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All Journal Syntax Jurnal Informatika Jurnal Informatika dan Teknik Elektro Terapan Journal of Information System JOURNAL OF APPLIED INFORMATICS AND COMPUTING INTECOMS: Journal of Information Technology and Computer Science J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Kreativitas PKM STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Systematics Jurnal Ilmiah Wahana Pendidikan J-SAKTI (Jurnal Sains Komputer dan Informatika) Innovative: Journal Of Social Science Research Jurnal INFOTEL
Asep Jamaludin
Universitas Singaperbangsa Karawang
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Health Professions Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Journal : STRING (Satuan Tulisan Riset dan Inovasi Teknologi)

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Implementasi Algoritme C4.5 untuk Prediksi Penanaman Cabai Merah Muhammad Syam Firdaus; Aji Primajaya; Asep Jamaludin
STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Vol 6, No 2 (2021)
Publisher : Universitas Indraprasta PGRI Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (860.144 KB) | DOI: 10.30998/string.v6i2.10378

Abstract

Chili has been the most widely grown plant in Indonesia because it can bear fruit and grow in the highlands and the lowlands. Every year the market demand for chili continues to increase, even the annual price of chili tends to increase as a result of reduced chili supply and less fulfilled market demand. Besides, the crop failure experienced by chili farmers cause inflation growth in 2020 as much as 0.31%, resulting from rising prices in the food sector, including the price of cayenne pepper and red chili. The fluctuations in chili prices are strongly influenced by weather, harvest season, trade policies and the accompanying momentum. According to the background, the purpose of this study is to predict chili planting using the C4.5 algorithm. First, the researchers collect weather and price data taken from DISPERINDAG, BMKG, use chili price data on the market as a dataset to be later preprocessed to eliminate missing values, data outliers and imbalance data and then make a model that can predict chili planting. The prediction results using the rule from the decision tree have an accuracy rate of 97.8% based on the calculation of the prediction using validation data as much as 95 data
Co-Authors Adrian Wibisono Agung Susilo Yuda Irawan Alma Apriliani Anissa Aidha Zulyani Apriade Voutama Carudin Chaerur Rozikin Didi Juardi Felix Sianturi Garno, Garno Hafiz Abdul Fatah Kurniawan Hendi Permana Heryana, Nono Indra, Jamaludin Intan Purnamasari Kamal Prihandani Kardo Trihandoko Miftahul Faizin Muhammad Budhiluhoer Muhammad Syam Firdaus shelladita fitriyani susilo Suparno Tawang Sahro Winanto Tesa Nur Padilah Thalita Meisya Permata Aulia Valerie Febriana Putri Indra Kusumawati Vina Yanuar Prasasti Wahyu Rudiansyah Yuyun Umaidah