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Jurnal Teknologi Informasi dan Komunikasi
Published by Sekolah Tinggi Manajemen Informatika dan Komputer Subang
ISSN : 22524517     EISSN : 27237249     DOI : https://doi.org/10.47561/a.v13i1
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering
Jurnal Teknologi Informasi dan Komunikasi menerbitkan kajian ilmiah hasil penelitian dan pemikiran di bidang ilmu dan teknologi komputer yang didistribusikan sebagai sumber referensi bagi para akademisi di bidang Ilmu dan Teknologi Komputer. Jurnal Teknologi Informasi dan Komunikasi menerima artikel ilmiah dengan cakupan penelitian: 1. Internet of Things 2. Machine Learning 3. Data Mining 4. Big Data 5. Sistem Pengambilan Keputusan 6. Sistem Artificial Intelligence 7. Jaringan Komputer 8. Sistem Informasi
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 148 Documents
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MODEL RUMAH DIGITAL BERBASIS ARDUINO UNO MENGGUNAKAN MIKROKONTROLER ATMEGA 328P Hermawan, Rian
Jurnal Teknologi Informasi dan Komunikasi Vol 16 No 1 (2023): April
Publisher : STMIK Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47561/a.v16i1.241

Abstract

The vulnerability of homeowners is a significant factor in various criminal activities, such as forgetting to lock doors or leaving the house with lights off. Therefore, it is necessary to design a digital home that allows homeowners to control their homes remotely. This research aims to build and enhance a smart home, which has been previously studied. Through this development, the smart home transforms into a digital home by adding several features. The features include Home Door Security, Home Temperature Monitoring, and Home Appliance Control via SMS. The digital home is expected to be beneficial in preventing crimes and addressing negligence-related incidents. By providing access codes to unlock doors, it helps prevent unauthorized entry, enhancing home security. Additionally, it addresses safety concerns related to negligence, such as electrical short circuits or gas leaks that may lead to fires. The digital home can provide immediate assistance by reacting to abnormal temperatures detected by sensors, activating fans to normalize the temperature. If the temperature remains above the specified limit, a danger alarm will sound, indicating an issue inside the house. Another function is the ability to control home appliances remotely via text messages (SMS) when the homeowner is away.
IMPLEMENTASI METODE SAW (SIMPLE ADDITIVE WEIGHTING) untuk MENENTUKAN PRIORITAS KEBERSIHAN TOILET SEKOLAH BERBASIS Internet of Things Wijaya, Anderias Eko; Hakim, Muhammad Azizul
Jurnal Teknologi Informasi dan Komunikasi Vol 16 No 1 (2023): April
Publisher : STMIK Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47561/a.v16i1.242

Abstract

This research proposes the implementation of the Simple Additive Weighting (SAW) method as an approach to determine priorities for school toilet cleanliness based on IoT. The system integrates temperature, humidity, and ammonia gas sensors as key indicators to measure the cleanliness condition of toilets. The SAW method is employed to calculate the relative weight of each parameter, which is then used to assign priority scores. The system operates by utilizing temperature sensors to identify the toilet's environmental temperature, humidity sensors to measure humidity levels, and ammonia gas sensors to detect ammonia concentration, a crucial indicator of toilet cleanliness. Data from these sensors are collected and processed using the SAW method, enabling the automatic determination of toilet cleanliness priorities. The success of this implementation is tested through simulations and field testing. Experimental results demonstrate that the system is capable of providing priority scores with high accuracy, allowing for more efficient management of toilet cleanliness. Other advantages include the system's ability to provide real-time notifications to relevant parties through the IoT platform, facilitating prompt corrective actions. This research contributes to the development of intelligent solutions for school toilet cleanliness management, integrating IoT technology and the SAW method to provide a measurable and effective approach. With the adoption of this system, it is expected to enhance the quality of school toilet sanitation, support student health, and optimize school facility management.
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.
RANCANG BANGUN ALAT PENDETEKSI DINI PONTENSI KEBAKARAN SECARA OTOMATIS pada RUANGAN TERINTGRASI dengan INTERNET of THINGS Udoyono, Kodar; Daniati, Dewi Nia
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.v16i2.246

