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All Journal Journal of Computer Science and Informatics Engineering Jurnal Pustaka Data : Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer IJESPG (International Journal of Engineering, Economic, Social Politic and Government) journal Polygon: Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam JITCoS : Journal of Information Technology and Computer System
Diah Putri Kartikasari
Program Studi Ilmu Komputer Universitas Islam Negeri Sumatera Utara
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Social Sciences

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Pengaruh Internet of Things (IoT) Dalam Bidang Kesehatan Terhadap Masyarakat Umum Diah Putri Kartikasari; Tengku Syahvina Rival Dini; Puji Sri Alhirani; Pebi Mina Husania
IJESPG (International Journal of Engineering, Economic, Social Politic and Government) Vol. 1 No. 3 (2023)
Publisher : IJESPG (International Journal of Engineering, Economic, Social Politic and Government)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26638/ijespg.v1i3.29

Abstract

This study aims to determine the influence of the increasing development of the Internet of Things (IoT) in the health sector on the general public. This research uses a quantitative method based on an indirect survey of health and general correspondents. The research took place online for approximately 3 days. The subjects of this study included 12 correspondents, including 5 people from the health sector and 7 people from the general public. The results of the research conducted can be concluded that the Internet of Things (IoT) is very influential in the world of health. Abstrak Penelitian ini bertujuan untuk mengetahui pengaruh meningkatnya perkembangan Internet of Things (IoT) dalam bidang kesehatan terhadap masyarakat umum. Penelitian ini menggunakan metode kuantitatif yang berdasarkan survei tidak langsung dari responden bidang kesehatan maupun umum. Penelitian ini berlangsung di dalam jaringan selama kurang lebih 3 hari. Subyek dari penelitian ini memuat 13 responden antara lain, 6 orang dari bidang kesehatan dan 7 orang dari umum. Hasil penelitian yang telah dilakukan maka dapat ditarik kesimpulan bahwa Internet of Things (IoT) sangat berpengaruh dalam dunia kesehatan. Kata Kunci: Internet of Things; Kesehatan; Masyarakat
Analisis Sentimen Pengguna X terhadap Kebijakan PPN 12% Menggunakan Naive Bayes Panggabean, Alwi Andika; Kartikasari, Diah Putri; Aulia, Rafif Risdi; Tambak, Tiara Ayu Triarta; Nabila, Siti Fadiyah; Furqan, Mhd
Jurnal Pustaka Data (Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer) Vol 5 No 1 (2025): Jurnal Pustaka Data (Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitekt
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakadata.v5i1.1002

Abstract

Kebijakan kenaikan Pajak Pertambahan Nilai (PPN) dari 11% menjadi 12% yang direncanakan berlaku pada tahun 2025 telah menimbulkan berbagai reaksi publik, terutama di media sosial. Penelitian ini bertujuan untuk menganalisis sentimen pengguna media sosial X (sebelumnya Twitter) terhadap kebijakan tersebut menggunakan metode Naive Bayes yang diimplementasikan dalam bahasa pemrograman R. Data diperoleh dari tweet yang relevan dengan topik PPN 12%, kemudian diproses melalui tahapan pra-pemrosesan dan pelabelan manual. Hasil analisis menunjukkan bahwa sentimen negatif mendominasi dengan proporsi 39%, diikuti sentimen netral 32%, dan sentimen positif 29%. Evaluasi performa model Naive Bayes menunjukkan akurasi sebesar 50%, dengan ketepatan klasifikasi tertinggi pada kategori negatif. Analisis lebih lanjut terhadap istilah kunci dan topik diskusi mengungkapkan bahwa kekhawatiran terhadap beban ekonomi dan dampak terhadap UMKM menjadi sumber utama sentimen negatif, sementara sentimen positif dikaitkan dengan harapan terhadap perbaikan layanan publik dan pembangunan. Penelitian ini memberikan wawasan penting bagi pembuat kebijakan untuk memahami persepsi publik terhadap kebijakan fiskal secara lebih mendalam dan berbasis data.
Design and Implementation of a Web-Based Digital Repository System in the Muamalah Study Program at UINSU Using the Waterfall Method Diah Putri Kartikasari; Farhan, Muhammad
Journal of Computer Science and Informatics Engineering Vol 4 No 4 (2025): October
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v4i4.1158

