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All Journal JURNAL ILMIAH MAHASISWA AGROINFO GALUH Jusikom: Jurnal Sistem Informasi Ilmu Komputer
-, Aripin
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Agriculture, Biological Sciences & Forestry Decision Sciences, Operations Research & Management

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ANALISIS RISIKO USAHA TERNAK AYAM BROILER DI DESA RAJADESA KECAMATAN RAJADESA KABUPATEN CIAMIS -, Aripin; Isyanto, Agus Yuniawan; -, Sudrajat
Jurnal Ilmiah Mahasiswa AGROINFO GALUH Vol 11, No 3 (2024): September 2024
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/jimag.v11i3.15628

Abstract

Penelitian ini bertujuan untuk mengevaluasi usaha peternakan ayam broiler, termasuk biaya, penerimaan, dan pendapatan dalam satu siklus produksi, serta menghitung R/C ratio dari usaha tersebut. Penelitian ini dilakukan pada bulan September 2023 hingga Maret 2024 di Desa Rajadesa, Kecamatan Rajadesa. Data yang digunakan meliputi data primer dan sekunder, dan pengumpulan data dilakukan melalui wawancara langsung dengan satu responden. Metode penelitian yang digunakan adalah metode kuantitatif dengan pendekatan studi kasus. Hasil penelitian menunjukkan total biaya (gabungan biaya tetap dan variabel) sebesar Rp. 482.132.500, penerimaan dari satu siklus produksi sebesar Rp. 517.900.000, dan pendapatan sebesar Rp. 35.767.500. R/C ratio untuk satu kali produksi adalah 1,07, yang berarti setiap Rp. 1 biaya yang dikeluarkan akan menghasilkan penerimaan sebesar Rp. 1,07. Koefisien variasi (CV) rata-rata sebesar 0,3 menunjukkan bahwa risiko usaha peternakan ayam broiler ini tergolong rendah karena nilainya ≤0,5. 
EARLY DETECTION OF BREAST CANCER USING THE K-NEAREST NEIGHBOUR (K-NN) ALGORITHM Panggabean, Refli Tiarma Ariani; Octavia, Ledy; Dwi, Noormala; -, Aripin
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 6 No. 2 (2023): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v6i2.3194

Abstract

ABSTRACT- Cancer is one of the Non-Communicable Disease groups whose growth and development are high-speed. One type of cancer is breast cancer (carcinoma mammae). Breast cancer is the leading cause of death for women. The first breast cancer cells can grow into tumors as large as 1 cm, spanning 8-12 years. The prevalence rate of breast cancer in Indonesia is 50 per 100,000 female population. The method used in this study uses the K-Nearest Neighbor (K-NN) algorithm by comparing k values, namely 3, 5, and 7. The dataset used was obtained from the UCI Machine Learning Repository with the Number of datasets after preprocessing, namely 653 data with a class consisting of benign tumors (benign) and malignant tumors (malignant). The variables used in this study take into account the variables of clump thickness, cell size uniformity, cell shape uniformity, marginal adhesion, single epithelial cell size, cell nucleus size, chromatin, normal cell nucleus, and mitosis. The results of the most influential classification for training and testing are using k = 3 with an accuracy of training and testing at a proportion of 70:30 of 83.8074% and 75%; the ratio of 80:20 is 84.6743% and 74.8092%; the percentage of 90:10 is 84.0136% and 84.6154%. Using the value of k = 3, the resulting gap between training and testing is similar.
Co-Authors Agus Yuniawan Isyanto Dwi, Noormala Octavia, Ledy Panggabean, Refli Tiarma Ariani Sudrajat -