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All Journal Journal of Computer Networks, Architecture and High Performance Computing International Journal of Economic, Business, Accounting, Agriculture Management and Sharia Administration (IJEBAS) Jurnal Minfo Polgan (JMP) TECHSI - Jurnal Teknik Informatika
Ramadhansyah, Rizki
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Library & Information Science Mathematics Social Sciences Other

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Aplikasi Peramalan Harga Emas dengan Menggunakan Metode Triple Exponential Smoothing Ramadhansyah, Rizki
TECHSI - Jurnal Teknik Informatika Vol. 14 No. 2 (2023)
Publisher : Teknik Informatika Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/techsi.v13i2.2695

Abstract

Emas merupakan salah satu logam berharga yang biasanya digunakan sebagai perhiasan, koleksi, dan investasi. Banyak orang yang mulai dalam melakukan investasi emas merasa kesulitan dalam mengambil keputusan untuk membeli dan menjual emas. Berdasarkan permasalahan tersebut, peneliti bermaksud membantu masyarakat biasa ataupun investor dengan cara menciptakan suatu sistem aplikasi peramalan harga emas dengan menggunakan metode triple exponential smoothing (TES). Data harga emas yang diambil mulai dari tahun 2014 sampai 2019 yang berasal dari 5 sumber harga emas yang berbeda yaitu monexnews.com, databoks.katadata.co.id, goldprice.org, hargaemasku.com, dan seputarforex.com. Untuk melakukan perhitungan menggunakan metode triple exponential smoothing (TES) ini menggunakan 305 data harga emas berasal dari 5 sumber yang berbeda. Dalam penerapannya, metode triple exponential smoothing (TES) menggunakan nilai parameter alpha 0,15 dan beta 0,85 menghasilkan tingkat akurasi 86,91 % dan MAPE 12,49 %.
Navigasi Realtime Menggunakan Incremental GPS Path Logging Algorithm dan Visualisasi Interaktif Berbasis Web: Pengembangan Sistem Pelacakan Posisi dan Arah Pengguna Berbasis Browser dengan Mapbox GL JS dan Kompas Digital Taufiqurrahman, Taufiqurrahman; Simatupang, Septian Enggar; Ramadhansyah, Rizki; Sari, Indah Clara; Rafli, Ihsan
Jurnal Minfo Polgan Vol. 14 No. 1 (2025): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v14i1.15006

Abstract

The advancement of web technologies and mobile device sensors has opened new opportunities in the development of lightweight and flexible realtime navigation systems. This study aims to develop a web-based navigation system utilizing the Incremental GPS Path Logging Algorithm for step-by-step route logging, and integrating a digital compass to align the map view with the device’s orientation. The map visualization is implemented using Mapbox GL JS, enabling a third-person interactive display in realtime. Built with JavaScript and React JS, the system was tested in lightweight mobility scenarios such as walking and cycling. Results showed the system accurately tracked user positions, efficiently updated routes without full redraw, and displayed speed, distance, and duration in realtime. The use of DeviceOrientationEvent provided a more intuitive navigation experience, despite challenges like sensor lag or permission restrictions on certain devices. This system demonstrates great potential for personal tracking and lightweight mobility use cases across platforms without app installation. Future research may focus on 3D visualization optimization, integration of historical data, and advanced route analytics
Development of a YOLO-Based Artificial Intelligence (AI) System for Early Detection of Stunting Risk in Children in 3T Regions of North Sumatra Province Ramadhansyah, Rizki; Simatupang, Septian; Abdillah, Rizky
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 4 (2025): Articles Research October 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i4.6954

Abstract

Stunting is a chronic nutritional problem that has long-term impacts on children’s physical growth, cognitive development, and future productivity. This condition remains a major challenge in the 3T regions (frontier, outermost, and disadvantaged areas) of North Sumatra Province due to limited healthcare personnel, lack of measurement facilities, and delays in early detection. This study aims to develop an artificial intelligence system integrating YOLOv8 and Random Forest to automatically and in real time detect stunting risk in children. The YOLOv8 model is utilized to detect the presence of a child and estimate height through visual image analysis, while the Random Forest algorithm classifies the risk level based on the Height-for-Age Z-score (HAZ) derived from anthropometric and demographic data. The dataset consists of 29 children from 3T regions, with training and testing splits used to evaluate model performance. The results show that the system achieved an accuracy of 97.8%, precision of 96.5%, recall of 95.9%, F1-score of 96.2%, and an area under the ROC curve (AUC) of 0.98. The system successfully detects children in real time, produces risk classifications consistent with manual measurements, and automatically documents examination data. The novelty of this research lies in the integration of YOLO for automatic height measurement and Random Forest for nutritional classification, which has not been applied in the 3T regional context. This system has the potential to serve as a digital tool for healthcare workers and posyandu cadres to accelerate child nutrition monitoring in an efficient, accurate, and well-documented manner.
GOLD PRICESFORECASTING USING TRIPLE EXPONENTIAL METHOD Khairawati, Khairawati; Fuadi, Wahyu; Ramadhansyah, Rizki; Fariadi, Dedi
International Journal of Economic, Business, Accounting, Agriculture Management and Sharia Administration (IJEBAS) Vol. 1 No. 2 (2021): December
Publisher : CV. Radja Publika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (376.232 KB) | DOI: 10.54443/ijebas.v1i2.79

Abstract

Governments, organizations, and citizens have taken an interest in gold price fluctuations. Gold price forecasting that is accurate may effectively capture price shift tendencies and reduce the effects of gold market volatility. However, due to the multi-factor and nonlinear nature of the gold market. The triple exponential smoothing strategy is used in this study to predict the rise in a value over time since it can replicate trends and seasonal patterns. according to the gold price swings pattern and seasonal components at the same time To calculate system accuracy, the Mean Absolute Percentage Error is employed (MAPE). With alpha 0.15 and beta 0.85 as parameter values, the triple exponential smoothing (TES) approach achieves an accuracy rate of 86.93 percent and a MAPE of 12.49 percent in this study.
Co-Authors Abdillah, Rizky Dedi Fariadi Fuadi, Wahyu Khairawati Khairawati, Khairawati Rafli, Ihsan Sari, Indah Clara Simatupang, Septian Simatupang, Septian Enggar Taufiqurrahman