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All Journal Jurnal Teknologi Informasi dan Komunikasi
Faritcan Parlaungan Siallagan, Timbo
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Computer Science & IT Control & Systems Engineering

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MACHINE LEARNING PENGAMAN BRANKAS BERBASIS IoT MENGGUNAKAN METODE ALGORITMA NAIVE BAYES PADA PLATFORM THING SPEAK Faritcan Parlaungan Siallagan, Timbo; Alghifari, Muhammad
Jurnal Teknologi Informasi dan Komunikasi Vol 16 No 2 (2023): Oktober
Publisher : STMIK Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47561/a.v16i2.244

Abstract

A safe is a tool used to store items, including money, jewelry, or other assets and securities. It is claimed to be simple but carries a high risk because it makes it easy for the safe to be broken into without the owner's knowledge. A household assistant (ART) with the initials HS stole a safe from inside her employer's house located in Taman Kedoya Permai, Kebon Jeruk, West Jakarta, "The safe contained securities documents, two house certificates, and several other documents," said Kebon Jeruk Police Chief Commissioner Slamet Riyadi in Jakarta. With this, the author developed by creating a tool entitled "Machine Learning for Safe Security Based on IoT (Internet of Things) Using the Naïve Bayes Algorithm Method on the ThingSpeak Platform" equipped with RFID as safe door access, SW-420 sensors to detect vibrations in the event of a forced break-in. , a Passive Infra Red sensor to detect movement by the user, and an HX-711 Load Cell sensor to measure the volume weight of the safe to obtain 4 parameters, then the data is processed using the Naïve Bayes algorithm. Naïve Bayes is a statistical grouping that can be used to predict the probability of class members. Naïve Bayes also has extreme accuracy and speed when applied to databases with big data.
Teknik RANCANG BANGUN JEMURAN PAKAIAN PINTAR BERBASIS IOT MENGGUNAKAN PLATFORM THINKSPEAK: RANCANG BANGUN JEMURAN PAKAIAN PINTAR BERBASIS IOT MENGGUNAKAN PLATFORM THINKSPEAK Faritcan Parlaungan Siallagan, Timbo; Faelasivah, Fiky; Anestasya S, Sellyna
Jurnal Teknologi Informasi dan Komunikasi Vol 17 No 1 (2024): April
Publisher : STMIK Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47561/a.v17i1.248

Abstract

Human dependence on the sun's heat to dry clothes cannot be abandoned, because there are no tools and technology yet. The global warming that is currently happening causes the season in Indonesia to be erratic, so that the dry season and rainy season can no longer be predicted. The purpose of this research is to design an IOT-based clothesline system in drying clothes efficiently by sorting by weather. The design of this clothesline problem uses Arduino Uno as a data processor, LDR sensor and Rain sensor as parameters to detect weather. The results of the sensor are sent via the ESP8266 module to the Thingspeak platform to be displayed on the system. The function of this design system is that the servo will automatically open and close according to the weather inputted by the light and rain sensors.
Co-Authors Alghifari, Muhammad Anestasya S, Sellyna Faelasivah, Fiky