kasus: Golden Gindi Residence Kota Bima Nusa Tenggara Barat)

This research aims to determine the minimum selling price of each type of house using the method of goal programming, so that the developer  get profit  in appropriate with the targets set. Goal Programming method is one of the method of solving linear programming to solve the problems that include multiple targets. The result of the research showed: (1) the minimum salling price type of house 36/150 is Rp. 56.371.450,-; (2) type 45/150 is Rp. 77.261.250,-; (3) type 52/150 is Rp. 84.221.445,56. To calculate monthly installment purchase of a home within 5 years and 10 years using Capital Recovery Factor (CRF) method with annual interest of 11.5%. In order to obtain the amount of monthly loan installments within 5 years with 60 time installments for the type 36/150 is Rp. 930.250 , type 45/150 is Rp. 1.275.000 and type 52/150 is Rp. 1.389.800. By using the same method obtained the amount of monthly installments within 10 years with 120 installments for the type 36/150 is Rp. 549.900, type 45/150 is Rp. 815.300 and type 52/150 is Rp. 888.800 . Optimal selling price obtained was lower than the selling price from the developer, so the developer need to consider again the results obtained for the salling price of homes. The calculation of credit installments depending on the amount of interest and repayment period, so not become burden for the customers

PEMILIHAN KRITERIA DALAM PEMBUATAN KARTU KREDIT DENGAN MENGGUNAKAN METODE FUZZY AHP

<p>The rise of credit card users, make banks compete to provide a wide range of offers to attract customers. This study aims to determine the priority criteria selected customers for establishment credit cards by using a fuzzy AHP method. Method fuzzy AHP is a combination of the AHP method and fuzzy method. Fuzzy AHP approach particularly triangular fuzzy number approach to the AHP scale should be able to minimize uncertainty for the results obtained are more accurate. The criteria used for this study is the interest rate , the promo/discount, limit, and annual dues. Based on the steps of calculation of data obtained fuzzy AHP respondents have value CR = 0.049, which means consistent because it meets the standards set CR &lt; 0.10 and that became the order of priority are limit, promo/discount, interest rate, and  continued with weights of priorities are 0408, 0.28, 0.16, and 0.152.</p