Research Laboratory

Heterogeneous Intelligent Network Technologies

HINT Laboratory berfokus pada riset jaringan heterogen, Internet of Things, edge intelligence, network automation, dan integrasi sistem cerdas untuk mendukung infrastruktur digital masa depan.

Research Focus

Intelligent network research for connected systems

Area riset laboratorium disusun untuk mendukung pengembangan jaringan, perangkat, dan aplikasi cerdas yang saling terhubung.

01

Heterogeneous Networks

Integrasi LoRaWAN, WLAN, MQTT, edge gateway, dan cloud untuk komunikasi data yang reliabel.

02

Edge Intelligence

Optimasi pemrosesan data, inferensi AI, dan pengambilan keputusan dekat dengan sumber data.

03

Network Automation

Automasi monitoring, kontrol perangkat, dan dashboard analitik untuk sistem jaringan cerdas.

Members

Researchers and students

All Members
Foto Pradini Puspitaningayu, S.T., M.T., Ph.D
Laboratory Chief

Pradini Puspitaningayu, S.T., M.T., Ph.D

Heterogeneous Intelligent Network Orchestration

Leading research on heterogeneous network integration, intelligent routing, edge-cloud coordination, and large-scale IoT systems.

Foto Meilinda Mutiara Susilo, S.T.
Master StudentM2

Meilinda Mutiara Susilo, S.T.

Heart Rate Interpretation using LLM

Implementation of Large Language Model to interpret heart rate data into easy-to-understand language

Blogs

Research stories from contributors

All Blogs

Publications

Selected published works

All Publications
Conference Paper • 2026

An Evaluation of LoRaWAN and WLAN for IoT-based Photovoltaic Microgrid Monitoring

Authors: Muhammad Aamir Nashrullah, Pradini Puspitaningayu, Muhamad Bagus Fikril Alan, Erwin Sutanto, Fahmi Fahmi, Unit Three Kartini
Published in: 2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems, ICETSIS 2024
DOI: https://doi.org/10.1109/ICETSIS61505.2024.10459411
Journal Article • 2025

Prediction of Solar Panel Voltage Using LSTM on a PV System with a 5 W Lamp Load

Authors: Muhamad Bagus Fikril Alan, Pradini Puspitaningayu, Muhammad ‘Aamir Nashrullah, Laras Suciningtyas, Md Mahbubur Rahman
Published in: LSTM-based Prediction of Photovoltaic Voltage with Lightweight Load Scenarios
DOI: https://doi.org/10.26740/jistel.v1n2.p200-210