Jurnal Matematika, Statistika dan Komputasi

Harnessing the Potential of the Blue Economy in Central Java: Mapping, Strategic Development, and Macroeconomic Analysis

Dwi Wahyudi

This study aims to map the potential of the blue economy across 35 regencies/cities in Central Java Province while analyzing the factors influencing its development. The Blue Economy Index (BEI) used in this research was developed by leveraging big data, such as satellite imagery and digital sensors, enabling more detailed and real-time data collection. The findings reveal significant disparities between the southern coastal areas, northern coastal areas, and non-coastal regions. The southern coastal areas exhibit higher BEI values compared to the northern coastal and non-coastal areas, which fall below the average. A two-step system GMM regression analysis shows that variables such as internet usage, infrastructure, and the COVID-19 period significantly influence BEI. Specifically, infrastructure development, as measured by the Nighttime Light (NTL) proxy, negatively impacts BEI, indicating that environmentally unfriendly infrastructure development can harm the sustainability of the blue economy. Meanwhile, access to digital technology through internet usage plays a crucial role in supporting inclusive blue economy growth. Based on these findings, the proposed policy recommendations include optimizing environmentally friendly infrastructure development, leveraging digital technology to expand market access, and strengthening blue economy resilience through ARI (Adaptive-Responsive-Innovative) crisis policies. Thus, the development of the blue economy in Central Java is expected to sustainably improve the welfare of coastal communities and fully optimize the potential of coastal regions.

Connectivity of Coprime Graphs over Cyclic Groups

Arif Munandar

Comparison of SARIMA and LSTM Performance in Forecasting the International Passenger Arrivals at Soekarno Hatta Airport

Akbar Rizki

Time series forecasting is the process of analyzing data to predict future values. Time series analysis often faces assumption violations due to dynamic and fluctuating data, such as the number of international passengers arriving at Soekarno Hatta Airport in Tangerang. This study uses the seasonal autoregressive integrated moving average (SARIMA) and long short term memory (LSTM) methods to find forecasting data with seasonal and fluctuating data. This research aims to compare the performance of the two models in predicting the number of international passengers arriving at Soekarno Hatta Airport in the next period. The data used consists of daily international passenger counts from January 1, 2022 to January 1, 2024 sourced from the sistem informasi angkutan dan sarana transportasi (SIASATI). The best model in SARIMA is SARIMA(0,1,1)(0,1,2)⁷ model, resulted in a MAPE of 7,98%, while the best LSTM model, with 50 neurons, 100 epochs, a learning rate of 0.01, a time step of 10, and a batch size of 16, achieved a MAPE of 7.81%. The results show that LSTM is more accurate in predicting the declining trend of passenger numbers at Soekarno-Hatta Airport over the next 31 days.

Pengelompokan Kabupaten/Kota di Provinsi Papua Barat Berdasarkan Indikator Kesejahteraan Rakyat Tahun 2023 Menggunakan Metode C-means dan Fuzzy C-means Clustering

Irfan Masrudin

Kesejahteraan rakyat adalah suatu kondisi yang menampilkan tentang keadaan kehidupan masyarakat yang dapat dilihat dari standar kehidupan masyarakat. Di Indonesia bantuan terutama di Provinsi Papua Barat, tingkat sosial yang masih sangat rendah dan banyak masyarakat yang hidup di garis kemiskinan. Salah satu upaya menuju kesejahteraan rakyat adalah dengan meningkatkan kesejahteraan masyarakat dalam aspek ekonomi dan sosial. Untuk mencapai tujuan ini, penting untuk memahami kondisi awal kesejahteraan mayarakat. Kondisi awal dapat ditentukan dengan mengelompokkan suatu kabupaten/kota dan melakukan pemerataan kesejahteraan masyarakat di setiap daerah. Dalam statistika terdapat dua metode yaitu pengelompokan dan klasifikasi. Dalam penelitian ini, metode statistika yang digunakan yaitu pengelompokan. Pengelompokan (clustering) adalah teknik mengelompokan data, yang bertujuan untuk mengelompokkan objek berdasarkan kesamaan karakteristiknya. Terdapat dua pendekatan dalam clustering yaitu berhierarki dan non-berhierarki. Dalam penelitian ini,pendekatan non-berhierarki yang digunakan. Non-berhierarki terdiri dari dua metode yaitu c-means dan fuzzy c-means. Tujuan pada penelitian ini adalah untuk mengelompokkan indikator kesejahteraan rakyat dengan metode c-means dan fuzzy c-means menggunakan data indikator kesejahteraan rakyat dari tahun 2023. Metode c-means adalah metode clustering yang membagi data ke dalam satu cluster atau lebih sebanyak buah, sedangkan metode fuzzy c-means adalah metode pengelompokan objek yang memanfaatkan dasar pembobotan dengan teori himpunan fuzzy. Hasil penelitian ini adalah membandingkan kedua metode tersebut untuk mendapatkan hasil pengelompokan terbaik, hasil yang diperoleh yaitu fuzzy c-means clustering dengan jumlah cluster dengan pembagian cluster yaitu cluster 1 terdapat 2 kabupaten. Cluster 2 terdapat 1 kabupaten, cluster 3 terdapat 4 kabupaten, cluster 4 terdapat 2 kabupaten dan cluster 5 terdapat 4 kabupaten. Diperoleh nilai indeks siluet sebesar 0,3428 yang dapat dikategorikan baik dan nilai rasio sigma w/sigma b adalah 0,7613.

