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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan Prosiding Seminar Nasional Unimus
Amrullah, Setiawan
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Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Health Professions Mathematics Mechanical Engineering Nursing Physics Public Health Transportation

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Pelatihan Pertanian Modern untuk Meningkatkan Regenerasi Petani Muda di Desa Sidorejo Demak Fadillah, Muhammad Reza; Fauzi, Fatkhurokhman; Haris, M. Al; Multiyaningrum, Riska; Pandiriyan, Muhammad Tegar; Amrullah, Setiawan; Putri, Melfia Verahma; Nur, Rachmat Kahfiwan; Ramadhan, Abimanyu Arya; Khikman, Muhammad Alvaro; Widiyanti, Karin Dita; Watur, Annisa Cahyaningrum; Fabiola, Gwenda; Syaharani, Nabbila Dyah; Putra, Septian Malik; Ninu, Maria Febronia; Barlian, Seftia Amelia Rizki
Prosiding Seminar Nasional Unimus Vol 7 (2024): Transformasi Teknologi Menuju Indonesia Sehat dan Pencapaian Sustainable Development G
Publisher : Universitas Muhammadiyah Semarang

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Abstract

Desa Sidorejo, Kecamatan Karangawen, Kabupaten Demak, merupakan daerah agraris dengan mayoritaspenduduk bermata pencaharian sebagai petani. Dalam upaya meningkatkan regenerasi petani muda danmemperkenalkan teknologi pertanian modern, Tim Pengabdian Himpunan Mahasiswa StatistikaUniversitas Muhammadiyah Semarang melaksanakan pelatihan penggunaan alat transplanter dan powerthresher. Kegiatan ini diawali dengan koordinasi bersama pemerintah desa dan Dinas Pertanian setempat,diikuti dengan pembuatan materi pelatihan yang divalidasi oleh Balai Penyuluhan Pertanian. Sebanyak 20petani muda berusia 15 hingga 35 tahun dilibatkan dalam pelatihan ini. Hasil evaluasi menunjukkanpeningkatan signifikan dalam pengetahuan dan keterampilan peserta, meskipun tantangan keberlanjutanprogram tetap perlu diperhatikan. Pelatihan ini diharapkan dapat mendorong pertanian berkelanjutan dankesejahteraan ekonomi masyarakat. Kata Kunci : Pemberdayaan Masyarakat, Pertanian Modern, Regenerasi Petani Muda, Transplanter, PowerThresher.
FUZZY GEOGRAPHICALLY WEIGHTED CLUSTERING WITH OPTIMIZATION ALGORITHMS FOR SOCIAL VULNERABILITY ANALYSIS IN JAVA ISLAND Fadlurohman, Alwan; Utami, Tiani Wahyu; Amrullah, Setiawan; Roosyidah, Nila Ayu Nur; Dhani, Oktaviana Rahma
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/barekengvol19iss3pp1841-1852

Abstract

The Social Vulnerability Index (SoVI) measurement assesses social vulnerability. However, the measurement of SoVI can only describe the general conditions without being able to show which factors dominate. Therefore, a clustering approach has been proposed to characterise the dominant social vulnerability factors. Fuzzy Geographically Weighted Clustering (FGWC) is a method that works for this purpose. FGWC is an extension of the Fuzzy C-Means algorithm, which involves geographical influences in calculating membership values. However, the FGWC method is sensitive because the initial initialisation to determine the centroid is randomised, and it will affect the cluster quality. This research uses a metaheuristic approach to overcome the weakness of FGWC by using Particle Swarm Optimisation (PSO) and Artificial Bee Colony (ABC). This study aims to cluster districts/cities in Java Island using the PSO-FGWC and ABC-FGWC methods based on social vulnerability variables and determine the dominant factors of social vulnerability in each region. Optimum cluster selection uses the index of the largest Partition Coefficient (PC) and the smallest Classification Entropy (CE). Clustering social vulnerability in Java Island resulted in the best clustering using the ABC-FGWC method with 5 optimum clusters based on the PC and CE index values of 0.343 and 1.298, respectively. This research found that social vulnerability exists in each region of Java Island. Cluster 1, consisting of 19 districts/cities, is characterized by vulnerabilities in demography and education. Cluster 2, consisting of 33 districts/cities, is characterized by demographic and health vulnerabilities. Cluster 3, which consists of 24 districts/cities, is dominated by education and economic vulnerability factors. Cluster 4, consisting of 14 districts/cities, has the highest social vulnerability characteristics on the unemployment rate and the proportion of house rent. The last one, cluster 5, consists of 29 districts/cities and has a vulnerability problem in the population growth variable.
Co-Authors Alwan Fadlurohman Barlian, Seftia Amelia Rizki Dhani, Oktaviana Rahma Fabiola, Gwenda Fadillah, Muhammad Reza Fauzi, Fatkhurokhman Khikman, Muhammad Alvaro M. Al Haris Multiyaningrum, Riska Ninu, Maria Febronia Nur, Rachmat Kahfiwan Pandiriyan, Muhammad Tegar Putra, Septian Malik Putri, Melfia Verahma Ramadhan, Abimanyu Arya Roosyidah, Nila Ayu Nur Syaharani, Nabbila Dyah Tiani Wahyu Utami Watur, Annisa Cahyaningrum Widiyanti, Karin Dita