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Perbandingan Metode ARIMA dan Fuzzy Time Series dalam Peramalan Harga Eceran Daging Sapi di Indonesia Amalani, Mukhamad Zulfa Bakhtiar; Santoso, Nugroho Adhi; Syefudin, Syefudin
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 3 (2025): Agustus - October
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i3.2283

Abstract

Peramalan harga eceran daging sapi menjadi krusial dalam menjaga stabilitas pangan dan mendukung kebijakan ekonomi di Indonesia. Penelitian ini bertujuan untuk membandingkan akurasi metode ARIMA dan Fuzzy Time Series (FTS) Chen dalam memprediksi harga eceran daging sapi di 34 provinsi Indonesia. Metode yang digunakan bersifat kuantitatif-komparatif dengan menerapkan kedua model pada data deret waktu tahunan periode 2020–2024, kemudian dievaluasi menggunakan metrik MAE, RMSE, dan MAPE. Hasil penelitian menunjukkan bahwa metode Fuzzy Time Series Chen memiliki performa lebih baik dibandingkan ARIMA dengan nilai MAE sebesar 3514,15, RMSE sebesar 5518,69, dan MAPE sebesar 2,57%, sedangkan ARIMA menghasilkan MAE sebesar 8523,43, RMSE sebesar 10462,26, dan MAPE sebesar 6,28%. Temuan ini menunjukkan bahwa pendekatan non-linier berbasis logika fuzzy lebih efektif dalam menangani data harga yang fluktuatif, sehingga metode FTS Chen layak dijadikan alternatif unggulan untuk pengembangan sistem prediksi harga komoditas pangan strategis di masa mendatang.
Development of mobile applications for IoT-based room temperature monitoring and control Murtopo, Aang Alim; Amalani, Mukhamad Zulfa Bakhtiar; Syefudin, Syefudin; Gunawan, Gunawan
Jurnal Mandiri IT Vol. 13 No. 1 (2024): July: Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v13i1.309

Abstract

The Internet of Things (IoT) has become one of the most significant technologies, offering a wide range of innovative solutions to improve efficiency and convenience in various aspects of life. One important application of IoT is in environmental management and control, especially room temperature. This research aims to develop a mobile application capable of monitoring and controlling room temperature with an easy-to-understand user interface and the ability to forecast future temperature needs. Research methods used include experimental approaches, data analysis, and model validation to ensure applications function optimally in real-world conditions. The results showed that the application developed was effective in monitoring room temperature conditions in real-time and was able to adjust the temperature quickly and accurately. The implication of this research is the improvement of user convenience and energy efficiency through the use of IoT technology in everyday life.