Abstract

In an effort to enhance safety and early detection of potential fires in indoor spaces, this research designs and constructs an automatic early fire detection device integrated with the Internet of Things (IoT). The device incorporates a flame sensor, MQ2 sensor, DHT11 temperature and humidity sensor, buzzer, LCD 16x2, and Node MCU to provide an effective and efficient solution. The flame sensor is utilized to detect the presence of fire, while the MQ2 sensor is employed to detect potentially hazardous gases associated with fires. The DHT11 sensor provides temperature and humidity information in the surrounding environment, aiding in identifying potential conditions conducive to fires. The Node MCU serves as the central processing unit of the system, collecting data from the sensors and transmitting it to the IoT platform via Wi-Fi connectivity. This data can be accessed and monitored in real-time through applications or online platforms. Upon detecting a potential fire, the buzzer issues an audible alert, and the LCD 16x2 displays detection information for the user. The primary advantage of this device lies in its ability to provide prompt and efficient detection information, accessible remotely through internet connectivity. With the integration of IoT, the device offers a smarter and more responsive solution for addressing potential fires in indoor spaces. The implementation of this device is anticipated to enhance safety and provide better protection against the risk of fires.
MACHINE LEARNING SMART PACKAGING PENGIRIMAN TELUR AYAM BERBASIS INTERNET oF THINGS (IoT) MENGGUNAKAN ALGORITMA C.45 DENGAN PLATFORM THINGSPEAK Jupriyanto, Jupriyanto; Putri, Cerafine Delna
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.v16i2.247

Abstract

In the era of Industry 4.0, the integration of Machine Learning and the Internet of Things (IoT) plays a crucial role in enhancing the efficiency and safety of logistics processes. This research aims to develop a Smart Packaging system for the shipment of chicken eggs utilizing Machine Learning with the C.45 algorithm and IoT-based on the ThingSpeak platform. The system integrates Node-MCU (ESP8266) as the central processing unit, the DHT11 sensor to monitor temperature and humidity within the packaging, the Vibration Sensor SW-420 to detect potential damage to eggs during shipment, and the Unblock Neo6m-V2 GPS Module for real-time location tracking. The C.45 algorithm is employed to process data and make intelligent decisions regarding the condition of the eggs and the shipping environment. Sensor data is collected and transmitted to the ThingSpeak platform through the Wi-Fi connection provided by Node-MCU. The C.45 algorithm is applied to analyze the data, provide predictions regarding egg conditions, and make decisions for further actions during the shipping process. Experiments were conducted to evaluate the system's accuracy using RapidMiner software. The results indicate that the system is capable of predicting egg conditions with a high level of accuracy, enabling responsive actions to situations that may affect egg quality during shipment. The implementation of Machine Learning and IoT technologies in this chicken-egg shipping system is expected to enhance the quality of delivered products, optimize logistical processes, and provide an intelligent solution to ensure the sustainability of the food product supply chain.
SISTEM IDENTIFIKASI SAMPAH ANORGANIK BERBASIS IOT (Internet of Things) MENGGUNAKAN METODE SAW (Simple Additive Weighting) Wijaya, Anderias Eko; Rokhman, Febriana Nur
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.v16i2.249

Abstract

Inorganic waste is one of the environmental issues that needs to be effectively managed. An Internet of Things (IoT)-based system using the Simple Additive Weighting (SAW) method is implemented to provide a solution for the more efficient management of inorganic waste. This system utilizes sensors connected to the IoT network to detect and identify the types of inorganic waste entering a specific area. The SAW method is employed to assign weights to each criterion applied in the identification process of inorganic waste, such as type, weight, and physical condition. The system assesses based on the predefined criteria weights, enabling high-accuracy categorization of inorganic waste. Identification results can be accessed in real-time through the IoT platform Thingspeak, allowing for quick monitoring and analysis. Implementing this system is expected to positively contribute to the management of inorganic waste, facilitating more efficient collection, categorization, and overall waste handling. Moreover, adopting IoT technology and the SAW method in this system is envisioned to provide sustainable solutions in waste management efforts to support environmental sustainability.
SISTEM PERINGATAN DINI TERHADAP PENCURIAN SEPEDAH MOTOR MENGGUNAKAN MIKROKONTROLER ATMEGA 328 ARDUINO UNO Permana, Eka; Setiadi, Kendi
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.v16i2.250

