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MODEL PEMBERDAYAAN MASYARAKAT MELALUI PELATIHAN KECAKAPAN HIDUP BERBASIS KEUNGGULAN LOKAL DESA WISATA MANDIRI WANUREJO BOROBUDUR MAGELANG Sutarto, Joko; Mulyono, Sungkowo Edi; Nurhalim, Khomsun; Pratiwi, Hesty
Jurnal Penelitian Pendidikan Vol 35, No 1 (2018): April 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jpp.v35i1.15091

Tujuan penelitian ini adalah: (a) menganalis model pemberdayaan masyarakat melalui pelatihan kecakapan hidup berbasis keunggulan lokal desa wisata mandiri di Desa Wanurejo Borobudur Kabupaten Magelang yang diimplementasikan saat ini; dan (b) merumuskan model konseptual pemberdayaan masyarakat melalui pelatihan kecakapan hidup berbasis keunggulan lokal yang ideal dikembangkan, sehingga membawa dampak terhadap penanaman kewirausahaan masyarakat. Penelitian ini dirancang dengan desain penelitian deskriptif-kualitatif. Teknik pengumpulan data menggunakan wawancara, observasi, dan dokumentasi. Data yang telah terkumpul kemudian dianalisis dengan menggunakan analisis deskriptif kualitatif. Temuan Penelitian menunjukkan: (a) pemberdayaan masyarakat melalui pelatihan kecakapan hidup berbasis keunggulan lokal dilakukan dengan pemberian keterampilan kecakapan hidup berupa kecakapan pemandu wisata, kecakapan seni budaya/tari, dan kecakapan busana jawa/blangkon/wiru jarik; dan (b) model (konseptual) yang ditawarkan berorientasi penyempurnaan model yang telah dilakukan selama ini seperti telah dipaparkan di atas, dengan modifikasi dimulai dari identifikasi masalah dan kebutuhan pelatihan, pendampingan teknis, dan seterusnya pelibatan pelaku usaha mulai tahap perencanaan, pelaksanaan dan evaluasi kegiatan kecakapan hidup dan proses pemagangan, pendampingan manajemen, pemasaran, dan penggalian bantuan kegiatan dari pemerintah.

COMPARISON OF WEIGHT MATRIX IN HOTSPOT MODELING IN WEST KALIMANTAN USING THE GSTAR METHOD Pratiwi, Hesty; Imro'ah, Nurfitri; Huda, Nur'ainul Miftahul; Ayyash, Muhammad Yahya
Jurnal Matematika UNAND Vol 14, No 1 (2025)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.14.1.31-45.2025

This research aims to investigate the usefulness of the Generalized Space- Time Autoregressive (GSTAR) approach in predicting the number of fire hotspots in West Kalimantan Province. Specifically, the study compares the performance of the Queen contiguity method and the uniform weight matrix. Fires in the forests and on the land in West Kalimantan are severe problems that cause harm to the environment and other adverse effects. Data on fire hotspots were collected from four different regencies in West Kalimantan between January 2018 and March 2023 to provide the information used in this study. Compared to the uniform weight matrix, the study results reveal that the Queen contiguity weight matrix produces more accurate results. This is evidenced by the fact that the Root Mean Squared Error (RMSE) and Mean Absolute Deviation (MAD) values are lower in the Queen contiguity weight matrix. Based on these findings, more effective techniques for preventing forest and land fires are anticipated to be considered for planning purposes.

COMPARISON OF WEIGHT MATRIX IN HOTSPOT MODELING IN WEST KALIMANTAN USING THE GSTAR METHOD Pratiwi, Hesty; Imro'ah, Nurfitri; Huda, Nur'ainul Miftahul; Ayyash, Muhammad Yahya
Jurnal Matematika UNAND Vol. 14 No. 1 (2025)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.14.1.31-45.2025

This research aims to investigate the usefulness of the Generalized Space- Time Autoregressive (GSTAR) approach in predicting the number of fire hotspots in West Kalimantan Province. Specifically, the study compares the performance of the Queen contiguity method and the uniform weight matrix. Fires in the forests and on the land in West Kalimantan are severe problems that cause harm to the environment and other adverse effects. Data on fire hotspots were collected from four different regencies in West Kalimantan between January 2018 and March 2023 to provide the information used in this study. Compared to the uniform weight matrix, the study results reveal that the Queen contiguity weight matrix produces more accurate results. This is evidenced by the fact that the Root Mean Squared Error (RMSE) and Mean Absolute Deviation (MAD) values are lower in the Queen contiguity weight matrix. Based on these findings, more effective techniques for preventing forest and land fires are anticipated to be considered for planning purposes.

