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All Journal Jurnal Hutan dan Masyarakat YUME : Journal of Management
Hamzah, Baginda
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Economics, Econometrics & Finance Health Professions Social Sciences

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Analisis Tingkat Keakuratan Prediksi Harga Saham dengan Metode Nonlinear Auto-Regressive Exogenous Model (NARX) Neural Network Berbasis Data Time Series: Studi Kasus pada Harga Saham PT. Bank Central Tbk. (BBCA) Hamzah, Baginda; Alimuddin, Ibriati Kartika; Alimuddin, Nur Hazimah; Farhanah Ramdhani Sumardi, Andi Raina Ananda Herdiyana, Audrey Michelle Wenny Yolanda,
YUME : Journal of Management Vol 8, No 3 (2025)
Publisher : Pascasarjana STIE Amkop Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37531/yum.v8i3.9446

Abstract

Penelitian ini menganalisis tingkat keakuratan prediksi harga saham PT. Bank Central Asia Tbk. (BBCA) menggunakan metode Nonlinear Auto-Regressive Exogenous Model (NARX) Neural Network berbasis data time series. Motivasi penelitian ini didasari oleh keterbatasan metode tradisional dalam memprediksi harga saham secara akurat, terutama dalam kondisi pasar yang volatil. Data penelitian menggunakan data sekunder harga saham BBCA periode Januari 2023 hingga Desember 2024 yang diperoleh dari Yahoo Finance, meliputi 470 data perdagangan harian dengan variabel open price, high price, low price, close price, dan volume perdagangan. Metodologi penelitian menerapkan preprocessing data menggunakan normalisasi min-max scaling, pembagian data menjadi 80% training, 10% validasi, dan 10% testing. Model NARX Neural Network dioptimalkan melalui metode trial-error untuk menentukan kombinasi parameter terbaik meliputi number of delay (1-5), algoritma pelatihan (trainlm, trainbr, trainscg), dan jumlah hidden neuron (1-10). Hasil penelitian menunjukkan bahwa konfigurasi optimal model menggunakan number of delay 4, algoritma Levenberg-Marquardt (trainlm), dan 8 hidden neuron dengan Mean Squared Error (MSE) sebesar 9.834,67. Evaluasi akurasi model menggunakan Mean Absolute Percentage Error (MAPE) menghasilkan nilai 1,018%, yang menurut kriteria Lewis (1982) tergolong highly accurate (MAPE < 10%). Temuan ini mengindikasikan bahwa metode NARX Neural Network efektif untuk prediksi harga saham BBCA dengan tingkat akurasi yang sangat tinggi.Kata Kunci: NARX Neural Network, Prediksi Harga Saham, BBCA, Time Series Analysis, Mean Absolute Percentage Error.
Recommendations for the “One Village, One Product” Strategy and Coffee Marketing Efficiency in Gowa Regency Hasannudin, Dian Ayu Lestari; Supratman; Alam, Syamsu; Makkarennu; Hamzah, Baginda
Jurnal Hutan dan Masyarakat VOLUME 17 NO 1, JULI 2025
Publisher : Fakultas Kehutanan, Universitas Hasanuddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24259/jhm.v17i1.44324

Abstract

The One Village One Product (OVOP) concept seeks to raise farmers’ income by promoting regionally distinctive commodities. In Topidi Village, South Sulawesi, coffee is widely cultivated and well suited for agroforestry systems, offering high market potential. However, farmer profits are reduced by inefficient marketing channels involving many intermediaries. This study analyzed marketing institutions and the efficiency of Arabica coffee marketing using Marketing Margin, Farmer’s Share, and Profit to Cost Ratio methods. Data from four marketing outlets showed that Outlet IV, where farmers sell directly to end users, achieved the highest marketing efficiency at 44 percent for ground coffee and the highest profit. Adopting the OVOP concept for coffee could help position it as a leading regional commodity by integrating production across areas with similar landscapes, thus strengthening local industry and boosting household incomes.
Integrasi Ekonomi Sirkular dalam Strategi Kolaboratif Pengelolaan Hutan Berbasis Masyarakat: Analisis Multi-dimensi Keberlanjutan di Indonesia Hamzah, Baginda; Hasannudin, Dian Ayu Lestari
Jurnal Hutan dan Masyarakat VOLUME 17 NO 1, JULI 2025
Publisher : Fakultas Kehutanan, Universitas Hasanuddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24259/jhm.v17i1.44325

Abstract

This study examines the integration of circular economy principles into community-based forest management (CBFM) collaborative strategies in Indonesia. Using a systematic literature review methodology, we analyzed 25 published studies and policy documents from 2015-2024, focusing on the interface between circular economy and collaborative forest governance. Results reveal that CBFM initiatives incorporating circular principles show enhanced resource efficiency and increased community income compared to conventional approaches. Four key integration models were identified: closed-loop forest product systems, regenerative agroforestry, waste-to-value conversion, and circular value chain partnerships. Critical success factors include adaptive governance mechanisms, multi-stakeholder knowledge platforms, and policy coherence across sectors. Significant implementation barriers persist, including capacity limitations, misaligned incentive structures, and inadequate market access. The study provides a multi-dimensional analytical framework and strategic recommendations for policymakers and practitioners seeking to advance sustainable forest management through circular economy integration in the Indonesian context.
Co-Authors Alimuddin, Ibriati Kartika Alimuddin, Nur Hazimah Farhanah Ramdhani Sumardi, Andi Raina Ananda Herdiyana, Audrey Michelle Wenny Yolanda, Hasannudin, Dian Ayu Lestari Makkarennu Supratman SYAMSU ALAM