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All Journal The IJICS (International Journal of Informatics and Computer Science) Journal Of Biology Education Research (JBER)
Khairunnisa Khairunnisa
Universitas Pembangunan Panca Budi
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Environmental Science

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Morphological Structure of Upland Rice Varieties at Different Light Intensities Khairunnisa Khairunnisa
Journal Of Biology Education Research (JBER) Vol 3, No 1 (2022): Volume 3 nomor 1 Tahun 2022
Publisher : Program Studi Pendidikan Biologi FKIP Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (279.597 KB) | DOI: 10.55215/jber.v3i1.4938

Abstract

Increasing food self-sufficiency, especially rice grown as intercrops, requires attention to the development ofupland rice varieties that are shade-tolerant and capable of high production. The objective of this research tostudy about the mechanism of tolerance, morphological characters as characterizing tolerance to shade. Theresearch was carried out in Cengkeh Turi Binjai with an altitude of ± 32 meters above sea level, with soil pH;4.5, started from May to August 2018. The study used a split plot design with two factors. The first factorwas the light intensity, consist of: 100%, 75%, 50%, and 25%. The second factor consisted of 5 rice varieties,namely: Inpago 5, Lipigo 4, Inpago 8, Inpago 10, and Lipigo 2. The result of this study was an increase in thearea of the flag leaf with a decrease in sunlight intensity by 75%. The conclusion of this study is that thelower the intensity of sunlight, the lower the angle of the flag leaf and the thickness of the upland rice leaf.Keywords: light; upland rice; varieties
Morphological Structure of Upland Rice Varieties at Different Light Intensities Khairunnisa Khairunnisa
Journal Of Biology Education Research (JBER) Vol 3, No 1 (2022): Volume 3 nomor 1 Tahun 2022
Publisher : Program Studi Pendidikan Biologi FKIP Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55215/jber.v3i1.4938

Abstract

Increasing food self-sufficiency, especially rice grown as intercrops, requires attention to the development ofupland rice varieties that are shade-tolerant and capable of high production. The objective of this research tostudy about the mechanism of tolerance, morphological characters as characterizing tolerance to shade. Theresearch was carried out in Cengkeh Turi Binjai with an altitude of ± 32 meters above sea level, with soil pH;4.5, started from May to August 2018. The study used a split plot design with two factors. The first factorwas the light intensity, consist of: 100%, 75%, 50%, and 25%. The second factor consisted of 5 rice varieties,namely: Inpago 5, Lipigo 4, Inpago 8, Inpago 10, and Lipigo 2. The result of this study was an increase in thearea of the flag leaf with a decrease in sunlight intensity by 75%. The conclusion of this study is that thelower the intensity of sunlight, the lower the angle of the flag leaf and the thickness of the upland rice leaf.Keywords: light; upland rice; varieties
Analysis of E-Commerce Consumer Purchasing Patterns Using the Naïve Bayes Algorithm Khairunnisa Khairunnisa; Muhammad Iqbal
The IJICS (International Journal of Informatics and Computer Science) Vol. 10 No. 1 (2026): Maret
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v10i1.9531

Abstract

The rapid growth of e-commerce has generated a large volume of transactional data; however, its utilization is often limited to sales reports. In fact, transaction data holds significant strategic potential to be analyzed in order to understand customer purchasing patterns. This study aims to analyze consumer purchasing behavior in e-commerce by applying the Naïve Bayes algorithm as a probabilistic classification method. The dataset used in this research consists of 30 transaction records, including attributes such as purchase frequency, transaction value, product type, payment method, and promotion, with the purchasing decision (buy or not buy) as the class attribute. The research stages include calculating prior probabilities and conditional probabilities for each attribute with respect to the purchasing decision classes. The results indicate that the majority of transactions belong to the buy class with a probability of 0.63, while the not-buy class has a probability of 0.37. Purchase frequency and transaction value are identified as the most influential factors, where medium to high purchase frequency and medium to large transaction values show a strong tendency toward buying decisions. Furthermore, electronic products and non-cash payment methods, particularly e-wallets and credit cards, exhibit high probabilities associated with purchase decisions. Promotions also contribute positively to encouraging purchases, although they are not the sole determining factor. Overall, this study demonstrates that the Naïve Bayes algorithm is effective in identifying customer purchasing patterns and can support strategic decision-making in e-commerce businesses.
Co-Authors Muhammad Iqbal