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Prototype and Validation of an IoT-Based Voltage and Temperature Monitoring System for Remote ISP Point-of-Presence (POP) Infrastructure
Monitoring electricity and temperature is crucial for maintaining PoP server performance. This research developed an Internet of Things (IoT)-based tool using a NodeMCU ESP32 to directly monitor these two factors. The ZMPT101B sensor measures electrical voltage, while the DHT22 sensor monitors the temperature of the room and server rack. Information obtained from the sensor is sent in real time via a Telegram Bot to the administrator. This tool is particularly useful for PoP located remotely, as...
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Enhanced Self-Esteem Classification: Leveraging Data Augmentation and Transformer-Based Sentence Embeddings
Ahmadiansah, Reza
; Mukti Ali
; Rasimin
; Achmad Maimun
; Kastolani
; Imam Subqi
; Embun Bening Di Moravia
; Semma, Andi Bahtiar
This study investigates automated self-esteem assessment from self-descriptive text using transformer-based sentence embeddings. Although prior research has explored text, behavioral, and multimodal signals, the combined effects of data augmentation, embedding choice, and classifier complexity in text-only self-esteem classification remain insufficiently understood.Accordingly, this study aims to systematically evaluate embedding–classifier combinations under both low-resource and augmented data...
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Loading-Dependent Physicochemical Characteristics of LiMn2O4 Composites with Plasma-Modified and Ammonia-Functionalized Rice Husk Carbon
Harianingsih, Harianingsih
; Deni Fajar Fitriyana
; Januar Parlaungan Siregar
; Agung Budiwirawan
; Ari Dwi Nur Indriawan
; Suryo Wiroyudho Wibowo
; Rizky Ilham Fadzillah
; Nabila Khoirunisa
This study investigates LiMn2O4 composites incorporated with nitrogen-functionalized rice husk-derived carbon as a sustainable secondary phase for cathode material development. Rice husk carbon was prepared through carbonization, acid-assisted activation, plasma treatment, and ammonia functionalization, then mechanically blended with LiMn2O4 at 2, 3, and 4 wt.% to obtain LMO-NC2, LMO-NC3, and LMO-NC4, respectively. FTIR analysis showed absorption bands at approximately 3390, 1625, 1400, 1008, 83...
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Dynamic Chaotic–Adversarial Framework for High-Capacity and Imperceptible Image Steganography
Sari, Wellia Shinta
; Sari, Christy Atika
; Setiyani, Safira Hasna
; Triyono, Agus
; Ali, Rabei Raad
The rapid growth of digital communication has intensified concerns regarding data confidentiality as sensitive information transmitted through multimedia images is increasingly vulnerable to interception and unauthorized analysis. Conventional image steganography methods often struggle to simultaneously achieve high embedding capacity, strong imperceptibility, and resistance to modern steganalysis. To address this challenge, this study proposes a steganographic framework that integrates dynamic...
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Lightweight Dual-Layer Chaotic Image Encryption Using Arnold Cat Map and Henon Zigzag Diffusion
Umam, Chaerul
; Abdussalam, Abdussalam
; Nursetyo, Arif
; Sugiarto, Bambang
; Islam, Husain Md Mehedul
Digital image transmission over open networks raises significant security concerns due to the high correlation and predictable statistical properties of image data. Existing chaotic encryption schemes based on Arnold Cat Map (ACM) and Henon mapping often suffer from high computational cost, parameter sensitivity, or reliance on complex multi-stage designs. To address these limitations, this study proposes a lightweight dual-layer chaotic image encryption framework that integrates ACM-based pixel...
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LDWFOX Optimization for Hyperparameter Tuning of Inception CNN in UAV-Based Vegetation Density Mapping
Pramunendar, Ricardus Anggi
; Alomoush, Ashraf
; Prabowo, Dwi Puji
; Megantara, Rama Aria
; Alzami, Farrikh
; Winarsih, Nurul Anisa Sri
; Pergiwati, Dewi
; Shidik, Guruh Fajar
Vegetation density classification from UAV imagery is a practical necessity in fire-prone landscapes, since fuel load on the ground directly informs risk management decisions. Convolutional neural networks handle this classification reasonably well, but good performance requires careful hyperparameter tuning, and manual trial and error produces results that are unstable and hard to reproduce. This study proposes LDW-FOX, a modified FOX metaheuristic using a Linearly Decreasing Weight mechanism t...
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Technical and Operational Evaluation of SRT-Based IP Contribution for Live Television Broadcasting
Secure Reliable Transport (SRT) is increasingly used for IP-based live-broadcast contribution because it enables low-latency delivery, packet recovery, and encrypted transport over public networks. However, its practical value depends on measurable performance under real operating conditions and disciplined operational control. This study evaluates the implementation of SRT in live football league and volleyball broadcasts using bounded case evidence from operational records, questionnaires, and...
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Pengembangan Digital Pressure Meter Berbasis IoT untuk Pengujian Tekanan Suction Pump dan Pencatatan Data Otomatis
MEDIKA TRADA : Jurnal Teknik Elektomedik Polbitrada
Vol 7
, No 1
(2026)
A suction pump requires periodic vacuum-pressure verification to support consistent performance assessment and reliable documentation. This study developed an Internet of Things (IoT)-based Digital Pressure Meter (DPM) that displays pressure in mmHg, Pascal (Pa), and bar and transmits measurement records to Google Sheets. The device integrated an Arduino Mega 2560, an MPX5050DP pressure sensor, a DHT22 sensor, a TFT LCD, and an ESP8266 module. Testing was performed at 0, 50, 100, 150, and 200 mm...
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PENGUATAN LITERASI DIGITAL MELALUI WORKSHOP DATA SCIENCE DAN MACHINE LEARNING BERBASIS PEMBELAJARAN INTERAKTIF
Abdi Teknoyasa
(2026)
Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan literasi data serta pemahaman konseptual dan aplikatif mengenai Data Science dan Machine Learning bagi sivitas akademika dan masyarakat umum. Kagiatan dilaksanakan oleh tim pengabdian masyarakat Program Studi Teknik Industri, Institut Teknologi Indonesia, melalui penyelenggaraan workshop berbasis pembelajaran interaktif. Materi pelatihan mencakup pengantar konsep data science, teknik pengumpulan dan pembersihan data, analisis...
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OPTIMALISASI PENGELOLAAN SAMPAH ORGANIK RUMAH TANGGA MENGGUNAKAN METODE BIO-ECOMPOST UNTUK PRODUKSI KOMPOS DI KELURAHAN ANDUONOHU
Abdi Teknoyasa
(2026)
Pengelolaan sampah organik rumah tangga masih menjadi tantangan di Kelurahan Anduonohu, Kota Kendari, seiring tingginya timbulan sampah dan rendahnya praktik pemilahan di tingkat rumah tangga. Kegiatan pengabdian ini bertujuan untuk mengoptimalkan pengelolaan sampah organik melalui penerapan metode bio-Ecompost sebagai teknologi tepat guna dalam produksi kompos rumah tangga. Metode pelaksanaan meliputi sosialisasi, pelatihan teknik pengomposan, pendampingan implementasi pada 20 rumah tangga, ser...
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