Abstract

Repository is a digital storage system that can store various kinds of data such as files, documents, and research results, often a repository is called a digital library by many people. Repository is used in various places, one of which is higher education, which can store student research results such as papers, theses, journals, thesis, and dissertations. Muamalah repository is addressed to the Muamalah Study Program, Faculty of Sharia and Law, State Islamic University of North Sumatra which still uses a manual library system so that it can cause problems in the process of searching, storing and managing documents that require a long time. So a digital library or digital repository is the right solution to deal with these problems. The waterfall software development method is used in this research because the process is structured and more organized so that it can facilitate research. The use of UML (Unified Modeling Language) as a design model and PHP (Hypertext Prepocessor) as a programming language makes this research easier to implement. The results of this study can help the muamalah study program in managing various data such as theses, journals, thesis, and so on
Hybrid Demand Forecasting and Monte Carlo Simulation for Retail Supply Chain Inventory Optimization Kartikasari, Diah Putri; Tambak, Tiara Ayu Triarta; Ridwanto, Aero Rizal
JITCoS : Journal of Information Technology and Computer System Vol. 1 No. 2 (2025): Volume 1 Number 2, December 2025
Publisher : CV. Multimedia Teknologi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65230/jitcos.v1i2.40

Abstract

Retail inventory optimization must balance service levels against holding, ordering, and stockout costs under uncertain demand and lead time. We develop an integrated framework that couples hybrid demand forecasting with Monte Carlo simulation (MCS) to evaluate continuous‑review policies. Historical daily sales are modeled using statistical baselines (naive and exponential smoothing) and gradient‑boosted trees with quantile objectives to obtain distributional forecasts. Predictive means and residual‑based dispersion calibrate a Negative Binomial demand model; because lead-time is not present in the dataset, we treat it as a scenario parameter in the simulator (baseline mean ~2 days, SD ~1 day) and probe it via sensitivity analyses. Using a representative retail subset, we simulate 90‑day horizons with 300 replications per item across a grid of values. Results reveal a convex cost–service frontier: (15,120) minimizes total cost in the tested grid, while (25,140) achieves the highest fill rate. Sensitivity analyses show costs are most responsive to safety stock and lead‑time variability. The framework links forecast uncertainty to inventory policy selection, offering a reproducible, data‑driven tool for practitioners and a baseline for future multi‑echelon and decision‑focused extensions.
Pembatasan Laju Adaptif Berbasis Verifiable Delay Function untuk Mitigasi Penyalahgunaan API pada Gateway Edge Ringan Diah Putri Kartikasari; Tiara Ayu Triarta Tambak; Agung Nugroho; Ibnu Rusydi
Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Vol. 4 No. 1 (2026): Januari : Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/polygon.v4i1.931

Abstract

API abuse on lightweight edge gateways has intensified as microservice-based services expose many REST endpoints to heterogeneous clients. Conventional per-identity rate limiting, such as static token buckets, is frequently bypassed through distributed bots and identity rotation, while legitimate burst traffic may be rejected and degrade user experience. This study proposes Adaptive Rate Limiting with Verifiable Delay Functions (ARL-VDF), which couples a lightweight risk score with selective VDF challenges to impose a tunable sequential-computation cost on suspicious clients without forcing aggressive dropping for low-risk users. The gateway continuously derives a per-identity risk score from short-window request rate, error tendency, and identity freshness, then maps the score to a target delay bounded by  and . Evaluation uses a 600-second discrete-event simulation on a mixed workload consisting of normal clients, legitimate bursts, and distributed attackers. Compared with a static token bucket baseline, ARL-VDF maintains full success for legitimate traffic, reduces attacker throughput that passes the gateway, and keeps verification overhead within a fixed budget on the edge device. The results indicate that combining adaptive control with verifiable sequential cost can improve availability and fairness on resource-constrained edge gateways without resorting to aggressive dropping.
Co-Authors Agung Nugroho Aulia, Rafif Risdi Ibnu Rusydi Mhd Furqan Muhammad Farhan Nabila, Siti Fadiyah Panggabean, Alwi Andika Pebi Mina Husania Puji Sri Alhirani Ridwanto, Aero Rizal Tambak, Tiara Ayu Triarta Tengku Syahvina Rival Dini Tiara Ayu Triarta Tambak