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All Journal Ocean Engineering: Jurnal Ilmu Teknik dan Teknologi Maritim Journal of Technology Informatics and Engineering Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika
Dani Sasmoko
Universitas Sains dan Teknologi Komputer Semarang
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Engineering Mechanical Engineering

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ADVANCED MALICIOUS SOFTWARE DETECTION USING DNN Sulartopo Sulartopo; Dani Sasmoko; Zaenal Mustofa; Arsito Ari Kuncoro
Journal of Technology Informatics and Engineering Vol 1 No 1 (2022): April: Journal of Technology Informatics and Engineering
Publisher : Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v1i1.144

Abstract

The special component of malicious software analysis is advanced malicious software analysis which implicates interested the main framework of malicious software that can be executed after executing it and aggressive malicious software investigation depend on inquisitive of the practice of malicious software after running it in a composed habitat. Advanced malicious software analysis is usually performed by contemporary anti-malicious software operating systems using signature-based analysis. The purpose of this research is to propose also decide a DNN for the progressive identification of portable files to study the features of portable executable malicious software to minimize the occurrence of distorted likeness when aware of advanced malicious software. The model proposed in this study is a NN with a Dropout model contrary to a resolution tree model to examine how well it performs in detecting real malicious PE files. Setup-skeptic methods are used to extract features from files. The dataset is used to train the proposed approach and measure outcomes by alternative common malicious software datasets. The results from this study illustrate that the use of simple DNNs to study PE vector elements is not only efficient but more fewer system comprehensive than the traditional interested disclosure approach. The model proposed in this study achieves an A-UC of ninety-nine point eight with ninety accurate specifics at one percent inaccurate specific on the R-OC curve. For shows that this model has the potential to complement or replace conventional anti-malicious software operating systems so for future research, it is proposed to implement this model practically.
Pengembangan Sistem Penyiraman Otomatis Berbasis Internet of Things untuk Optimalisasi Urban Farming: Studi Kasus: Poktan Bensor Semarang Muhammad Hasanuddin; Sulartopo Sulartopo; Dani Sasmoko
Ocean Engineering : Jurnal Ilmu Teknik dan Teknologi Maritim Vol. 5 No. 3 (2026): Ocean Engineering : Jurnal Ilmu Teknik dan Teknologi Maritim
Publisher : Fakultas Teknik Universitas Maritim AMNI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58192/ocean.v5i3.5408

Abstract

Urban Farming is a strategic solution for improving food security in urban areas through productive use of limited land and space Fei et al. However, manual watering remains a major obstacle, requiring time and labor while risking water volumes that mismatch plants' physiological needs Hayati. This study designs, builds, and implements an Internet of Things (IoT)-based automatic watering system to optimize Urban Farming at the Bendan Ngisor Farmer Group (Poktan Bensor), Semarang, capable of monitoring plant environmental conditions in real time and controlling watering automatically or manually from a distance Atzori et al., Kamienski et al. The system uses an ESP32 microcontroller as the control unit Espressif Systems, Kolban, a DHT22 sensor for temperature and humidity Aosong Electronics, Taiz et al. a Soil Moisture Sensor Bogena et al. Muñoz-Carpena, a relay actuator Petruzella, a DC water pump Çengel & Cimbala, and Telegram as the remote interface Telegram, Hidayat & Gunawan, following a Research and Development approach Monk. Results show the system reads parameters stably, executes automatic watering below the critical threshold (<40%), and sends Telegram Bot notifications with a 98.5% success rate, proving effective for sustainable Urban Farming management.
Prototype Sistem Kendali Penyiraman Tanaman Otomatis Berbasis IoT dengan Mode Manual dan Otomatis Menggunakan ESP32 dan Platform Blynk Rifki Aldiansyah; Dani Sasmoko
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 4 No. 5 (2026): September : Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Inf
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/jupiter.v4i5.1609

Abstract

The increasing scarcity of water resources and the need for optimal soil moisture levels for plant growth have driven the development of smart irrigation systems based on the Internet of Things (IoT). This study presents a prototype of an automatic plant watering control system using an ESP32 microcontroller equipped with a capacitive soil moisture sensor, relay module, and I2C LCD interface. The system is designed with two operating modes: an automatic mode that independently activates the water pump based on soil moisture thresholds, and a manual mode that allows users to control the pump directly through the Blynk application on a smartphone. Sensor data is transmitted to the Blynk platform in real-time via a WiFi connection using virtual pin communication protocols. Test results show that the system is capable of reading soil moisture values with good accuracy, responding to changes in soil conditions in less than 2 seconds, and simultaneously displaying moisture status and pump conditions on both the LCD and the Blynk application. This system is expected to serve as a solution for efficient water use in urban and household agriculture, supporting the concept of sustainable and energy-efficient farming.
Co-Authors Arsito Ari Kuncoro Muhammad Hasanuddin Rifki Aldiansyah Sulartopo Sulartopo Sulartopo Sulartopo Zaenal Mustofa