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Multiyaningrum, Riska
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Pelatihan Pertanian Modern untuk Meningkatkan Regenerasi Petani Muda di Desa Sidorejo Demak Fadillah, Muhammad Reza; Fauzi, Fatkhurokhman; Haris, M. Al; Multiyaningrum, Riska; Pandiriyan, Muhammad Tegar; Amrullah, Setiawan; Putri, Melfia Verahma; Nur, Rachmat Kahfiwan; Ramadhan, Abimanyu Arya; Khikman, Muhammad Alvaro; Widiyanti, Karin Dita; Watur, Annisa Cahyaningrum; Fabiola, Gwenda; Syaharani, Nabbila Dyah; Putra, Septian Malik; Ninu, Maria Febronia; Barlian, Seftia Amelia Rizki
Prosiding Seminar Nasional Unimus Vol 7 (2024): Transformasi Teknologi Menuju Indonesia Sehat dan Pencapaian Sustainable Development G
Publisher : Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Desa Sidorejo, Kecamatan Karangawen, Kabupaten Demak, merupakan daerah agraris dengan mayoritaspenduduk bermata pencaharian sebagai petani. Dalam upaya meningkatkan regenerasi petani muda danmemperkenalkan teknologi pertanian modern, Tim Pengabdian Himpunan Mahasiswa StatistikaUniversitas Muhammadiyah Semarang melaksanakan pelatihan penggunaan alat transplanter dan powerthresher. Kegiatan ini diawali dengan koordinasi bersama pemerintah desa dan Dinas Pertanian setempat,diikuti dengan pembuatan materi pelatihan yang divalidasi oleh Balai Penyuluhan Pertanian. Sebanyak 20petani muda berusia 15 hingga 35 tahun dilibatkan dalam pelatihan ini. Hasil evaluasi menunjukkanpeningkatan signifikan dalam pengetahuan dan keterampilan peserta, meskipun tantangan keberlanjutanprogram tetap perlu diperhatikan. Pelatihan ini diharapkan dapat mendorong pertanian berkelanjutan dankesejahteraan ekonomi masyarakat. Kata Kunci : Pemberdayaan Masyarakat, Pertanian Modern, Regenerasi Petani Muda, Transplanter, PowerThresher.
Forecasting the Volatility of Tuna Fish Prices in North Sumatra using the ARCH Method in the Period January - April 2024 Multiyaningrum, Riska; Amri, Ihsan Fathoni; Haris, M. Al; Salsabilla, Havinka Angel; Ginasputri, Heppy Nur Asavia; Sintya, Salsabila Dhea
Eigen Mathematics Journal Vol 7 No 2 (2024): December
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v7i2.236

Abstract

Tuna (Euthynnus affinis) is one of the most important fisheries commodities in Indonesia with significant economic value, especially in its contribution to fisheries export revenue. However, the price of tuna experiences significant fluctuations that can affect local and national economic stability. This study analyzes the daily price fluctuations of tuna in the North Sumatra market from January 1, 2024 to April 29, 2024 using a time series analysis approach. Daily price data were collected and analyzed to identify existing price patterns and volatility. The Autoregressive Conditional Heteroskedasticity (ARCH) model was selected to address the heteroscedasticity in the data, which suggests that the volatility of tuna prices can be well predicted based on past price behavior. The analysis steps include identifying the optimal ARCH model using the Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF), as well as testing parameter significance and normality assumptions to validate the model fit. The results show that the ARMA (1,0,0) model is the optimal one to model the price volatility of yellow tuna with the MAPE obtained of 2.382. compared to the ARMA-ARCH method with the MAPE value obtained of 2,747. Because it still contains heteroskedasticity effects, even though the results are good, the prediction results do not closely match the original data. The model is effective in improving price forecasting accuracy, which is important to support decision-making in risk management and economic planning in the fisheries sector. The findings contribute to understanding the dynamics of the yellowtail market and optimizing strategies for fisheries management.
Survival Analysis Using Kaplan-Meier and Cox Regression in Hypertension Patients at Kefamenanu Regional Hospital Khikman, Muhammad Alvaro; Multiyaningrum, Riska; Kholifah , Revika Inta Nur; Sa'adah , Lydia Nur; Safira, Elfina Latifah; Sarah, Albertus Dion; Amri, Ihsan Fathoni; Haris, M. Al
Eigen Mathematics Journal Vol 8 No 2 (2025): December
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v8i2.270

