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All Journal Jurnal Solum Journal of Artificial Intelligence and Digital Business
Solfianti, Maidia
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Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science

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Implementation of Simple and Weighted Moving Average for Forecasting Tela-Tela Production in MSME X Sariati, Sariati; Pratama, Borneo Satria; Albar, Ferdy; Sitio, Dea Yolanda Putri; Riandry, Dimas Dwika; Antonio, Marcho; Januarti, Sri; Aliansyah, Bayu Rimba; Sutignya, Th. Candra Wasis Agung; Solfianti, Maidia; Erwan, Erwan; Sembiring, Loko Jeremia
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 4 (2026): November - January
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i4.5205

Abstract

Accurate production forecasting is essential for micro, small, and medium enterprises (MSMEs) to support effective production planning, inventory control, and decision-making. This study evaluates the performance of the Simple Moving Average (SMA) and Weighted Moving Average (WMA) methods in forecasting tela-tela production demand at MSME X using different historical period lengths. Production data from November 2023 to October 2024 were analyzed, and forecasting accuracy was assessed using the Mean Absolute Percentage Error (MAPE). The results indicate that forecasting accuracy varies depending on both the length of the moving average period and the weighting scheme applied. The WMA model with a 4-period window (n = 4) achieved the highest accuracy, producing the lowest MAPE value of 8.36%, which is classified as highly accurate. The SMA model with n = 4 also demonstrated good performance, with a MAPE value of 14.40%. Meanwhile, models employing longer historical periods (n = 8) yielded MAPE values of 16.20% for WMA and 19.82% for SMA, both falling within the good forecasting performance category but exhibiting lower responsiveness to recent demand changes. These findings highlight that shorter historical periods, when combined with appropriate weighting, can more effectively capture recent demand patterns in dynamic production environments. Accordingly, the WMA method with a 4-period window is recommended for MSME X as a reliable and accurate approach to support production planning, optimize resource allocation, and reduce the risk of overproduction or stock shortages.  
The Evaluation of Land Suitability for Arabica Coffee Cultivation (Coffea arabica L.) in Nagari Koto Gadang Guguk, Solok Regency, West Sumatra Solfianti, Maidia; Gunadi
Jurnal Solum Vol. 23 No. 1 (2026)
Publisher : Departemen Ilmu Tanah dan Sumberdaya Lahan, Fakultas Pertanian Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jsolum.v23i1.315

Abstract

Arabica coffee (Coffea arabica L.) is one of the high economic value plantation commodities, where the level of production is largely determined by land suitability. Scientific information related to specific land suitability in potential areas, such as Solok Regency, is still minimal. This research was conducted in Nagari Koto Gadang Guguk, Gunung Talang District, West Sumatra, with the aim of assessing the level of land suitability for Arabica coffee cultivation. The research was conducted from August to November 2024 through field surveys, laboratory analysis, and Geographic Information System (GIS)-based mapping at a scale of 1:50,000. Analysis included soil physical characteristics (texture, effective depth, drainage), chemical properties (pH, organic carbon, cation exchange capacity, base saturation), as well as topography and climate factors. Results showed that the study land was dominated by dusty loam to dusty clay textures with medium to high C-organic content (2.68-3.12%), slightly acidic pH (5.50-6.18), medium-high CEC values (21.53-32.54 cmol kg-¹), and base saturation of 42.53-68.23%. From the evaluation results, four land units (SL1-SL4) were categorized as S3 class (marginally suitable) with the main constraints of excess rainfall (2,817-3,000 mm/year) and slope (9-40%). Meanwhile, SL5 is categorized as class N (unsuitable) due to drainage problems. The potential to increase land suitability is still open through the application of soil and water conservation, terrace construction, use of adaptive varieties, and improvement of soil and water management. The overall results confirm the importance of land suitability evaluation as a foundation for sustainable Arabica coffee management in the tropical highland region. Key words : Arabica coffee, land suitability, soil conservation, GIS
Co-Authors Albar, Ferdy Aliansyah, Bayu Rimba Antonio, Marcho Erwan Erwan, Erwan Gunadi Januarti, Sri Pratama, Borneo Satria Riandry, Dimas Dwika Sariati Sariati, Sariati Sembiring, Loko Jeremia Sitio, Dea Yolanda Putri Th. Candra Wasis Agung Sutignya