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All Journal HAYATI Journal of Biosciences SISFO
M. Tanzil Furqon, M. Tanzil
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Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Engineering Industrial & Manufacturing Engineering

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Prediksi Nilai Mata Kuliah Mahasiswa Menggunakan Algoritma K-Apriori Muflikhah, Lailil; Yunita, W. Lisa; Furqon, M. Tanzil
SISFO Vol 6 No 2 (2017)
Publisher : Department of Information Systems, Institut Teknologi Sepuluh Nopember

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Abstract

Tujuan utama dari prediksi nilai mata kuliah adalah membantu mahasiswa mengambil mata kuliah pilihan secara tepat. Kebanyakan mahasiswa mengambil mata kuliah didasarkan pada jumlah mahasiswa mengambil matakuliah. Sekumpulan transkrip mahasiswa dapat dianalisis pola keterkaitan (association rule) antar nilai matakuliah. K-Apriori merupakan metode data mining untuk mencari pola keterkaitan nilai mata kuliah sehingga dapat digunakan memprediksi nilai mata kuliah lain. Tahapan utama metode ini meliputi mengelompokkan data menggunakan metode K-Means dan menemukan pola nilai mata kuliah menggunakan Apriori. Namun terdapat kekosongan nilai karena seluruh mata kuliah yang ditawarkan tidak diambil setiap mahasiswa. Oleh karenanya, dilakukan preprocessing data menggunakan Wiener Transformation sebelum dicari polanya.Pengujian didasarkan tingkat kemampuan akademik mahsiswa dengan minimum support dan confidence sebesar 10% dan lift ratio >1. Hasilnya, rule yang dibangkitkan dari IPK di bawah dan di atas rata-rata memiliki tingkat kesalahan sebesar 8.75% dan 8.5%. Sedangkan jika rule dibangkitkan dari IPK rata-rata memiliki kesalahan sebesar 11%.
Mangroves in Alas Purwo National Park, Indonesia: Diversity and Its Potential Carbon Services Samsu Rijal, Seftiawan; Furqon, M. Tanzil; Kadhafi, Muammar; Supriatin, Febriyani Eka; Aprillianto, Riqki Yoga
HAYATI Journal of Biosciences Vol. 31 No. 3 (2024): May 2024
Publisher : Bogor Agricultural University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.4308/hjb.31.3.589-595

Abstract

Mangroves are important ecosystems that help prevent global warming by storing carbon. A study in Alas Purwo National Park aimed to identify the species diversity and estimate the market value of total carbon from each mangrove species. The study used field sampling and diversity indexes. The study found that the study area has high diversity, with Shannon-Weiner, Margalef, and Pielou's Indexes of H' = 2.276, J = 0.949, and R = 1.453, respectively. Rhizophora apiculata was the dominant species with Above-Ground Carbon (AGC) and Below-Ground Carbon (BGC) stocks of about 34.73 Mg C Ha-1 and an economic value of $1,605, the highest among other species. The results of this study can help improve our understanding of the role of mangrove characteristics for both ecology and the economy.
Co-Authors Aprillianto, Riqki Yoga Lailil Muflikhah Muammar Kadhafi Samsu Rijal, Seftiawan Supriatin, Febriyani Eka Yunita, W. Lisa