FOREST FIRE ANALYSIS FROM PERSPECTIVE OF SPATIAL-TEMPORAL USING GSTAR (p;λ_1,λ_2,…,λ_p) MODEL Pratiwi, Hesty; Imro'ah, Nurfitri; Huda, Nur'ainul Miftahul
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp1379-1392

West Kalimantan is particularly susceptible to the devastating effects of forest fires, among the natural disasters that have a significant impact. One of the indicators that can be used to identify forest fires is the presence of hotspots. The term "hotspot" refers to data that has both spatial and temporal characteristics. Using the Generalized Space-Time Autoregressive (GSTAR) model combined with the Queen Contiguity weight matrix, this research aims to model and forecast the confidence level of hotspots in Kubu Raya Regency and its surrounding areas. We chose the GSTAR model because of its ability to model spatial interactions between locations and temporal change patterns over time. According to NASA FIRMS, the data used in this study were confidence level hotspot data, covering the period from January 2014 to August 2024. To define locations for modeling, the study area was divided into grids measuring degrees. The maximum confidence level value in each grid was used to represent the highest potential fire risk. The research process consists of the following stages: data preparation, stationarity testing, calculation of the Queen Contiguity spatial weight matrix, identification of model orders based on STACF and STPACF plots, and estimation of model parameters to predict hotspot confidence levels. The GSTAR (3;1) model was selected as the best model because it satisfies the white-noise assumption and has a MAPE value of 14.78%. Based on the MAPE, the GSTAR (3;1) model can provide reasonably accurate predictions for the confidence level of fire points over the following three periods. The prediction results indicate a decline in the fire point confidence level across all locations during the following three periods. The findings of this study can support the optimization of resource allocation in the prevention of forest fires.

Forest Fires in Peatlands Analyzed from Various Perspectives: Spatial, Temporal, and Spatial-Temporal Huda, Nur'ainul Miftahul; Imro'ah, Nurfitri; Ayyash, Muhammad Yahya; Pratiwi, Hesty
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 2 (2025): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i2.28884

Peatland fires are characterized by the compaction of organic matter below the soil surface. If dry conditions occur, the organic matter can burn, making it difficult to extinguish the fire. This study aims to analyze peatland forest fires with three perspectives, namely temporal, spatial, and spatial-temporal. The data used is the confidence level data of hotspots in forest fires in Kubu Raya Regency, West Kalimantan from January 2014 to December 2023. The methodology used includes collecting fire data from satellite imagery and prepocessing the data. Furthermore, three different data analyzes were carried out, namely temporal, spatial, and spatial-temporal analysis. The results of the study obtained three perspectives, namely from the time period, handling of forest fire cases because they have an impact on the future as seen from the ARIMA model. Regarding spatiality, the distribution of hotspots spread to surrounding areas that were heavily affected by hotspots as seen from the contour map using Kriging interpolation. Finally, regarding spatiality and temporality, forest fire projections show that locations that are close together and have a history of being affected by forest fires have a strong potential for the distribution of forest fire cases as seen from the GSTAR space-time model.

A Hybrid ARIMA-Intervention Modelling for Forest Fire Risk in The Dry Season Imro'ah, Nurfitri; Huda, Nur'ainul Miftahul; Pratiwi, Hesty; Ayyash, Muhammad Yahya
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i2.36741

This study explores the time-related patterns of forest fires and assesses the impact of measures implemented during the dry season. Special focus is directed towards the effects of these interventions on the frequency and intensity of fires. This study highlights the importance of combining temporal analysis with spatial data to identify high-risk locations and optimize resource allocation for fire prevention. This study develops an ARIMA model to forecast fire risk before intervention. The findings indicate that integrating intervention factors into the ARIMA model will enhance the model's accuracy. The satisfactory MAPE values and the value data plots effectively demonstrate the data patterns. This method establishes a solid basis for predicting and reducing the risk of forest fires in the dry season, thereby enhancing the fire resilience of ecosystems considered at risk. The findings indicate that the onset of the dry season significantly elevates the risk of forest fires, especially in areas near bodies of water.

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