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Pengembangan Sistem Pengukur pH Air Untuk Menentukan Derajat Asam Basa Media Kolam Ikan Berbasis Internet of Things (IoT) Ramdani, Cecep Muhamad Sidik; Gufroni, Acep Irham; Rachman, Andi Nur; Shofa, Rahmi Nur
CESS (Journal of Computer Engineering, System and Science) Vol 9, No 1 (2024): January 2024
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v9i1.50799

Bidang fisika dapat mempengaruhi keberlangsungan segala sesuatu yang hidup di lingkungan alam secara langsung atau tidak langsung, salah satunya berpengaruh pada kegiatan budidaya ikan. Kualitas air sangat berpengaruh pada kondisi ikan sehingga apabila kualitas air nya tidak memenuhi standar air untuk budidaya ikan, maka akan membuat ikan rawan terserang penyakit bahkan bisa menyebabkan kematian. Ada beberapa parameter yang dapat mempengaruhi kualitas air, diantaranya Ph air. Alat yang digunakan untuk mengukur Ph air yaitu Ph meter. Alat tersebut harus secara langsung di gunakan di lokasi media kolam ikan untuk dapat mengetahui nilai suhu dan Ph air. Dengan kondisi tersebut membuat kegiatan monitoring kolam ikan menjadi kurang efektif dan efisien. Untuk mengatasi hal tersebut maka dibuat suatu sistem monitoring Ph air berbasis Internet of Thing (IoT) yang dapat melakukan pemantauan dan monitoring kolam ikan secara real time. Pada monitoring Ph air ini menggunakan sensor PH-4502C. mikrokontroler yang digunakan yaitu NodeMCU ESP8266 dan Arduino Uno yang di lengkapi dengan Wi-Fi module ESP8266. Hasil pengujian yang di lakukan di tiga titik pada satu kolam ikan dalam rentang waktu 1 jam mempunyai nilai rata-rata 7,56 yang berarti nilai Ph air yang ada pada kolam tersebut masih sedikit di atas batas normal yaitu 7.

Pengujian Parameter Algoritma Genetika dan Feed-Forward Neural Networks pada Permainan Ular Klasik BISRY, AHMAD; RAMDANI, CECEP MUHAMAD SIDIK; YULIYANTI, SITI
MIND (Multimedia Artificial Intelligent Networking Database) Journal Vol 9, No 2 (2024): MIND Journal
Publisher : Institut Teknologi Nasional Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/mindjournal.v9i2.135-152

AbstrakKonfigurasi parameter yang tepat sangat penting untuk memaksimalkan kinerja dari sebuah algoritma. Algoritma genetika dan neural networks memerlukan pemilihan parameter yang sesuai dalam penggunaannya. Pada permainan ular, performa diukur dari score dan efisiensi runtime. Penelitian ini menguji parameter untuk menemukan konfigurasi optimal bagi kedua algoritma. Permainan ular digunakan sebagai model eksperimen karena metrik kinerja yang jelas, seperti score yang didapat dan beberapa rintangan yang ada. Sebanyak 60 eksperimen dilakukan untuk membandingkan jumlah generasi dan populasi, mutation chance, dan jumlah neuron pada hidden layer. Hasil penelitian menunjukkan konfigurasi dengan generasi lebih besar dari populasi adalah yang paling optimal, menghasilkan score setara dengan generasi dan populasi yang sama besar, namun dengan runtime lebih efisien. Mutation chance 0.1% merupakan yang terbaik dibandingkan dengan 0.2% sampai 0.5%. Selain itu, hidden layer dengan 16 neuron lebih efisien dibandingkan 24 neuron, baik dari segi score maupun runtime.Kata kunci: Algoritma genetika, neural networks, Permainan ular klasikAbstract Appropriate parameter configuration is crucial to maximizing algorithm performance. Genetic algorithms and neural networks require careful parameter selection. In the game of Snake, performance is measured by score and runtime efficiency. This research tests parameters to find optimal configurations for both algorithms. Snake serves as an experimental model due to clear performance metrics such as score and various obstacles. Sixty experiments compare generation and population sizes, mutation chances, and neuron counts in hidden layers. Findings indicate that configurations with larger generations than populations are optimal, yielding scores similar to equal-sized generations and populations but with more efficient runtime. A 0.1% mutation chance outperforms rates of 0.2% to 0.5%. A hidden layer with 16 neurons proves more efficient than 24 neurons in both score and runtime aspects.Keywords: Genetic algorithm, neural networks, classic snake game

Pengembangan Sistem Pengukur pH Air Untuk Menentukan Derajat Asam Basa Media Kolam Ikan Berbasis Internet of Things (IoT) Ramdani, Cecep Muhamad Sidik; Gufroni, Acep Irham; Rachman, Andi Nur; Shofa, Rahmi Nur
CESS (Journal of Computer Engineering, System and Science) Vol. 9 No. 1 (2024): January 2024
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v9i1.50799

