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All Journal Jurnal Sains Matematika dan Statistika BAREKENG: Jurnal Ilmu Matematika dan Terapan
Budijono, Gabriella Agnes
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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Analisis Korespondensi Hasil Produksi Budidaya Perikanan Berdasarkan Jenis Budidaya dan Pembagian Wilayah di Indonesia Abdillah, Adrian Wahyu; Marthabakti, CitraWani; Budijono, Gabriella Agnes; Wulandari, Indana Zulfa; Amelia, Dita; Mardianto, M. Fariz Fadillah; Ana, Elly
Jurnal Sains Matematika dan Statistika Vol 11, No 1 (2025): JSMS Januari 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/jsms.v11i1.27913

Abstract

Indonesia dikenal sebagai negara maritim karena mayoritas wilayahnya terdiri dari perairan sehingga sektor perikanan menjadi bagian integral dari kehidupan dan ekonomi masyarakat Indonesia. Produk perikanan menjadi salah satu komoditas ekspor utama Indonesia. Adanya perbedaan faktor geografis dan topografis di berbagai wilayah Indonesia berpengaruh terhadap jenis budidaya yang paling cocok pada keberhasilan budidaya perikanan. Oleh karena itu, penelitian menganalisis kecenderungan dari jenis budidaya perikanan dengan wilayah Indonesia secara geografis. Hasil pencatatan dari Produksi Budidaya Perikanan Menurut Provinsi dan Jenis Budidaya pada tahun 2021 digunakan sebagai data sekunder yang akan dianalisis. Pendekatan statikstika yang dipilih yaitu analisis korespondensi dengan jenis budidaya perikanan dan pembagian wilayah Indonesia sebagai variabel analisis. Sebelum dilakukan analisis korespondensi, diperlukan uji independensi yang hasilnya adalah terdapat keterkaitan yang nyata antar kedua variabel. Dari hasil analisis korespondensi diperoleh bahwa jenis budidaya jaring apung tawar, jaring apung laut, tambak intensif, tambak semi intensif, kolam air tenang, kolam air deras, dan minapadi sawah lebih cenderung dikembangkan di wilayah barat. Sedangkan jenis budidaya jaring tancap tawar, tambak sederhana. karamba, dan rumput laut lebih cenderung dikembangkan di wilayah tengah. Dan jenis budidaya laut lainnya lebih cenderung dikembangkan di wilayah timur Indonesia. Dari hasil ini, para pelaku produksi perikanan budidaya dapat menggunakannya sebagai acuan dalam memilih jenis budidaya yang tepat sehingga hasil produksi dapat lebih maksimal.
MODELING FACTORS CAUSING ALZHEIMER’S DISEASE USING LOGIT, PROBIT, AND GOMPIT LINK FUNCTIONS IN GENERALIZED LINEAR MODEL Kurniawan, Ardi; Budijono, Gabriella Agnes; Siagian, Kimberly Maserati; Abdillah, Adrian Wahyu
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 4 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss4pp2877-2890

Abstract

This study addresses the ongoing challenge of clarifying the risk factors contributing to Alzheimer's disease, a neurodegenerative condition marked by progressive cognitive decline and memory dysfunction, with cases rising globally. To provide a more accurate and comprehensive understanding of the predictors associated with the disease, this research models the contributing factors using logit, probit, and gompit link functions within the Generalized Linear Model (GLM). Utilizing secondary data from 2024, which includes predictor variables such as age, family history, head injury, hypertension, memory complaints, and behavioral disturbances, this research models the relationship between these variables and Alzheimer's diagnosis. The analysis finds that the logit, probit, and gompit link functions yield significant results in identifying risk factors associated with Alzheimer's diagnosis, particularly memory complaints and behavioral disturbances. The gompit link is selected as the best model due to its highest deviance R-squared value of 30.01%, indicating better reliability in predicting Alzheimer's diagnosis than other models. This GLM approach provides insights to support early prevention and intervention efforts for Alzheimer's disease and contribute to achieving Sustainable Development Goals (SDGs) number 3 on good health and well-being.
SPATIAL EXTRAPOLATION OF MALARIA CASES IN CENTRAL PAPUA USING CO-KRIGING BASED ON RAINFALL AND OBSERVATIONAL DATA FROM PAPUA PROVINCE Saifudin, Toha; Chamidah, Nur; Zhafira, Azizah Atsariyyah; Budijono, Gabriella Agnes; Sihite, Rivaldi; Baihaqi, Mochamad; Januarta, R. Arya
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss2pp1485-1500

Abstract

Malaria is an infectious disease that remains a significant health burden in Indonesia, particularly in Papua Province. This province has the highest malaria incidence rate nationally, influenced by various environmental factors such as rainfall. This study aims to estimate the number of malaria cases in districts/cities of Central Papua Province that do not have direct observation data, by utilizing the Co-Kriging method based on rainfall as a secondary variable and malaria cases as a primary variable from Papua Province. The secondary data used in this study were obtained from the official website of the Badan Pusat Statistik (BPS) of Papua Province, which includes the number of malaria cases in districts/cities as well as rainfall data from meteorological stations in the same region, collected in 2023. Three types of semivariogram models-spherical, exponential, and gaussian-were used to select the best model through statistical evaluation using Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE). The results showed that the Gaussian semivariogram model provided the most optimal prediction results with an MSE of 10.895 and an MAPE of 4.67%. The estimates show that malaria cases in Central Papua are relatively uniform, with the highest incidence in Puncak Jaya district (219/1000 population) and the lowest in Mimika district (211/1,000 population). This approach is expected to be an important tool in spatially based disease planning and control and support the achievement of Sustainable Development Goals (SDGs), especially goals 3 (Good Health and Well-Being) and 13 (Climate Action).
Co-Authors Abdillah, Adrian Wahyu Ardi Kurniawan Baihaqi, Mochamad Dita Amelia Elly Ana Januarta, R. Arya M. Fariz Fadillah Mardianto Marthabakti, CitraWani Nur Chamidah Siagian, Kimberly Maserati Sihite, Rivaldi Toha Saifudin Wulandari, Indana Zulfa Zhafira, Azizah Atsariyyah