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All Journal MANAJEMEN HUTAN TROPIKA Journal of Tropical Forest Management Journal of Informatics Management and Information Technology
Ranjani
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Agriculture, Biological Sciences & Forestry Computer Science & IT

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Penerapan Teknik Neural Network dalam memprediksi Perkembangan Impor Kelompok Industri Tekstil dengan Metode Backpropagation Ranjani; Suci Cahya Mita; Agus Perdana Windarto
Journal of Informatics Management and Information Technology Vol. 3 No. 1 (2023): January 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v3i1.252

Abstract

The aim of this research is to analyze the development of the textile industry group in Indonesia using Artificial Intelligence. The analysis is conducted through a predictive model that will be used to predict the import development of the textile industry group. The dataset is sourced from the Indonesian Central Bureau of Statistics through the website https://www.bps.go.id/. The technique used is neural network with backpropagation method, and the analysis is conducted using Matlab. Backpropagation is a training method that has a target to be sought. This method is also a multilayer method, which has input, hidden, and output layers. The research process consists of two stages, namely the training stage and the testing stage. Out of several architecture models tested (3-10-1, 3-25-1, 3-50-1, 3-80-1, and 3-100-1), the best architecture model obtained is 3-100-1 with an MSE of 0.000999996 and an accuracy value of 100 percent.
A Bibliometric Analysis on Public-Private Partnerships in Forest Management Using Bibliometrix R-Studio Sajida; Ranjani; Fajri, Afrizal
Jurnal Manajemen Hutan Tropika Vol. 32 No. 1 (2026)
Publisher : Institut Pertanian Bogor (IPB University)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.7226/jtfm.32.1.14

Abstract

The paper thereby joins the discussion on the fast-changing research landscape of public-private partnerships (PPPs) in forest management, providing a comprehensive bibliometric analysis. A dataset of 241 documents is retrieved from the Scopus database, whose analyses are done using advanced bibliometric tools available within the Bibliometrix package in R Studio. The study maps the intellectual structure of the field, identifies its key themes, and traces their evolution from 1987 to 2024. The bibliometric approach allows for the identification of core authors, influential journals, leading institutions, and geographical distribution of contributions, thereby painting a clear picture of the knowledge dynamics within the domain. The findings underline the central place PPP holds in the face of such global challenges as climate change, preservation of biodiversity, and sustainable development but bring into sharper focus the governance and institutional frameworks that underpin these partnerships. Special attention is paid to the policy discourses and academic debates surrounding PPP arrangements, especially in developing countries where forest governance is often contested. This paper identifies major emerging trends in future research, in particular, the integration of cutting-edge technologies like machine learning. It fills this critical gap with a holistic overview of the current state of the art in forest management PPPs, thus offering useful insights for researchers, policymakers, and practitioners who want to enhance the effectiveness of such partnerships in achieving sustainable environmental outcomes.
Co-Authors Agus Perdana Windarto Fajri, Afrizal Sajida Suci Cahya Mita