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All Journal INTECOMS: Journal of Information Technology and Computer Science Jurnal Informasi dan Komputer Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Hafifah Bella Novitasari
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Mathematics Other

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Penerapan Layanan Cloud Server Secara Self-Service Menggunakan Model Finite State Automata Muchamad Bachram Shidiq; Windu Gata; Hafifah Bella Novitasari; Achmad Bayhaqy; hendra setiawan
INTECOMS: Journal of Information Technology and Computer Science Vol 5 No 1 (2022): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/intecoms.v5i1.3216

Abstract

Cloud computing merupakan teknologi yang memungkinkan pengguna untuk menggunakan layanan komputasi berbasis internet. Seiring dengan perkembangan teknologi cloud computing, beberapa instansi pemerintahan sudah melakukan implementasi cloud computing, salah satunya adalah PUSINTEK Sekretariat Jenderal Kementerian Keuangan. Salah satu layanan PUSINTEK dalam bidang cloud computing adalah menyediakan layanan cloud server berupa Virtual Machine (VM) yang dapat diakses oleh pengguna. Pada penyelenggaraan layanan dimaksud terdapat berbagai kesulitan, seperti pembuatan VM yang membutuhkan waktu lama dan adanya potensi kesalahan saat pembuatan VM. Penelitian ini akan membahas desain layanan dan rancangan sistem layanan cloud server secara self-service menggunakan model Finite State Automata dengan 7 (tujuh) state serta fungsi transisi yang berhasil menerima berbagai kemungkinan string input. Penerapan model FSA pada alur siklus layanan cloud server ini diharapkan dapat mempersingkat waktu pemenuhan layanan dan mengurangi potensi kesalahan pembuatan VM tersebut karena dilakukan secara mandiri oleh pengguna.
PENERAPAN FINITE STATE AUTOMATA PADA DESAIN VENDING MACHINE MASKER DAN HAND SANITIZER Ridwan Muhammad; Windu Gata; Hafifah Bella Novitasari; Laela Kurniawati; Sri Rahayu
Jurnal informasi dan komputer Vol 10 No 1 (2022): Jurnal Sistem Informasi dan Komputer yang terbit pada tahun 2022 pada bulan 04 (
Publisher : STMIK Dian Cipta Cendikia Kotabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35959/jik.v10i1.275

Abstract

The COVID-19 pandemic that has occurred for almost 2 years has hit this country caused by a mutation by the SARS-CoV virus, making changes in people's attitudes and behavior to become more concerned about cleanliness and health. In this case, the use of masks and hand sanitizers is very basic and a primary need during this pandemic. Vending Machine is a form of technological development that is used to sell or provide various kinds of products. Finite State Automata (FSA) is applied to vending machines for masks and hand sanitizers. FSA is a mathematical model that can accept input and output from the same state. The method used in this study consists of four stages, the first is knowledge of the FSA, the second is the design of the system diagram in this case the researcher uses the JFLAP application in making the FSA diagram, the third stage is the FSA test by describing the transition table and for the test it is still using JFLAP and the last stage is the VM design design process, in this case the researcher tries to design a VM using a display that is easy to use by buyers and designs the payment system with 2 methods, namely cash and digital money. The conclusion obtained from this study is that the application of the FSA concept to VM masks and hand sanitizers can make transactions of eight products, namely five types of mask products and three types of hand sanitizer products. this time trying to sell two different types of products.
Indonesian Government Revenue Prediction Using Long Short-Term Memory Mahmud; Windu Gata; Hafifah Bella Novitasari; Sigit Kurniawan; Dedi Dwi Saputra
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol. 14 No. 1 (2024): Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Pusat Penelitian dan Pengabdian Pada Masyarakat Sekolah Tinggi Manajemen Informatika dan Komputer AKBA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35585/inspir.v14i1.67

Abstract

Government revenue plays an important role in achieving national development goals. In the context of optimal state treasury management, accurate forecasts of government revenue are needed so that cash can be utilized optimally for the coming period. This study examines the appropriate method for predicting government revenue based on historical data from 2013 to 2022. It proposes applying the Long Short-Term Memory (LSTM) model for this purpose. Experiments show that the LSTM model, using two hidden layers and the right hyperparameters, can produce a Mean Absolute Percentage Error (MAPE) of 11.14% and a Root Mean Square Error (RMSE) of 15.43%. These results are better than those obtained using conventional modeling techniques such as Autoregressive Integrated Moving Average (ARIMA) and Seasonal Autoregressive Integrated Moving Average (SARIMA). The findings indicate that the LSTM model offers superior predictive accuracy and can significantly improve the management of government finances. By implementing this advanced predictive model, policymakers can make more informed decisions, enhancing the efficiency of resource allocation and contributing to the overall economic stability of the nation.
Co-Authors Achmad Bayhaqy Dedi Dwi Saputra Gata, Windu HENDRA SETIAWAN Laela Kurniawati Muchamad Bachram Shidiq Ridwan Muhammad Sigit Kurniawan Siti Helmyati SRI RAHAYU