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Analisis Prediksi Perencanaan Produksi dengan Fuzzy Logic Tsukamoto Anugrahwaty, Rina; Azmi, Fadhillah
Sinkron : jurnal dan penelitian teknik informatika Vol. 1 No. 2 (2017): SinkrOn Volume 1 Nomor 2 April 2017
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (372.984 KB)

Abstract

Produksi adalah salah satu bagian penting pada setiap perusahaan. Produksi merupakan proses dari bahan baku menjadi bahan jadi yang mana memiliki nilai lebih tinggi bagi penggunanya. Tujuan produksi untuk merencanakan dan mengendalikan persediaan produksi yang mana menghasilkan output produksi sesuai dengan permintaan. Memperkirakan produksi berdasarkan kebiasaan dapat berdampak pada kurangnya ketersediaan produk di pasar dan adanya penumpukkan produk yang tidak menentu. Penulis menggunakan metode logika fuzzy dengan model Tsukamoto untuk menyelesaikan permasalahan perencanaan produksi.
Analisis Matriks 5x7 Pada Kriptografi Playfair Cipher Azmi, Fadhillah; Anugrahwaty, Rina
Sinkron : jurnal dan penelitian teknik informatika Vol. 1 No. 2 (2017): SinkrOn Volume 1 Nomor 2 April 2017
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (188.104 KB)

Abstract

Kriptografi memiliki peran yang sangat penting di era digitalisasi yang mana bertujuan untuk mengamankan informasi. Informasi yang bersifat privasi dapat terhindar dari orang ketiga dan informasi yang akan disampaikan dapat dilindungi. Salah satu keamanan data yang ditawarkan dengan metode kriptografi playfair cipher yang mana sebelumnya telah dianalisa dengan menggunakan matriks 5x5, 7x4 dan 6x6. Tujuan dari penulisan ini untuk menganalisis matriks 5x7 pada metode kriptografi playfair cipher sejauh mana tingkat keamanan yang dapat diberikan dengan membandingkan hasil analisa yang telah dilakukan sebelumnya yaitu pada matriks 5x5, 7x4 dan 6x6.
Design of DCU Smart Lighting for Public Streetlights in Medan City Batubara, Febrin Aulia; Anugrahwaty, Rina
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 3 No. 4 (2024): IJRVOCAS - Special Issues - International Conference on Science, Technology and
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v3i4.199

Abstract

Currently, Medan City is developing a public streetlight project along the highways of Medan City. The Medan city government has spent billions to fix this. The construction of these public streetlights also consumes the city's electricity resources. Efficiency measures are needed to reduce the use of electricity for public streetlights. We propose this research using smart lighting technology. This device will detect human and vehicle movements, time settings, and step dimming that allows dynamic lighting and dimming. This technology also allows for communication from one device to another, such as if a pedestrian or car is detected, then the surrounding streetlights will turn on. This device will be equipped with PIR sensors, ultrasonic sensors, and light sensors. With the development of Internet of Things technology currently, it is expected to help control remotely and have an integrated system. The control and monitoring system is connected via the internet. The parameters to be controlled are the presence of humans, vehicles, and lighting, and all these parameters can be monitored with web-based and Android applications. Based on the above studies, this research will design a public streetlight system using a Data Control Unit (DCU) to facilitate the control system, and this device will be integrated with sensors such as human sensors (PIR), light sensors, and ultrasonic sensors. The system is in the form of smart lighting that can be monitored remotely, such as whether lights will be bright or dim if there are road users and vehicles, and each streetlamp will be connected to each other wirelessly.
Implementasi Metode Rule-Based dalam Sistem Pakar Pemilihan Program Studi Menggunakan Bahasa Prolog Faza, Sharfina; Rizka, Ade; Husna, Meryatul; Anugrahwaty, Rina; Fawwaz, Insidini
Journal Global Technology Computer Vol 4 No 2 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jogtc.v4i2.7293

Abstract

The alignment between study programs and students' interests and abilities is a crucial factor in academic success at the university level. Unfortunately, many prospective students face confusion when choosing majors due to limited knowledge about the characteristics of each program and its relationship with career prospects, potentially affecting their academic performance and career paths. To address this challenge, our research presents a solution in the form of a rule-based expert system developed using Prolog language. This system is designed to provide study program recommendations through analysis of user responses to various structured questions. Using score calculation methods and matching against established value parameters, the system can propose the most relevant majors among four options: Computer Engineering (CE), Information Management (MI), Multimedia Graphics Engineering Technology (TRMG), and Software Engineering Technology (TRPL). Through this implementation, prospective students receive recommendations aligned with their potential and interests, facilitating more accurate decision-making. In addition to functioning as an assistive instrument in career and academic counseling for high school students, this research also lays the foundation for the development of more sophisticated expert systems with enhanced assessment weights and precision levels in the future.
Intelligent Actuator Control in Smart Agriculture through Machine Learning and Sensor Data Integration Azmi, Fadhillah; Gibran, M. Khalil; Fawwaz, Insidini; Anugrahwaty, Rina; Saleh, Amir
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 1 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i1.24421

Abstract

Smart agriculture leverages Internet of Things (IoT) technology to develop intelligent greenhouses capable of monitoring and responding to environmental changes in real time. This study proposes the use of machine learning to analyze real-time sensor data—such as temperature, humidity, water level, and soil nutrient levels (N, P, K)—to determine the optimal timing for activating actuators, including fans, irrigation systems, and water pumps. In the initial stage, the study utilized the "IoT Agriculture 2024" dataset from Kaggle, which consists of 37,922 records and 13 attributes describing crop and environmental conditions. This dataset was used to train a robust machine learning model based on gradient boosting to support intelligent actuator control decisions. The model demonstrated strong predictive accuracy, achieving 99.62%. In the final stage, the model was evaluated in a simulated IoT-based agricultural system using synthetic sensor data designed to mimic real-world readings of temperature, humidity, soil moisture, and nutrient concentrations. The model achieved a high validation accuracy of 99.55%, indicating its reliability and robustness within the simulated environment. These results demonstrate that the integration of machine learning with real-time sensor data is an effective strategy for automating actuator control in smart greenhouses. The proposed approach has the potential to reduce manual intervention, optimize resource utilization, and improve overall agricultural productivity. This study contributes to the advancement of adaptive, data-driven precision agriculture systems that support long-term food security.