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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) International Conference on Engineering and Technology Development (ICETD) DINAMIKA DOTCOM Jurnal EECCIS Jurnal Teknologi Informasi dan Ilmu Komputer AGRIVITA, Journal of Agricultural Science International Journal of Advances in Intelligent Informatics JOIV : International Journal on Informatics Visualization Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Journal of Robotics and Control (JRC)
Heru Nurwarsito
Universitas Brawijaya Malang
Aerospace Engineering Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Mechanical Engineering

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Enhancing Coffee Productivity and Carbon Stock in Agroforestry Systems Using the WaNuLCAS Model under Climate Change Nurwarsito, Heru; Suprayogo, Didik; Prayogo, Cahyo; Fitra, Ahmad Ali Yuddin
AGRIVITA Journal of Agricultural Science Vol 47, No 3 (2025)
Publisher : Faculty of Agriculture University of Brawijaya in collaboration with PERAGI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17503/agrivita.v47i3.4935

Abstract

The coffee-pine agroforestry model, where coffee is grown under shade trees, provides environmental benefits such as carbon sequestration and soil health improvement. However, maintaining carbon stocks over time is challenging due to climate change, which alters water and nutrient availability. Using the WaNuLCAS model, this study assessed system optimization under various climate scenarios, focusing on coffee yield, carbon stock, and biomass balance. The model simulates water and nitrogen cycling as well as coffee–pine interactions. The results showed that an increase in rainy season enhanced coffee growth, while applying Best Management Practice (BMP) led to a 44.64% higher coffee yield and a 4.52% increase in biomass production compared with the control. Conversely, low coffee (LC) with poor management increased carbon stock by 6.91% and biomass by 26.74%, the largest differences observed between treatments. This highlights trade-offs in land use performance. Previous studies mainly emphasized agroforestry’s contributions to carbon sequestration, biodiversity, and timber, with limited quantification of trade-offs between yield, carbon, and biomass under varying rainfall. By integrating site-specific calibration of the WaNuLCAS model, this study offers a novel approach showing how contrasting strategies (BMP vs. LC) differently optimize productivity and ecological services, guiding climate-resilient coffee agroforestry.
Predictive Analytics for Employability in Malaysian TVET with a Hybrid of Regression and Clustering Methods Mahdin, Hairulnizam; Nurwarsito, Heru; Baharum, Zirawani; Kamri, Khairol Anuar; Hassan, Azman; Haw, Su-Cheng; Arshad, Mohammad Syafwan
JOIV : International Journal on Informatics Visualization Vol 9, No 5 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.5.4516

Abstract

Graduate employability remains a high concern for Technical and Vocational Education and Training (TVET) institutions, particularly within Malaysia’s Technical University Network (MTUN), where producing industry-ready graduates is a central goal. While machine learning has transformed fields like healthcare and finance, its application in vocational education remains underexplored—particularly for employability prediction. This study addresses this gap by hybridizing decision trees and clustering to uncover non-linear patterns in student survey data. Guided by Human Capital Theory and SERVQUAL, which inform variable selection (e.g., technical skills as productivity investments), this study integrates multiple linear regression, decision tree regression, and K-Means clustering to identify significant predictors and uncover latent student groupings. Using a publicly available dataset of Likert-scale responses from MTUN students, technical skills and supervisory support consistently emerged as the most impactful employability predictors. Communication showed moderate influence, while training delivery and problem-solving exhibited variable effects depending on the modelling approach. Unlike regression, decision trees revealed non-linear interaction thresholds. For example, students with SVR < 3.5 and TS < 4.0 had 40% lower employability scores, suggesting targeted mentoring could yield disproportionate improvements. Clustering revealed three distinct student profiles, which could support data-driven interventions. This hybrid framework demonstrates the potential for integrating machine learning into institutional analytics for proactive support of employability.
Co-Authors Adaby, Resnu Wahyu Adhi Kurniawan Aidi Rahman Aji Prasetya Wibawa Alfrienza Tighfaraka Alifibioneri Ananda Adiyatma Putra Andy Wiranto Aprino, Dani Ardia Regita Pramesti ari kusyanti Armansyah Armansyah Arshad, Mohammad Syafwan Aryadna Nareindra Atiqo Tuzumah Baharum, Zirawani Barlian Henryranu P Barlian Henryranu Prasetio Bekti Widyaningsih Bintang Mada Suharsono Bisma Arie Yaqudsa Bisma Prasetya Cahyo Prayogo, Cahyo Cindy Zefira Afiani Denny Sagita Rusdianto Denny Sagita Rusdianto Desman Desman Devano Mirza Nugroho Didik Suprayogo Dwiki Ansarullah Ervani Sofyana Putra Fathul Hakim Fedro Jordie T. H. Simangunsong Fegi Eriyani Ferdi Cezano Santosa Fernanda Yerisha Hartinah Ridwan Firlhi Kurniawan Firstian Satya Yulihardi Fitra, Ahmad Ali Yuddin Galeh Prehandayana Getdra Saragih Sumbayak Guntur Wahyu Pamungkas Hairulnizam Mahdin, Hairulnizam Hassan, Azman Herdian Zend Komara I Putu Krisna Yoga Tanaya Imam Cholissodin Imam Cholissodin Kamri, Khairol Anuar Kasyful Amron Kharisma Fadillah Kuni Yustika Dewi M. Fatkur Rohman Made Widya Anjani Mahendra Data Maulana Yoga Wiyananta Mirsha Akbar Muhamad Alfarisi Muhamad Romdoni Rachman Wijaya Muhammad Arhangga Satriawan Muhammad Isman Suga Muhammad Rifqi Fauzi Muhammad Rizqi Fauzi Naufal Hilmi Ni Luh Irma Arini Niar Ariati Novanto Yudistira Nurul Azmi Nurul Hidayat Oakley, Simon Pradana, Kevin Dion Andre Pramukantoro, Eko Sakti Priyambadha, Bayu Purnomo Budi Santoso Purnomo Budi Santoso Putra, Mahdiaffan Dwi Putu Gede Sayoga Rakhmadhany Primananda Reynaldi Firman Tersianto Reza Andria Siregar Ricky Yohanes Ridwan Eko Prasetyo Rifqi Raditya Wibowo Rifqi Zumadilla Pratama Rika Yunitarini Riksa Suta Adji Riski Manta Simanjorang Rizal Fahturrizqi Salman Al Farizi Sandya Ratna Maruti Sarah Atemalem Octaviana Toruan Satrio Trimada Tarigan Seisarrina, Maulidya Larasaty Setyawan P. Sakti Setyawan Purnomo Sakti Shofura Naufal Rifiera Simon Oakley Sindy Alvionita Su-Cheng Haw Sukron Alfa Dani Setiawan Tesa Putri Cendani Tyo Enos Revan Gultom Velient Vinandha Verio Brika Sejahtera Wayan Firdaus Mahmudy Widhi Yahya Wijaya Kurniawan Winda Silviana Yuli Wahyuni