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Serverless Computing: A Comparative Analysis of Cloud Run and Cloud Function Prices on Google Kubernetes Engine Cluster Node Management Google Cloud Putra, Christian Bayu Anggoro; Asmoro, Dimas Prasetyo Tegar; Yulianto, Akmal Budi
Jurnal Teknologi Informatika dan Komputer Vol. 11 No. 2 (2025): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v11i2.2780

Abstract

The advancement of cloud computing technology has revolutionized the way companies build and deploy applications, offering unprecedented flexibility, scalability, and efficiency. One of the most significant innovations in this space is serverless computing, which allows developers to build and run applications without managing the underlying server infrastructure. This model fundamentally changes the application development paradigm, shifting from static resource allocation to an event-driven model where resources are consumed only when needed (Sharma et al., 2021). The increasing adoption of serverless architectures has driven the need for detailed cost optimization strategies, particularly for automated infrastructure management tasks. This study examines the operational cost efficiency between Google Cloud Run and Google Cloud Functions. The study addresses the common need for programmatically managing cluster nodes within Google Kubernetes Engine. Solutions are developed and implemented using both serverless services to perform representative cluster management operations. A comprehensive analysis of pricing models, including resource consumption and invocation costs, is performed. Significant differences in operational costs are observed for this specific infrastructure automation scenario. The findings of this study provide clear guidance for architects and developers looking to minimize cloud spending through selecting the right platform.
Android-Based Stock Opname Application Development with SQLite and Firebase Maulana, Ishaq; Yasin, Verdi; Yulianto, Akmal Budi
Jurnal Teknologi Informatika dan Komputer Vol. 11 No. 2 (2025): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v11i2.2786

Abstract

Stocktaking, or stock data matching, is a crucial activity in inventory management within a company. Through this process, the stock data recorded in the system is compared with the physical conditions in the field (Jims, 2023). This activity not only aims to ensure data accuracy (Tarigan, 2021) but also serves as an integral part of internal control within the company's supply chain. PT Multilindo Surya Cemerlang is a company engaged in the distribution and sales of electronic goods. Stocktaking is a crucial component in maintaining the accuracy of a company's inventory data. However, at PT Multilindo Surya Cemerlang, this process is still performed manually by recording on paper and then re-entering it into a computer. This method is quite time-consuming and carries the risk of recording errors. Therefore, this study aims to develop an Android-based application that can assist the stocktaking process directly in the field. The application is designed with SQLite database support for local storage and Firebase for online data storage and synchronization. The development was conducted using the SDLC (System Development Life Cycle) model with a waterfall approach, encompassing the stages of requirements analysis, system design, implementation, testing, and maintenance. Trial results demonstrated that the application was able to assist staff in recording stock more quickly and accurately, as well as simplifying the overall inventory data recapitulation process.
Sistem Informasi Bank Sampah Induk Rawasar Suku Dinas Lingkungan Hidup Kota Administrasi Jakarta Pusat Berbasis Website Dengan Metode Design Thinking Gunawan, Iwan; Zulhalim, Zulhalim; Yulianto, Akmal Budi
COMSERVA : Jurnal Penelitian dan Pengabdian Masyarakat Vol. 4 No. 9 (2025): COMSERVA: Jurnal Penelitian dan Pengabdian Masyarakat
Publisher : Publikasi Indonesia

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Abstract

Pelaksanaan Penelitian pada Bank Sampah Induk Rawasari Jl. Rawasari Selatan No. 35 RT. 016 RW. 02 Kel. Cempaka Putih Timur Kec. Cempaka Putih Kota Administrasi Jakarta Pusat, dibawah bimbingan (Pembimbing I : Zulhalim, S. Kom, M.TI) dan (Pembimbing II : Akmal Budi Yulianto, ST, MM). Untuk pencatatan dan pelaporan pada Bank sampah Induk Rawasari Suku Dinas Lingkungan Hidup masih bersifat manual biasanya menggunakan catatan pada selembar kertas atau mengirimkan email dengan demikian ada kemungkinan data pencatatan dan laporan tersebut hilang atau tercecer. Untuk itu, sistem informasi ini dibuat sebagai solusi agar data laporan tersebut terdata dengan baik dengan harapan dari penelitian ini adalah memilikinya data informasi laporan yang lebih efektif dan efisien. Dengan adanya aplikasi pelaporan ini dapat membantu pencatatan laporan bank sampah secara digital. Metodologi penelitian yang digunakan pada Sistem Informasi Bank Sampah ini adalah dengan metode wawancara, observasi, studi pustaka, dan literature sejenis. Sedangkan untuk pengembangan dan implementasi pemodelan sistemnya menggunakan bahasa pemograman php dan database managemen MySQL, Metode yang digunakan dalam penelitian yaitu Design Thinking
PERAN KECERDASAN BUATAN DALAM MENDORONG DIGITALISASI UMKM DI DKI JAKARTA Yulianto, Akmal Budi
Journal of Information System, Applied, Management, Accounting and Research Vol 9 No 4 (2025): JISAMAR (Journal of Information System, Applied, Management, Accounting and Resea
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jisamar.v9i4.2139

Abstract

Penelitian ini bertujuan untuk menganalisis peran kecerdasan buatan (AI) dalam mendorong digitalisasi UMKM di DKI Jakarta. UMKM memiliki kontribusi signifikan terhadap perekonomian nasional, menyumbang 61% terhadap PDB Indonesia dan menyerap lebih dari 117 juta tenaga kerja. Namun, adopsi digital masih menghadapi tantangan besar. Data dari BPS, Kemenkop UKM, Kominfo, KI DKI, dan Dinas PPUKM DKI Jakarta menunjukkan tren peningkatan jumlah UMKM yang memanfaatkan teknologi digital, meskipun masih relatif rendah. AI berpotensi besar membantu UMKM dalam desain produk, analisis pasar, segmentasi konsumen, serta menjaga mutu produk agar dapat bersaing di pasar global. Benchmarking dengan Tiongkok, Korea Selatan, dan Singapura menunjukkan bahwa penerapan AI dapat mempercepat transformasi digital UMKM. Penelitian ini menekankan perlunya sinergi pemerintah, akademisi, dan swasta untuk menciptakan ekosistem UMKM berbasis AI yang berdaya saing.