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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Community Development Journal: Jurnal Pengabdian Masyarakat Journal of Innovation Information Technology and Application (JINITA)
Sirli Fahriah
Politeknik Negeri Semarang
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Public Health

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Systematic Literature Review: Current Products, Topic, and Implementation of Graph Database Adhy Rizaldy; Sirli Fahriah; Nahrun Hartono
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 7, No 1 (2021): April
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v7i1.19007

Abstract

Planning, developing, and updating software cannot be separated from the role of the database. From various types of databases, graph databases are considered to have various advantages over their predecessor, relational databases. Graph databases then become the latest trend in the software and data science industry, apart from the development of graph theory itself. The proliferation of research on GDB in the last decade raises questions about what topics are associated with GDB, what industries use GDB in its data processing, what the GDB models are, and what types of GDB have been used most frequently by users in the last few years. This article aims to answer these questions through a Literature Review, which is carried out by determining objectives, determining the limits of review coverage, determining inclusion and exclusion criteria for data retrieval, data extraction, and quality assessment. Based on a review of 60 studies, several research topics related to GDB are Semantic Web, Big Data, and Parallel computing. A total of 19 (30%) studies used Neo4j as their database. Apart from Social Networks, the industries that implement GDB the most are the Transportation sector, Scientific Article Networks, and general sectors such as Enterprise Data, Biological data, and History data. This Literature Review concludes that research on the topic of the Graph Database is still developing in the future. This is shown by the breadth of application and the variety of new derivatives of GDB products offered by researchers to address existing problems.
PELATIHAN PEMBUATAN VIDEO MENGGUNAKAN KINEMASTER DI SMK ROBBI RODLIYYA Amran Yobioktabera; Muhammad Irwan Yanwari; Sirli Fahriah; Wiktasari Wiktasari; Aisyatul Karima; Bagus Yunanto; Tahan Prahara; Efrilia Marifatul Khusna; Achmad Fahrul Aji
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 2 No. 2 (2021): Volume 2 Nomor 2 Tahun 2021
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v2i2.1736

Abstract

Seiring dengan perkembangan teknologi, pengembangan konten video sebagai sebuah bidang pekerjaan menjadi salah satu bidang yang memiliki potensi dalam menyerap tenaga kerja yang belum teralokasikan. Setiap bidang kerja tentunya memerlukan kompetensi yang sesuai dengan bidang yang dituju. Untuk mendukung bidang kerja pengembangan konten video tentunya diperlukan pelatihan dalam pembuatan konten video. SMK Robbi Rodliyya merupakan sekolah yang berfokuskan pada bidang multimedia. Bidang yang menjadi fokus pada SMK ini adalah media gambar dimana siswa mendapatkan pengajaran untuk membuat brosur, banner, dan lainnya menggunakan perangkat lunak pengolahan gambar. Hal ini menyebabkan ketika industri berkembang pada bidang konten video kesulitan dalam penyesuaian kemampuan siswa dalam memenuhi tuntutan perkembangan industri, sehingga perlu dilakukan eksplorasi dan pengembangan wawasan pada bidang pembuatan konten video. Metode yang digunakan pada kegiatan ini meliputi pendampingan pelatihan pembuatan video menggunakan Kinemaster yang terdiri dari empat aktivitas yaitu perencanaan, analisis, implementasi dan evaluasi. Luaran dari pengabdian ini berupa (3) teknologi tepat guna; dan (2) jasa. Hasil pengabdian ini mampu membantu meningkatkan kemampuan siswa dalam pembuatan video dengan menggunakan software Kinemaster. Selain itu dengan adanya pelatihan ini akan sangat membantu para siswa mengembangkan pembuatan konten digital terutama dalam proses pembelajaran.
Gold Price Forecasting using Time Series Modeling on a Web Platform Dwi Ratna Puspita Sari; Sirli Fahriah; Kurnianingsih; Santi Purwaningrum
Journal of Innovation Information Technology and Application (JINITA) Vol 7 No 2 (2025): JINITA, December 2025
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/4p33wz16

Abstract

Gold is one of the most favored investment instruments due to its stability and its ability to preserve value against inflation. However, its price movements are volatile and influenced by various global economic factors, currency exchange rates, and geopolitical conditions, making gold price forecasting a significant challenge. This study aims to develop a gold price forecasting system using the Long Short-Term Memory (LSTM) algorithm, a variant of the Recurrent Neural Network (RNN) that excels in processing time-series data. The dataset consists of historical daily gold buying and selling prices from 2015 to 2025, collected from Yahoo Finance, Logam Mulia, and the official website of Bank Indonesia. The modeling process follows the CRISP-DM methodology, which includes business understanding, data preparation and exploration, modeling, and evaluation stages. Time Series Cross Validation (TSCV) is used to validate the model. LSTM performance is compared with other models such as GRU, CNN-1D, and Simple RNN to identify the best-performing architecture. Evaluation results indicate that LSTM achieved the highest performance with an R² score of 0.99 for selling prices and 0.98 for buying prices on the final test dataset. The system is deployed online, making it accessible in real-time. This research is expected to assist investors, financial analysts, and the general public in making smarter investment decisions based on valid historical data and advanced forecasting technology.
Co-Authors Achmad Fahrul Aji Adhy Rizaldy Aisyatul Karima Amran Yobioktabera Bagus Yunanto Dwi Ratna Puspita Sari Efrilia Marifatul Khusna Kurnianingsih, - Muhammad Irwan Yanwari Nahrun Hartono Prahara, Tahan Santi Purwaningrum Wiktasari Wiktasari