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All Journal Journal of Computer Science and Engineering (JCSE) Trends in Applied Sciences, Social Sciences, and Education Civil and Military Cooperation Journal
Akbar, Ahmad Aldizar
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Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

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Accuracy Assessment of Monthly Rainfall Predictions using Seasonal ARIMA and Long Short-Term Memory (LSTM) Akbar, Ahmad Aldizar; Darmawan, Yahya; Wibowo, Arief; Rahmat, Hayatul Khairul
Journal of Computer Science and Engineering (JCSE) Vol 5, No 2: August (2024)
Publisher : ICSE (Institute of Computer Sciences and Engineering)

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Abstract

Hydro meteorological disasters are common in Indonesia. Rainfall predictions can help mitigate the impact of these disasters. This research aims to compare the accuracy of monthly rainfall prediction models using Seasonal Autoregressive Integrated Moving Average (SARIMA) and Long Short-Term Memory (LSTM) methods. The input data consists of monthly rainfall records from four locations: Sampali, Kualanamu, Belawan, and Tuntungan, located around Medan, North Sumatra. The dataset spans from 2000 to 2020, with training data from 2000 to 2018 and test data from 2019 to 2020. The accuracy assessment reveals that Belawan has the largest RMSE values for both models, measuring 27.68 mm for LSTM and 28.36 mm for SARIMA. Belawan records the highest MAE values, with LSTM and SARIMA yielding 5.65 mm and 5.79 mm, respectively. SARIMA models effectively capture general trends and seasonality in linear time series data with clear patterns but struggle with extreme changes or sharp fluctuations due to their reliance on linear relationships. In contrast, LSTMs are effective at modeling complex, non-linear relationships, making them suitable for capturing general trends, seasonal patterns, and more complicated variations in the data. Understanding the characteristics of the data is crucial before applying SARIMA or LSTM models.
Trauma Pasca Bencana dan Tantangan Intervensi Psikososial: Kajian Terhadap Respons Psikologis di Gunung Semeru Akbar, Ahmad Aldizar; Rahmat, Hayatul Khairul; Wahyuningtyas, Ayu
Trends in Applied Sciences, Social Science, and Education Vol. 3 No. 1 (2025): Juni
Publisher : PT Hakhara Akademia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71383/tase.v3i1.91

Abstract

The eruption of Mount Semeru in December 2021 had multidimensional impacts on affected communities, not only physically and economically but also psychologically. This article aims to examine various psychosocial intervention approaches for disaster survivors, particularly children and other vulnerable groups, in the aftermath of the eruption. This study employs a literature review method, analyzing nine national journal articles selected based on their relevance to the topic and intervention strategies. The findings indicate that methods such as trauma healing, play therapy, Psychological First Aid (PFA), and mental health nursing interventions are effective in reducing trauma symptoms and improving the psychological well-being of survivors. Participatory and community-based approaches, such as Asset-Based Community Development (ABCD) and Participatory Learning and Action (PLA), have shown more sustainable and contextually relevant outcomes. This study concludes that strengthening holistic and locally driven psychosocial interventions is essential in post-disaster recovery strategies.
Globalisasi dan Nasionalisme pada Generasi Z: Sebuah Studi Implikasi dalam Penerapan Nilai-Nilai Pancasila Hasrian, Hasrian; Akbar, Ahmad Aldizar; Raharjo, Didik Hariyadi
Civil and Military Cooperation Journal Vol. 1 No. 2 (2024): September
Publisher : PT. Civil Military Center

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Abstract

Indonesia adalah negara yang beragam, terdiri dari berbagai suku, agama, dan ras. Keberagaman ini harus dikelola dengan serius, salah satunya melalui peningkatan rasa nasionalisme. Nasionalisme berperan penting dalam memperkuat identitas bangsa sebagai satu kesatuan di tengah perbedaan. Namun, di era globalisasi ini, rasa nasionalisme di kalangan masyarakat, terutama pada Generasi Z, semakin menurun. Generasi Z memiliki karakteristik yang berbeda dibandingkan generasi lain. Oleh karena itu, penelitian ini bertujuan untuk mengeksplorasi pentingnya nasionalisme bagi Generasi Z di era globalisasi. Penelitian ini menggunakan metode studi literatur dengan pendekatan kualitatif deskriptif yang berbasis kajian kepustakaan. Hasil penelitian menunjukkan adanya keterkaitan erat antara nasionalisme, globalisasi, dan Generasi Z. Meningkatkan nasionalisme pada Generasi Z sangat penting karena mereka mudah terpengaruh oleh budaya dan ideologi asing. Salah satu cara efektif untuk melakukannya adalah dengan memanfaatkan teknologi sebagai sarana pengenalan budaya bangsa dan penanaman rasa cinta tanah air.
Co-Authors Arief Wibowo Ayu Wahyuningtyas Didik Hariyadi Raharjo Hasrian, Hasrian Hayatul Khairul Rahmat Yahya Darmawan