Examination of School Participation Rates with Nonparametric Geographically Weighted Regression-Truncated Spline Approach

Muhammad Rayhan Arman

This study analyzes school participation rates (APS) in Indonesia using the Nonparametric Geographically Weighted Regression-Truncated Spline (NGWR-TS) method. The objective is to identify significant factors influencing APS across 34 provinces, considering geographic variations and nonlinear data patterns. Secondary data was obtained from the Central Bureau of Statistics (BPS), the Ministry of Education and Culture (Kemendikbud), and the Ministry of Women's Empowerment and Child Protection (KemenPPPA). The analysis results indicate that APS are influenced by accessibility to education, teaching quality, and socioeconomic conditions. Spatial mapping reveals that regions with high APS, such as Special Region of Yogyakarta, have good educational infrastructure support, while Papua exhibits low participation due to geographic and social challenges. This study emphasizes the need for more focused and locally responsive education policies to improve APS, especially in underdeveloped regions. The contribution of this research to achieving the Sustainable Development Goals (APS) in Indonesia is significant, particularly in enhancing educational participation in areas that require more attention. The aim of this approach is to develop policies that will substantially enhance educational outcomes and increase school attendance across Indonesia.

Global Stability and Sensitivity Analysis of a Mumps Transmission Model

Ratna Widayati

Mumps is a viral infection that targets the parotid glands, caused by a virus from the Rubulavirus genus within the Paramyxoviridae family. Early symptoms include fever, headache, muscle pain, and facial swelling. Transmission occurs through droplets, fomites, or direct contact. The best prevention is the MMR vaccine, although its effectiveness is limited due to high virus mutation rates. Children aged five to nine and vaccinated young adults are also at risk. Due to the decreased effectiveness of the vaccine, new management strategies such as quarantine have been introduced. This study builds on previous research by focusing on both global stability and sensitivity analysis, which had not been addressed before. It uses Lyapunov functions to analyze global stability at both equilibria and sensitivity analysis with respect to the basic reproduction number and the infected population size to identify factors contributing to high transmission rates. The findings show that global stability analysis indicates that the disease-free equilibrium is globally asymptotically stable if the basic reproduction number is less than or equal to 1, while the endemic equilibrium is globally asymptotically stable if the basic reproduction number is greater than 1. Sensitivity analysis identifies that the most influential parameters on the infected population are those affecting the graph directly and inversely, namely the contact rate between susceptible and infected individuals, the natural death rate, and the birth rate. Increasing the contact rate between susceptible and infected individuals and the birth rate raises the number of infected individuals, whereas increasing the natural death rate reduces the number of infected individuals.

Bahasa Indonesia Hybrid Hierarchical Clustering Via Mutual Cluster pada Pengelompokan Kabupaten/Kota di Pulau Kalimantan Berdasarkan Indikator Kemiskinan

Farikah Ayu arinanda

Analisis cluster adalah salah satu teknik analisis data yang digunakan untuk mengelompokkan suatu objek dalam satu cluster berdasarkan kemiripan karakteristik antar objeknya. Hybrid hierarchical clustering via mutual cluster merupakan metode pengelompokan yang menggabungkan keunggulan dari dua pendekatan yang bersifat buttom up dan yang bersifat top down. Hierarchical clustering digunakan untuk membangun struktur hierarki dari data, sedangkan mutual cluster membantu dalam penentuan jumlah cluster optimal serta memastikan kestabilan hasil clustering. Tujuan penelitian ini adalah melakukan pengelompokan Kabupaten/Kota di Pulau Kalimantan berdasarkan indikator-indikator yang diduga berpengaruh terhadap kemiskinan Tahun 2022. Hasil penelitian, diperoleh cluster optimal sebanyak 4 cluster dari hasil validitas menggunakan Cluster Tightness Measure (CTM) dengan nilai terkecil yaitu sebesar 0,655. Karakteristik dari setiap cluster yang terbentuk dapat menjadi informasi untuk pemetaan daerah kemiskinan.

Kata kunci: Analisis Cluster, Buttom Up, Hybrid Hierarchical Clustering, Mutual Cluster,

Top Down, dan Cluster Tightness Measure (CTM)

A NOTE ON EQUIVALENCE RELATIONS ON TERNARY SEMIGROUPS

Dr. U. Nagi Reddy Ulavala

The awareness of ideals affects obviously to the concern of certain equivalence relations over a ternary semi-group. These equivalence relations, early studied by J.A. Green (1951), have acted a basic role in the progress of semi-group theory. The majorapplication of this paper is to find the some results on Greens Relations and their conditions on ternary semigroups.

Average Temperature Prediction Using The Singular Spectrum Analysis Method

Farafina Masayu Azzahra

Surabaya is one of the cities with the highest population density in Indonesia, which continues to grow and urbanize at an extraordinary speed. In addition to having a dense population, the capital of East Java Province has a complex infrastructure, so ma

Dian Yuliati

Surabaya is one of the cities with the highest population density in Indonesia, which continues to grow and urbanize at an extraordinary speed. In addition to having a dense population, the capital of East Java Province has a complex infrastructure, so many emergency events occur. According to the annual report of BPBD Surabaya City, as many as 13 thousand emergency events occurred in 2023. Therefore, with a large chance of emergency events occurring, it is necessary to reduce the risk of emergency events. Therefore, capacity building is important to increase community resilience during emergency events. This research aims to determine the level of capacity of an area. This calculation is carried out using the Principal Component Analysis (PCA) method based on the parameters that determine the capacity of an area. The calculation results found that there are 9 sub-districts with high capacity levels, 17 sub-districts with medium capacity levels, and 5 sub-districts with low capacity levels. So it can be concluded that Surabaya City still needs an increase in capacity.