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All Journal Journal of Degraded and Mining Lands Management INTAN Jurnal Penelitian Tambang
Valderama, Aldi Fariz
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Engineering

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PREDICTION OF SETTLEMENT AND LAND USE CHANGES ON MANSINAM ISLAND FROM 2025 TO 2031 USING THE CELLULAR AUTOMATA SIMULATION METHOD Valderama, Aldi Fariz; Taplo, Yulianto; Riansyah, Ardi; Habibi, Syavitra L. P.; Siagian, Adi Frianda; Popoi, Taufik Syahrul; Nasir, Muh. Irwana Segara; Iba, Amos; Laitupa, Karmila
INTAN Jurnal Penelitian Tambang Vol. 8 No. 2 (2025): INTAN: Jurnal Penelitian Tambang
Publisher : Program Studi S1 Teknik Pertambangan Fakultas Teknik Pertambangan dan Perminyakan Universitas Papua

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56139/intan.v8i2.337

Abstract

Indonesia, as an archipelagic country, faces development challenges on its small islands, including Mansinam Island. This study aims to predict settlement and land cover changes on Mansinam Island for the period 2025–2031. The data used were surface reflectance-corrected Sentinel-2 imagery with a spatial resolution of 10 meters. The imagery was acquired in 2019, 2022, and 2025. Land cover classification was performed using a supervised classification method with the minimum distance algorithm, achieving an accuracy of 87.82%. Land change prediction modeling was carried out through land use change analysis and simulation using the Cellular Automata (CA) and Artificial Neural Network-Cellular Automata (ANN-CA) models. The model produced a Percent of Correctness of 89.96%. The simulation results indicate that from 2025 to 2031 there will be no significant land change, with transformed land areas of 43.85 ha in 2025, 42.62 ha in 2028, and 42.64 ha in 2031. The results also show that the development rate on Mansinam Island tends to slow down.
Probabilistic slope stability of alluvial materials in Maruni River, Papua, using MC-LHS and Bishop-Spencer methods Lamma, Louis Hermanus; Setiawan, Arif; Valderama, Aldi Fariz; Aras, Firwansyah; Paradida, Yulia Putri
Journal of Degraded and Mining Lands Management Vol. 13 No. 3 (2026)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2026.133.10821

Abstract

The Maruni River in Manokwari Regency is one of the locations with sand and gravel resources, which are used as raw materials for infrastructure development. In the vicinity of the river, there is a slope with a steep inclination (>60°) and a height of approximately 8 m, which exhibits indications of minor landslides, suggesting potential instability. This condition necessitates a more comprehensive evaluation of slope stability. Therefore, this study aimed to evaluate slope stability using a probabilistic approach to obtain a more representative assessment of failure risk. The analysis was conducted using the Bishop and Spencer methods, combined with Monte Carlo (MC) and Latin Hypercube Sampling (LHS) techniques. Distribution tests were conducted for the cohesion, internal friction angle, and bulk density parameters of the original soil using Kolmogorov-Smirnov (KS), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). Based on the analysis, it is recommended to choose the Lognormal distribution for cohesion and internal friction angle, while the Normal distribution is more suitable for specific gravity. The findings indicate that the slope is marginally stable because its safety factor is approximately (close to) one, and the probability of failure does not decrease significantly. In stability assessment, the Spencer method provides a higher safety factor than the Bishop method; in addition, the LHS technique shows greater sensitivity than the MC method. Therefore, the application of probabilistic analysis with the integration of the Spencer method is considered more effective for evaluating slope stability.
Co-Authors Aras, Firwansyah Arif Setiawan Habibi, Syavitra L. P. Iba, Amos Laitupa, Karmila Lamma, Louis Hermanus Nasir, Muh. Irwana Segara Popoi, Taufik Syahrul Riansyah, Ardi Siagian, Adi Frianda Taplo, Yulianto Yulia Putri Paradida