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All Journal Hanif Journal of Information Systems Al'Adzkiya International of Computer Science and Information Technology Journal
Husaini, Abdillah
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Computer Science & IT Library & Information Science

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Implementation of Fuzzy K-Nearest Neighbor Method in Dengue Disiase Classification Jannah, Aulia; Husaini, Abdillah; Ichsan, Aulia; Azhari, Mulkan
Hanif Journal of Information Systems Vol. 1 No. 2 (2024): February Edition
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/hanif.v1i2.14

Abstract

Dengue hemorrhagic fever (DHF) is a condition brought on by infection with the dengue virus. DHF is a severe illness with hemorrhagic clinical signs that can result in shock and death. One of the four viral serotypes of the genus Flavivirus is responsible for DHF. DHF symptoms include fever, joint pain, red skin patches, and others that are similar to those of other illnesses. So that there are no errors in illness prediction, strong accuracy and accuracy are required when classifying DHF patients or not. The Fuzzy K-Nearest Neighbor (FKNN) method is used in this study to classify dengue sickness in order to obtain the best classification outcomes. In this investigation, k was searched for eight times, with values of 3,5,7,9,11,13,15, and 20. Each K's accuracy statistics are 75.15, 75.16, 77.58%, 79.51%, 85.01%, 78.14%, and 75.20 percent. K = 13, which has an accuracy score of 85.01%, yields the highest accuracy.
Smart Monitoring System of Water Tank Based on Internet of Things Husaini, Abdillah; Sary, Yoshida
Hanif Journal of Information Systems Vol. 2 No. 1 (2024): August Edition
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/hanif.v2i1.25

Abstract

The first village located in Sei Meran Village, Pangkalan Susu Subdistrict, with a population of 640 people consisting of 325 men and 315 women. The village experienced clean water scarcity and received assistance in the form of a drilled well, water pump, and water tank from the Langkat Police Chief through the POLRI Cares for the Environment program. This program significantly improved villagers' access to clean water. However, the village administration and the village head found it challenging to monitor and calculate the fair distribution of clean water. This issue was addressed by implementing an Internet of Things (IoT)-based smart water tank system. This automated system incorporates various sensors, including an ultrasonic sensor and a relay module, to control the water pump and fill the water tank. Additionally, a 4x4 keypad allows villagers to enter an access code that activates the solenoid valve and water flow sensor to measure the distributed water volume. The system can be remotely monitored via the Blynk application using internet access. The ESP8266 microcontroller serves as the data center and control unit. The test results show that the ultrasonic sensor has an average accuracy of 98.7% in measuring distance, while the flow meter sensor has an average accuracy of 98.3% in measuring water flow volume. This system can accurately and efficiently monitor water levels and water withdrawal, automating the water resource management process in the tank.
Implementation of Digital Image Processing Techniques in Measuring the Diameter of Citrus Fruits Husaini, Abdillah
Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 4, No 1 (2023)
Publisher : Al'Adzkiya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55311/aiocsit.v3i1.251

Abstract

Oranges are one of the many fruits that produce vitamin C. The size of oranges will affect the selling price in the market. Large oranges will be sold at a higher price and even become an export commodity. Oranges are valued by two factors; size and quality. This research aims to develop an automated system to determine the size of oranges using the requirements of the Indonesian National Standard (SNI 3932:2008) on the quality of Kepro oranges. This process uses image processing techniques, specifically segmentation by finding the area of the orange diameter. Orange size is measured by its diameter, and there are four levels of size based on SNI, namely first (70 mm), second (61-70 mm), third (51-60 mm), and fourth (40-50 mm). This size determination is usually done visually, but due to its subjectivity, this research aims to create a more objective automated system. The image processing includes testing several edge detection methods such as Prewitt, Canny, Roberts, and Sobel. In addition, the use of RGB coloring was also explored to improve the clarity of orange edges. The results show that the developed system is successful in acquiring images of oranges and identifying their size according to the requirements of the Indonesian National Standard.
Co-Authors Ichsan, Aulia Jannah, Aulia Mulkan Azhari Yoshida Sary