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All Journal Enthusiastic : International Journal of Applied Statistics and Data Science Emerging Statistics and Data Science Journal
Cahyaningrum, Nafisah Hanan
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics

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Perbandingan Algoritma K-Means dan K-Medoids dalam Pengelompokan Peternakan Unggas di Daerah Istimewa Yogyakarta Tahun 2023: Perbandingan Algoritma K-Means dan K-Medoids dalam Pengelompokan Peternakan Unggas di Daerah Istimewa Yogyakarta Tahun 2023 Mas'udi, Nafisah Mas'ud; Cahyaningrum, Nafisah Hanan; Yotenka, Rahmadi; Suparna
Emerging Statistics and Data Science Journal Vol. 3 No. 2 (2025): Emerging Statistics and Data Science Journal
Publisher : Statistics Department, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/esds.vol3.iss.2.art16

Abstract

Peternakan merupakan salah satu sektor strategis dalam mendukung ketahanan pangan dan perekonomian daerah. Di kabupaten/kota se-Provinsi Daerah Istimewa Yogyakarta sektor pertenakan unggas memiliki kontribusi besar terhadap ekonomi lokal dan mendukung pendapatan masyarakat. Penelitian ini menganalisis berdasarkan jenis ternak, meliputi ayam ras pedaging, ayam ras petelur, ayam kampung pedaging, ayam kampung petelur, itik pedaging, dan itik petelur. Data sekunder dari Badan Pusat Statistik Provinsi Daerah Istimewa Yogyakarta tahun 2023 dianalisis menggunakan metode klaster non-hierarki dari penelitian ini didapat bahwa algoritma k-means dengan k sebanyak 2 lebih baik dalam mengelompokan peternakan unggas di Provinsi Daerah Istimewa Yogyakarta pada tahun 2023 dengan cluster 1 sebanyak 44 kecamatan dan cluster 2 sebanyak 34 kecamatan. Hasilnya diharapkan dapat mendukung pengembangan sektor unggas secara berkelanjutan untuk ketahanan pangan dan pertumbuhan ekonomi lokal.
Forecasting Production Growth of Micro and Small Textile Industries Using SARIMA Cahyaningrum, Nafisah Hanan; Yotenka, Rahmadi; Suparna
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 6 Issue 1, April 2026
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol6.iss1.art5

Abstract

Micro and small industry (MSME) is an industrial sector that includes small-scale businesses, both those with limited assets and turnover. MSME is an industrial business that is mostly labor-intensive and plays a role in creating jobs and driving the local economy. One of the largest industries in MSME is the textile industry. Production in the textile industry tends to fluctuate due to market demand, availability of raw materials, and economic conditions. Understanding the dynamics of market demand is very important for the government and business actors in making decisions. This study aimed to predict the growth of MSME production in the textile industry using the seasonal autoregressive integrated moving average (SARIMA) method. Several SARIMA models were used to predict the growth of MSME production in the textile industry. However, only the model with the smallest AIC value was selected to predict the growth of MSME production in the textile industry. The prediction results showed that fluctuations occurred in the growth of the textile industry in each period.
Co-Authors Mas'udi, Nafisah Mas'ud Suparna Yotenka, Rahmadi