A Machine Learning-Based Ambiguous Alphabet Recognition for Indonesian Sign Language System (SIBI)

Yoan Purbolingga, Ahmad Ridwan, Dila Marta Putri — Mon, 30 Jun 2025 00:00:00 +0000

One of the communication problems in deaf people is the inhibition of verbal communication. This is due to the limited hearing function which has an impact on the imperfection of language sound reception. To communicate with deaf people, extraordinary communication is needed so that the meaning of the conversation can be conveyed properly. Sign language is the main communication medium for deaf people. However, in the use of sign language, there are ambiguous letters, namely “D “,“E“,“M“,“N“,“R“, “S“, and “U“. This research uses the chain code method to identify and reconstruct the shape of hand gesture objects. Then, to solve the problem of ambiguity of alphabet letters, an artificial intelligence method, namely K-Nearest Neighbors (K-NN), is used. The sample used consists of 350 real-time images with variations in object recognition accuracy. Based on the research using chain code and K-NN classification method, it can be concluded that the recognition of ambiguous letters in sign language has 245 training data for K-NN which has 88.76% accuracy, and 105 test data with 90% accuracy. This test data is divided into seven letters: “D“, “E”, “M”, “R” and “U” at 100%, and “N” and “S” at 98.88%.

Prototype of IoT-Based Temperature and Humidity Monitoring and Controlling System for Broiler Chicken Coops

Mon, 30 Jun 2025 00:00:00 +0000

Temperature and humidity are critical factors that influence the health and productivity of broiler chickens. Manual monitoring and control of coop conditions are often ineffective and inefficient, leading to a decline in production quality. This research aims to develop a prototype IoT-based monitoring and controlling system for temperature and humidity in broiler chicken coops. The system employs a DHT22 sensor to measure temperature and humidity, a Wemos D1 R1 microcontroller for data processing, and the Blynk application as a user interface for real-time monitoring and notifications. The Evolutionary Prototyping method is applied in the development of this system to allow gradual adjustments based on user needs. Testing results show that the prototype can monitor temperature and humidity in real-time and automatically activate fans or lights when the temperature is outside the optimal range. With this system, farmers can monitor coop conditions remotely, simplifying farm management.

CogITo Smart Journal

A Machine Learning-Based Ambiguous Alphabet Recognition for Indonesian Sign Language System (SIBI)

Prototype of IoT-Based Temperature and Humidity Monitoring and Controlling System for Broiler Chicken Coops