Abstract

Motorcycle theft is a prevalent issue that often results in significant losses for its owners. In addressing this challenge, this research introduces an Early Warning System for Motorcycle Theft utilizing the ATmega328 microcontroller, particularly the Arduino Uno. The system is designed to detect unusual movements or vibrations in the motorcycle. Vibration and motion sensors are installed on the motorcycle to monitor suspicious activities. The ATmega328 microcontroller acts as the brain of the system, analyzing inputs from the sensors and triggering an alert when potential theft is detected. Early warnings can be implemented through various channels, including the use of alarms, message notifications, or sending information to the owner's device via wireless connectivity. The system's advantage lies in its ability to provide a rapid response to potential theft situations, offering a greater opportunity to prevent losses. Through the utilization of microcontroller technology and sensors, this research contributes to the development of effective and affordable security solutions for safeguarding valuable assets such as motorcycles. The implementation of this system is expected to be a proactive step in enhancing motor vehicle security and providing peace of mind for the owners.
SISTEM MONITORING KENYAMANAN TOILET BERBASIS IoT MENGGUNAKAN PLATFORM BLYNK Parlaungan S., Timbo Faritcan; Novianti, Wieke; Permana, Eka; Ahmad, Hermansyah Nur
Jurnal Teknologi Informasi dan Komunikasi Vol 17 No 2 (2024): October
Publisher : STMIK Subang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47561/a.v17i2.245

Abstract

The purpose of this research can monitor and control the comfort of IoT-based toilets (Internet Of Things) using the Blynk Platform. In general, the comfort of the toilet is known if the situation is dirty and seen directly, especially if it causes an unpleasant odor. This system aims to collect temperature, gas data and provide access to toilet condition information to cleaners easily and quickly through an application integrated with Blynk. In monitoring comfort in toilets, the research methods used include literature surveys to understand IoT concepts and relevant technologies, as well as a review of temperature and gas sensor technologies that are suitable for data collection. In addition, user needs analysis and system design are also carried out to ensure the availability of accurate and relevant information. From the results obtained, it is hoped that this study can help determine the condition of the toilet in realtime so that toilet comfort is more awake and users feel comfortable when using the toilet. This research can also be a reference for future researchers related to the material used.
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

Ketergantungan manusia pada panas matahari untuk mengeringkan pakaian belum dapat ditinggalkan, karena belum adanya alat dan teknologi . Pemanasan global yang sekarang ini sedang terjadi menyebabkan musim di Indonesia menjadi kurang menentu, sehingga musim kemarau dan musim penghujan sudah tidak dapat diprediksikan lagi. Tujuan dari penelitian ini adalah merancang sistem tempat jemuran pakaian berbasis IOT dalam mengeringkan pakaian secara efisien dengan memilah berdaskan cuaca[1]. Perancangan masalah jemuran ini menggunakan Arduino Uno sebagai pengolah data, sensor LDR dan sensor Hujan sebagai parameter untuk mendeteksi cuaca. Hasil dari sensor tersebut dikirim melalui modul ESP8266 ke platform Thingspeak untuk ditampilkan pada sistem. Fungsi sistem perancangan ini yaitu servo akan secara otomatis membuka dan menutup sesuai dengan cuaca yang di input oleh sensor cahaya dan hujan.[2]
SISTEM PENDUKUNG KEPUTUSAN PENENTUAN STATUS GIZI BALITA PADA DINAS KESEHATAN KABUPATEN ALOR MENGGUNAKAN ALGORITMA C4.5 Molina, Jon Idrison; Malese, Lasarus Pelipus
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.v17i1.252

Abstract

Assessment of nutritional status plays a very important role in monitoring children's nutrition. If the assessment of nutritional status is carried out correctly and accurately, signs or symptoms of impaired growth and development in children can be identified early so that mitigation and prevention can be carried out in an effort to improve the nutritional status of children under five. And the occurrence of nutritional problems can be minimized. For this reason, determining the nutritional status of toddlers must be done quickly and accurately. Puskesmas as the technical implementer of the Health Service, has the main task of collecting data and assessing the nutritional status of toddlers and submitting the results of the assessment to the Health Service. The determination of nutritional status that has been carried out is by looking at and calculating the standard anthropometric table for assessing the nutritional status of toddlers according to the Decree. Minister of Health Number: 1995/Menkes/SK/XII/2010. However, Puskesmas are often slow in treating large numbers of patients and also have limited resources, especially in areas where there is a shortage of medical personnel. So this also influences the results of the assessment of determining the nutritional status of toddlers. For this reason, the Health Service needs to provide an optimal method for determining the nutritional status of toddlers to be used by Community Health Centers to determine the nutritional status of toddlers quickly, precisely and accurately. So researchers have conducted research and produced a decision support system for determining nutritional status in toddlers using the C4.5 algorithm. Test results to measure algorithm performance using the Confusion Matrix, Accuracy, Precision and Recall testing method, it is known that the C4.5 algorithm has an accuracy value of 72.13 %, Precision value 71.43% and Recall value 22.73% Keywords : Decision Support, Nutritional Status, Toddlers, C4.5 Algorithm

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