Bidang fisika dapat mempengaruhi keberlangsungan segala sesuatu yang hidup di lingkungan alam secara langsung atau tidak langsung, salah satunya berpengaruh pada kegiatan budidaya ikan. Kualitas air sangat berpengaruh pada kondisi ikan sehingga apabila kualitas air nya tidak memenuhi standar air untuk budidaya ikan, maka akan membuat ikan rawan terserang penyakit bahkan bisa menyebabkan kematian. Ada beberapa parameter yang dapat mempengaruhi kualitas air, diantaranya Ph air. Alat yang digunakan untuk mengukur Ph air yaitu Ph meter. Alat tersebut harus secara langsung di gunakan di lokasi media kolam ikan untuk dapat mengetahui nilai suhu dan Ph air. Dengan kondisi tersebut membuat kegiatan monitoring kolam ikan menjadi kurang efektif dan efisien. Untuk mengatasi hal tersebut maka dibuat suatu sistem monitoring Ph air berbasis Internet of Thing (IoT) yang dapat melakukan pemantauan dan monitoring kolam ikan secara real time. Pada monitoring Ph air ini menggunakan sensor PH-4502C. mikrokontroler yang digunakan yaitu NodeMCU ESP8266 dan Arduino Uno yang di lengkapi dengan Wi-Fi module ESP8266. Hasil pengujian yang di lakukan di tiga titik pada satu kolam ikan dalam rentang waktu 1 jam mempunyai nilai rata-rata 7,56 yang berarti nilai Ph air yang ada pada kolam tersebut masih sedikit di atas batas normal yaitu 7.

Development of Information System Classification of Community Complaints Based on Keyword Case Study: District Pangandaran Ramdani, Cecep Muhamad Sidik; Rachman, Andi Nur
Journal of Applied Information System and Informatic (JAISI) Vol 2, No 1 (2024): Mei 2024
Publisher : Deparment Information System, Siliwangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/jaisi.v2i1.10795

The growing technology of the public complaint system requires the development to solve the problems that exist in Pangandaran Regency. One of the problems is not applying the classification of complaints based on keywords. So that people still have difficulty understanding the functions of government agencies correctly because there are several government agencies that have similar functions. The development of the complaints system can minimize these errors. System development used is the Extremme Programming method which has four frameworks including planning, design, coding and testing, using UML modeling (Unified Modeling Language). Extreme Programming is the development of the previous method, the Agile method. For testing applications using Black Box Testing is done only to observe the results of execution through test data and check the functional of the software. So that the results obtained are classifiers of public complaints that are directly conveyed to the relevant agencies running well.

Evaluation of Information Technology Governance at DISKOMINFO Tasikmalaya City Using COBIT 2019 Rachmasari Biduri, Nadia; Ramdani, Cecep Muhamad Sidik
Journal of Applied Information System and Informatic (JAISI) Vol 1, No 1 (2023): November 2023
Publisher : Deparment Information System, Siliwangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/jaisi.v1i1.8992

The Office of Communication and Informatics (DISKOMINFO) is an agency engaged in the fields of communication, informatics, coding and statistics. Based on the results of interviews with the Head of Application and Informatics DISKOMINFO Tasikmalaya City, it is known that there are obstacles related to limited resources. Starting from human resources, equipment, budget, and also other supporting facilities. So that an evaluation of information technology governance is needed to determine the capabilities possessed by the information technology. This study uses the COBIT 2019 framework using the RACI diagram as a mapping reference for observation and questionnaire distribution. The domains used are BAI02 (Managed Requirements Definition), DSS02 (Managed Service Requests and Incidents), and MEA01 (Managed Performance and Conformance Monitoring). The results of this study are to determine the capability level in each domain so that the current conditions of the Tasikmalaya City DISKOMINFO are obtained. After carrying out the analysis, it was found that the service performance from the BAI02 domain was at level 4, the service performance from the DSS02 domain was at level 2, and the service performance from the MEA01 domain was at level 3. The results of this service performance measurement made a recommendation to be implemented to increase the value information technology governance in accordance with the needs of DISKOMINFO Tasikmalaya City. Capability level objectives can be increased by carrying out activities that are not yet optimal by the agency until it reaches the full value for each level.

Implementation Of C5.0 Classification And Support Vector Machine Algorithm With Correlation-Based Feature Selection In Application Liver Disease Rachman, Andi Nur; Ramdani, Cecep Muhamad Sidik; Insani, Muhammad Hanif
Journal of Applied Information System and Informatic (JAISI) Vol 2, No 1 (2024): Mei 2024
Publisher : Deparment Information System, Siliwangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/jaisi.v2i1.10848

Liver disease is a general term that refers to a number of disorders or problems that affect the liver. The liver is an important organ in the human body and has many diverse functions, including food processing, protein production, toxin removal, and energy storage. Therefore, when the liver experiences disorders or disease, it can have a serious impact on the overall health and function of the body. Liver disease is a significant global health problem. Early detection as well as classification of liver disease can provide valuable guidance for effective treatment. Based on the problems above, the aim of this research is to create a liver disease classification model using C5.0 and Support Vector Machine with Radial Basis Function (RBF) and Sigmoid kernels. With data obtained from the liver disease dataset. The two methods will be compared and we will find out which one produces the best results. The method used is also optimized with CFS (Correlation Based Feature Selection) feature selection. The results of the classification process, namely the C5.0 Model and Support Vector Machine (RBF) with CFS have a similar accuracy of 76%, while the Support Vector Machine (Sigmoid) has an accuracy of 70%, without feature selection the C5.0 algorithm has an accuracy of 66% , Support Vector Machine between RBF and sigmoid kernels has an accuracy of 69% and 55%.

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