Text Mining for Pest and Disease Identification on Rice Farming with Interactive Text Messaging

Costa, Edio da; Tjandrasa, Handayani; Djanali, Supeno

doi:10.11591/ijece.v8i3.pp1671-1683

Cited by 7 publications

(7 citation statements)

References 13 publications

(14 reference statements)

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“…Penggunaan cisine similarity dalam penelitian ini lebih baik disbanding dengan Euclidean dalam system temu kembali informasi klinik [10] demikain juga dengan [11] sama pada data klinik, khususnya data teks untuk kemiripan pasien. Menganalisis biogeografis dan ekologis asal dan pemilihan spesies arctic menggunakan teks mining dalam sebuah system expert-knowledge [12] penggunaan lainnya teks mining oleh [13]. Menggunakan metode pengeolahan teks untuk menganalisis data bio medis [14].…”

Section: Tinjauan Pustakaunclassified

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Abidin¹,

Sukmadinata²

2020

oai

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Section: Tinjauan Pustakaunclassified

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Abidin¹,

Sukmadinata²

2020

oai

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“…The stemming process in Indonesian is more complicated than English because there are variations of affixes that must be removed to get the base word [22]. The structure of Indonesian morphology has a higher level of complexity than English [23]. Besides Indonesian and English, stemming can be used in Arabic, as in research [24].…”

Section: ) Stemmingmentioning

confidence: 99%

Indonesian Words Error Detection System using Nazief Adriani Stemmer Algorithm

Yudhana¹,

Fadlil²,

Rosidin³

2019

IJACSA

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Stemming in each language has a different process and is determined according to the structure of the language. Stemming is mostly used as a complete step in the processing of words and phrases. There are many stemming algorithms available, and some used as a process for word processing. One function of stemming is to detect word errors in Indonesian. In this study, researchers created the Indonesian words error detection system using Nazief and Adriani algorithm. In the trials conducted, the system will accept text input obtained from the user. Then the system will preprocess the text. In this study, there are three stages of preprocessing, namely tokenization, case folding, and filtering. After the stages in preprocessing are finished, the system will call each word for the process of stemming. The results of the stemming will be compared with the base words available in the database. If it does not match, then the word is highlighted and is considered an error word. The first finding is the Nazief Adriani's algorithm can be able to detect words error until 100%. The second finding is the Nazief Adriani's algorithm also detect non-words error, the accuracy of detecting is 97.464%.

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“…Rice is considered by the Timorese population as the safest, sanitary food in the country. Rice consumption in East Timor is 135,000 tons per year, while farmers produce only 65 tons per year (Costa, Tjandrasa, & Djanali, 2018). Timorese rice consumption is approximately 112 kg, per capita, per year (Silva, Henriques, Jorge, & Narciso, 2012;Reis, 2020, In Nesbitt, Erskine, da Cruz & Moorhead, 2016.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Rice Value Chain in East Timor—The Consumers’ Perspective

Reis¹

2021

OJBM

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The consumer is an important factor to measure the performance of the rice agri-food value chain in East Timor. The purpose of this work is to identify the links in the rice chain, as well as to do the consumers' characterization, along with their segments. The methodologies used to represent the functioning of consumer preferences are cluster analysis, applied the K-Mean method, qualitative nature, exploratory factor analysis (EFA) and regression analysis. It was constituted a sample of 240 rice consumers in the county of Dili, capital of East Timor, and the questionnaire was conducted in the presence of the researcher. As consumers become more aware and experience higher purchasing standards, failure to consider their concerns will affect the profit of value chain participants, many of whom will need to update their practices. The result of KMO statistic, 0.781, shows that the quality of the analysis is good and the null hypothesis of Bartlett's test of sphericity was rejected. It was found the existence of two components, with the first having a greater weight of variables in relation to distance, transportation and availability, while the second component has a greater weight on variables related to quality, human benefit and healthy living. The first component was considered as Access and the second as Quality. Regarding the segmentation of consumers, we proceeded to create two distinct groups of rice consumers. Group I, composed of 171 individuals, and a Group II, with 69 individuals. Both groups considered rice to be the key food element, particularly important for the Timorese population.

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Text Mining for Pest and Disease Identification on Rice Farming with Interactive Text Messaging

Cited by 7 publications

References 13 publications

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Indonesian Words Error Detection System using Nazief Adriani Stemmer Algorithm

Analysis of the Rice Value Chain in East Timor—The Consumers’ Perspective

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