1. Autoregressive Moving Average and Generalized Autoregresive Moving Average in Covid-19 Confirmed Cases in Indonesia

   http://arxiv.org/abs/2202.11794v1 · arxiv

   Autoregressive moving average and generalized autoregressive moving average are often used in statistical modeling. This study uses this method because the method uses data from the previous period to model the data for the current period. In addition, the technique is often used in data prediction.

2. Education and Food Consumption Patterns: Quasi-Experimental Evidence from Indonesia

   http://arxiv.org/abs/2109.08124v1 · arxiv

   How does food consumption improve educational outcomes is an important policy issue for developing countries. Applying the Indonesian Family Life Survey (IFLS) 2014, we estimate the returns of food consumption to education and investigate if more educated individuals tend to consume healthier bundle

3. The Small World Phenomenon and Network Analysis of ICT Startup Investment in Indonesia and Singapore

   http://arxiv.org/abs/2102.09102v1 · arxiv

   The internet's rapid growth stimulates the emergence of start-up companies based on information technology and telecommunication (ICT) in Indonesia and Singapore. As the number of start-ups and its investor growth, the network of its relationship become larger and complex, but on the other side feel

4. Deep Interpretable Models of Theory of Mind

   http://arxiv.org/abs/2104.02938v2 · arxiv

   When developing AI systems that interact with humans, it is essential to design both a system that can understand humans, and a system that humans can understand. Most deep network based agent-modeling approaches are 1) not interpretable and 2) only model external behavior, ignoring internal mental

5. Healthy diets are affordable but often displaced by other foods in Indonesia

   http://arxiv.org/abs/2509.20203v1 · arxiv

   New methods for modeling least-cost diets that meet nutritional requirements for health have emerged as important tools for informing nutrition policy and programming around the world. This study develops a three-step approach using cost of healthy diet to inform targeted nutrition programming in In

6. Application of Executive Information System for COVID-19 Reporting System and Management: An Example from DKI Jakarta, Indonesia

   http://arxiv.org/abs/2108.09738v1 · arxiv

   SARS CoV-2 infection and transmission are problematic in developing countries such as Indonesia. Due to the lack of an information system, Provinces must be able to innovate in developing information systems related to surveillance of SARS CoV-2 infection. Jakarta Department of Health built a data m

7. Social media as political party campaign in Indonesia

   http://arxiv.org/abs/1406.4086v1 · arxiv

   Social media as a trend in the Internet is now used as a medium for political campaigns. Author explores the advantages and social media implementation of any political party in Indonesia legislative elections 2014. Author visited and analyzed social media used by the contestants, such as: Facebook,

8. Komodo: A Linguistic Expedition into Indonesia's Regional Languages

   http://arxiv.org/abs/2403.09362v2 · arxiv

   The recent breakthroughs in Large Language Models (LLMs) have mostly focused on languages with easily available and sufficient resources, such as English. However, there remains a significant gap for languages that lack sufficient linguistic resources in the public domain. Our work introduces Komodo

9. Replicable Benchmarking of Neural Machine Translation (NMT) on Low-Resource Local Languages in Indonesia

   http://arxiv.org/abs/2311.00998v1 · arxiv

   Neural machine translation (NMT) for low-resource local languages in Indonesia faces significant challenges, including the need for a representative benchmark and limited data availability. This work addresses these challenges by comprehensively analyzing training NMT systems for four low-resource l

10. SlimNets: An Exploration of Deep Model Compression and Acceleration

    http://arxiv.org/abs/1808.00496v1 · arxiv

    Deep neural networks have achieved increasingly accurate results on a wide variety of complex tasks. However, much of this improvement is due to the growing use and availability of computational resources (e.g use of GPUs, more layers, more parameters, etc). Most state-of-the-art deep networks, desp

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