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Journal : Journal of Advanced Computer Knowledge and Algorithms

The Use of Brown's Double Exponential Smoothing Method to Predict Harvest Yields in Horticultural Crops Mutiara, Mutiara; Fuadi, Wahyu; Maryana, Maryana
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 4 (2024): Journal of Advanced Computer Knowledge and Algorithms - October 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i4.17806

Abstract

Agriculture stands as a pivotal sub-sector within the economy of North Aceh. Among its primary commodities are horticultural crops, encompassing the cultivation of vegetables, fruits, medicinal plants, and ornamental flora. In endeavors to boost agricultural productivity and efficiency, the utilization of harvest prediction methodologies has grown increasingly indispensable. This study relies on historical harvest data spanning from 2017 to 2022 to forecast crops such as leafy greens, fruits, and medicinal plants. The selected plants for prediction include spinach, water spinach, cucumber, banana, durian, rambutan, ginger, lesser galangal, and turmeric. Data analysis employs Brown's double exponential smoothing method, selecting the α (alpha) parameter that minimizes the Mean Absolute Percentage Error (MAPE) for accurate forecasting. Spinach is anticipated to yield 1239.9508 quintals, with an α (alpha) parameter of 0.9 and a MAPE of 38.46%. Water spinach is forecasted to yield 2069.75 quintals, with an α (alpha) parameter of 0.5 and a MAPE of 18.14%. Cucumber is projected to yield 1023.22432 quintals, with an α (alpha) parameter of 0.4 and a MAPE of 31.51%. Consequently, the highest projected yield is for water spinach at 2069,75 quintals.
Devayan Language Translator Dictionary Application Using the Levenshtein Distance Method on Android Faturrahman, Puja; Ardian, Zalfie; Maryana, Maryana
Journal of Advanced Computer Knowledge and Algorithms Vol. 2 No. 2 (2025): Journal of Advanced Computer Knowledge and Algorithms - April 2025
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v2i2.20124

Abstract

Indonesia is a country with a rich diversity of regional languages. Language is the primary tool of human communication, serving as a means to establish social relationships in daily life and as a medium for conveying information. One of the regional languages in Indonesia is Devayan, the native language of the people in Simeulue Regency. This language is used as a daily communication medium by the local residents. As one of Indonesia's archipelagic regions, Simeulue Island has various tourism potentials that attract tourists, workers, and students from outside the region. However, communication barriers often occur when visitors to Simeulue Island face difficulties interacting with the local community. Additionally, the language is gradually fading with the passage of time, as many young generations on Simeulue Island now have limited understanding of their regional language. Therefore, a dictionary application is needed to translate vocabulary from Devayan to Indonesian and vice versa. The Levenshtein Distance method is applied to the application's search feature, which has proven capable of correcting errors in input words and suggesting the closest words to users with an accuracy rate of 80.95%.