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All Journal Agricore: Jurnal Agribisnis dan Sosial Ekonomi Pertanian Unpad Prosiding Seminar Nasional Official Statistics
Siregar, Tiara Khorijah Hamid
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Humanities Computer Science & IT Economics, Econometrics & Finance Social Sciences

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Perbandingan Agglomerative Nesting dan K-Means untuk Klasterisasi Ketimpangan Gender berdasarkan Dimensi Kesehatan Reproduksi Raihannabil, Syfriza Davies; Ilyas, Hilmi Malika Atim; Shafira, Hervira Nur; Riani, May Alya; Hastin, Nadya Noor; Siregar, Tiara Khorijah Hamid
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.1977

Abstract

Gender inequality in Indonesia is ranked 4th out of 11 ASEAN countries with key problems such as high maternal mortality rates and teenage births. Indonesia ranks 3rd with the highest maternal mortality rate in Southeast Asia. Besides that, around 61% of provinces still have adolescent birth rates above the national average. This research uses clustering techniques to group provinces based on reproductive health dimensions to provide insight for policymakers. The two clustering methods used are Agglomerative Nesting (AGNES) and K-Means. The analysis found that the K-Means method was more effective in producing three clusters: 15 provinces in the medium category, 10 provinces in the high category, and 9 provinces in the low category. It is hoped that the results of this research can help the government make appropriate policies regarding improvements in the reproductive health dimensions to achieve gender equality in Indonesia, especially in provinces with high categories.
PERAMALAN PRODUKSI GULA TEBU DI INDONESIA MENGGUNAKAN MODEL HYBRID SARIMA (SARIMA-ANN) DALAM MENGUKUR CAPAIAN SWASEMBADA GULA 2025 Hermawan, Kadek Dody Kusuma; Cahyarani, Arista Ika; Siregar, Tiara Khorijah Hamid; Kartiasih, Fitri
Agricore Vol 10, No 1 (2025): Volume 10 No 1, Juni 2025
Publisher : Departemen Sosial Ekonomi Faperta Unpad dan Perhepi Komisariat Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/agricore.v10i1.62470

Abstract

AbstrakGula merupakan salah satu barang hasil industri yang termasuk kebutuhan esensial bagi masyarakat Indonesia. Penelitian ini bertujuan untuk menentukan model terbaik dalam meramalkan produksi gula di Indonesia, sekaligus meramalkan pencapaian swasembada gula nasional pada tahun 2025. Penelitian ini menggunakan data bulanan produksi gula di Indonesia dari periode Januari 2014 sampai Desember 2023, yang bersumber dari Badan Pusat Statistik. Data tersebut dimodelkan dengan model SARIMA (Seasonal Autoregressive Integrated Moving Average) dan hybrid SARIMA (gabungan Seasonal Autoregressive Integrated Moving Average dengan Artificial Neural Network) untuk menentukan model terbaik. Kedua model tersebut dapat memodelkan produksi gula di Indonesia yang memiliki pola musiman kuat. Namun, model hybrid SARIMA menghasilkan akurasi peramalan yang lebih baik dibandingkan model SARIMA. Oleh karena itu, model terbaik yang digunakan untuk meramalkan produksi gula di Indonesia adalah model hybrid SARIMA. Hasil peramalan dengan model tersebut pada dua tahun ke depan menunjukkan bahwa produksi gula nasional mengalami stagnan, sehingga belum mampu mencapai swasembada gula nasional pada tahun 2025.Kata kunci: Produksi gula, swasembada gula, SARIMA, hybrid SARIMA.AbstractSugar is one of the industrial goods that are essential to the Indonesian people. This study aims to determine the best model for forecasting sugar production in Indonesia and to assess the achievement of national sugar self-sufficiency by 2025. The study uses monthly data on sugar production in Indonesia from January 2014 to December 2023, sourced from Statistics Indonesia. The data were modeled using SARIMA (Seasonal Autoregressive Integrated Moving Average) and hybrid SARIMA models (a combination of SARIMA and Artificial Neural Network) to identify the best model. Both models were capable of capturing the strong seasonal pattern of sugar production in Indonesia. However, the hybrid SARIMA model produces better forecasting accuracy than the SARIMA model. Therefore, the hybrid SARIMA model was selected as the best model for forecasting sugar production in Indonesia. Forecast results for the next two years indicate stagnation in national sugar production, suggesting that Indonesia is unable to achieve sugar self-sufficiency by 2025.Keywords: Sugar production, sugar self-sufficiency, SARIMA, hybrid SARIMA.
Co-Authors Cahyarani, Arista Ika Fitri Kartiasih Hastin, Nadya Noor Hermawan, Kadek Dody Kusuma Ilyas, Hilmi Malika Atim Raihannabil, Syfriza Davies Riani, May Alya Shafira, Hervira Nur