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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan ABDIMASY: Jurnal Pengabdian dan Pemberdayaan Masyarakat Journal of Statistics and Data Science
Crisdianto, Riki
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ANALYSIS OF THE EXISTENCE OF THE AGRICULTURAL SECTOR IN MODELING POVERTY IN BENGKULU PROVINCE USING GAUSSIAN COPULA MARGINAL REGRESSION Nugroho, Sigit; Rini, Dyah Setyo; Novianti, Pepi; Crisdianto, Riki; Karuna, Elisabeth Evelin; Fairuzindah, Athaya
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp1251-1262

Abstract

Bengkulu Province ranks second in the category of the highest percentage of poor people in the Sumatra region, at 14.62% in March 2022, and sixth in Indonesia, which is undoubtedly one of the fundamental problems that requires mutual attention. The phenomenon of high poverty in Bengkulu Province is inseparable from the lives of people whose main livelihood is in the agricultural sector, especially tenant farmers. Therefore, in this study, the Copula and Gaussian Copula Marginal Regression (GCMR) methods are applied to determine how the agricultural sector affects poverty in Bengkulu Province using secondary data obtained from the Bengkulu Provincial Statistics Agency (Susenas 2022). The results show that the Copula model can identify various types of dependency between the number of poor households in each district/city in Bengkulu Province in 2022 and each of the variables, namely the Number of Agricultural Business Households , the Growth Rate of the Agricultural Sector , the Human Development Index , and the Open Unemployment Rate ( ) by considering the different characteristics of dependency such as top-tail, bottom-tail, or negative dependency. Meanwhile, the GCMR model can provide the direction of influence of the independent variables on the dependent variable Y, where it can be seen that the variables , , and have a negative influence on the variable , whie the variable has a positive impact on the variable . Therefore, in general, it can be concluded that either positive or negative dependencies identified by the Copula model can influence the resulting GCMR model by providing more profound complexity regarding the relationship between the variables analyzed.
Pelatihan pembuatan kukis tepung pisang dengan fortifikan bubuk daun kelor kepada warga desa Nubamado Lembata Nusa Tenggara Timur Nurholisah, Nurholisah; Nirmala, I Gusti Ayu Asti Devi; Althaf, Anindita Nareswari; Cahyani, Amalia Regita; Oktaviyani, Yanti; Crisdianto, Riki; Hidayat, Rosyid; Lena, Damasus Frederiko; Tukan, Gerardus Diri
ABDIMASY: Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol. 6 No. 1 (2025): ABDIMASY: Jurnal Pengabdian dan Pemberdayaan Masyarakat
Publisher : STAI Auliaurrasyidin Tembilahan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46963/ams.v6i1.2347

Abstract

Nubamado Village, Lembata Regency has the potential for kepok bananas (Musa acuminata balbisiana Colla) which are still processed and utilized traditionally so this potential has little economic value. This training aims to provide knowledge and skills to residents to process this potential into functional food. The activity method is training. Activity results: partners are enthusiastic about participating in the training.  Ingredients: 5 kg of fresh bananas, peeled, sliced, dried in the sun, then blended until smooth and filtered. Obtained 2.3 kg of flour. Young Moringa leaves are also dried and blended until they become a fine white powder. Add 200 grams of banana flour, one chicken egg, 50 grams of margarine, 10 grams of sugar and 5 grams of Moringa leaf powder. The dough is formed into semi-circular cookies with a diameter of 5cm and baked in the oven until dry. There were 62 cookies obtained. The training participants tasted the cookies produced and expressed their liking and joy because they had gained knowledge, skills and experience in making banana cookies.
Earthquake Clustering Using the CLARA Method and Modeling Using the Inhomogeneous Spatial Cox Processes Method in the Ambon Region: Earthquake Clustering Using the CLARA Method and Modeling Using the Inhomogeneous Spatial Cox Processes Method in the Ambon Region Meiwidian, Muhamad Iqbal; Crisdianto, Riki; Rini, Dyah Setyo
Journal of Statistics and Data Science Vol. 2 No. 2 (2023)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jsds.v2i2.30249

Abstract

Earthquakes are natural events whose time and place cannot be predicted. Ambon is the largest city in the Maluku Islands region and is the center of development and the capital of Maluku Province. This research will group earthquake events, analyze the characteristics of earthquake events, create earthquake zones and map them using CLARA cluster analysis, and create modeling that will look at the risk of earthquake events in a location based on distance to faults and subduction zones using the Inhomogeneous Neyman-Scott Cox Process. The data used is data on earthquake events in the Ambon region obtained from the United States Geological Survey (USGS) catalog from January 1926 to December 2022, with a depth of ≤360.1 Km and a magnitude of ≥4 Mw. Grouping earthquake events in the Ambon area using CLARA cluster analysis obtained 2 groups of earthquake clusters with an optimal silhouette score of 0.7430. The model obtained in this earthquake research is not good because it is based on the K-function value plot of the original data which is far from the modeling K-function value plot.
Co-Authors Althaf, Anindita Nareswari Cahyani, Amalia Regita Fairuzindah, Athaya Gerardus Diri Tukan Hidayat, Rosyid Karuna, Elisabeth Evelin Lena, Damasus Frederiko Meiwidian, Muhamad Iqbal Nirmala, I Gusti Ayu Asti Devi Nurholisah, Nurholisah Oktaviyani, Yanti Pepi Novianti Rini, Dyah Setyo Sigit Nugroho