Abstract

Hypertension is a chronic disease with a steadily increasing global prevalence and is one of the leading causes of serious complications. Indonesia is among the countries with a high prevalence of hypertension, necessitating an understanding of the factors influencing patient treatment duration to enhance the effectiveness of healthcare services. This study aims to analyze differences in the survival rates of hypertensive patients at Kefamenanu Hospital based on gender. The Kaplan-Meier method was used to estimate patient survival rates, while Cox Proportional Hazards regression was used to evaluate the influence of gender on survival time. The Kaplan-Meier analysis results showed that female patients had a higher probability of survival than male patients during hospitalization. However, the Cox Proportional Hazards regression analysis indicated that this difference was not statistically significant. These findings suggest that while there are differences in survival patterns, gender is not the primary determinant of the duration of care for hypertensive patients. The results of this study are expected to provide input for hospitals in designing more effective care strategies that focus on other factors that may influence patient survival time.
Forecasting the Rupiah exchange rate against the US Dollar using the LSTM algorithm Multiyaningrum, Riska; Dawi, Herculianus Rowa; Hartanto, Raka Nurhaq Mulya; Haris, M. Al; Amri, Ihsan Fathoni
Journal Focus Action of Research Mathematic (Factor M) Vol. 8 No. 2 (2025): Vol. 8 No. 2 (2025)
Publisher : Universitas Islam Negeri (UIN) Syekh Wasil Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30762/f_m.v8i2.6530

Abstract

Exchange rates are a vital indicator of an economy's balance. The fluctuations of Indonesia's currency, the rupiah, against the USD influenced trade patterns, investment, and both monetary and fiscal policy. Exchange rate fluctuations affect international trade, investment, inflation, and overall economic stability. The high volatility of the Rupiah against the USD, driven by macroeconomic and monetary factors, has a significant impact on national economic policy, necessitating research that utilizes the latest data and adaptive models. To capture the nonlinear and complicated behavior of exchange rates, an advanced methodology for forecasting is needed. This journal utilizes the Long Short-Term Memory (LSTM) neural network model to forecast the exchange rate of the rupiah towards the dollar from March 1, 2022, up to February 28, 2025, in daily data. The data used in this research are sourced from www.bi.go.id, which provides the official daily exchange rate of USD to IDR. The Long Short-Term Memory method was chosen for modeling long-term dependencies within time series. After normalization, an 80/20 split is performed for training and testing on the dataset. The network runs optimization using three hidden layers with 50 neurons each and a batch size of 32 for 200 epochs. The optimal configuration, achieved through experimental trials, consisted of two hidden layers with 50 neurons, a batch size of 32, and 200 epochs. This is manifest in the fact that LSTM effectively captures movements in exchange rates, with an RMSE of 0.6226 and a MAPE of 0.3031%. This degree of accuracy enables the model to inform economic policy decisions based on data.
Co-Authors Amrullah, Setiawan Barlian, Seftia Amelia Rizki Dawi, Herculianus Rowa Fabiola, Gwenda Fadillah, Muhammad Reza Fauzi, Fatkhurokhman Ginasputri, Heppy Nur Asavia Haris, M. Al Hartanto, Raka Nurhaq Mulya Ihsan Fathoni Amri Khikman, Muhammad Alvaro Kholifah , Revika Inta Nur M. Al Haris Ninu, Maria Febronia Nur, Rachmat Kahfiwan Pandiriyan, Muhammad Tegar Putra, Septian Malik Putri, Melfia Verahma Ramadhan, Abimanyu Arya Sa'adah , Lydia Nur Safira, Elfina Latifah Salsabilla, Havinka Angel Sarah, Albertus Dion Sintya, Salsabila Dhea Syaharani, Nabbila Dyah Watur, Annisa Cahyaningrum Widiyanti, Karin Dita