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All Journal INFORMAL: Informatics Journal Proceeding of the Electrical Engineering Computer Science and Informatics KOMPUTIKA - Jurnal Sistem Komputer Bubungan Tinggi: Jurnal Pengabdian Masyarakat TEKIBA : Jurnal Teknologi dan Pengabdian Masyarakat Prosiding Konferensi Nasional PKM-CSR
Nova El Maidah
Universitas Jember
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Mechanical Engineering Nursing Public Health Social Sciences Other

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Journal : INFORMAL: Informatics Journal

 1 
Implementasi Metode Fuzzy Sebagai Sistem Kontrol Kepekatan Nutrisi Otomatis Tanaman Hidroponik Berbasis Mikrokontroler Pasa Rangkaian Nutrient Film Technique (NFT) Kurniawan Dwi Yulianto; Achmad Maududie; Nova El Maidah
INFORMAL: Informatics Journal Vol 7 No 1 (2022): Informatics Journal (INFORMAL)
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v7i1.29386

Abstract

Hydroponics is a method of cultivating plants by utilizing water as a growth medium by emphasizing on meeting the nutritional needs of hydroponic plants. Hydroponics requires special treatment such as maintaining nutrient levels within the range so that the use of a control system is used. The implementation of the automatic nutrition control system aims to make it easier for farmers to regulate the mixing of AB mix + POC nutrients with water at the PPM value of lettuce plants automatically based on the age of plant growth, so that farmers can produce plants with optimal growth and maximum yields. The hydroponic nutrition control system uses the Fuzzy method. The system will also be integrated with the Arduino Uno microcontroller which is equipped with a Total Dissolved Solids (TDS) sensor. The results of this study can be seen that the success of the system can work well in detecting nutrients in the reservoir and can control pumps and water pumps in low, normal, and high conditions. The sensor used can also work well, where the TDS sensor has an error value of 4.81% and then calibration is carried out so that it gets the equation for the TDS value
A Fuzzy Control System for Temperature and Humidity Warehouse Control Nova El Maidah; Agfianto Eko Putra; Reza Pulungan
INFORMAL: Informatics Journal Vol 1 No 2 (2016): INFORMAL : Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

A control system is designed to control certain parameters in the system. The desired state maintained is called a steady state. Control actions however may perform something that makes the system experiences a state of overshoot before reaching the steady state. A fuzzy control system can be used to control the system to reach the steady state without overshoot. In this paper, a model of Mamdani's fuzzy inference process is proposed as the basis for this control. MIN operator is used for inference process if there is only one active rule, while MAX operator is used for composition of inferences if there are more than one active rule. A prototype of the fuzzy controller for temperature and humidity achieves an accuracy of 83.33% for temperature controller and an accuracy of 63.33% for humidity controller.
Perbandingan Algoritma Genetika dengan Algoritma Greedy Untuk Pencarian Rute Terpendek Rizky Berlia Oktaviandi; M. Sadid Tafsirul Hadi; Alanfansyah Ghozy Santoso; Nova El Maidah
INFORMAL: Informatics Journal Vol 3 No 1 (2018): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v3i1.9847

Abstract

In everyday life we ​​often travel from place to place. So that we need to consider the time and cost efficient. Therefore, accuracy is needed to determine the shortest path as a consideration in decision to show the path to be taken. The results obtained also require speed and accuracy with the help of a computer. Using or functioning a computer there must be a distributed program in it. The programs contained in the computer vary widely and each program must use an algorithm. Algorithm is a collection of commands to solve a problem gradually from start to finish. There are various algorithms that can be used to find the shortest route such as Breadth First Search algorithm, Depth First Search, A *, Hill Climbing and others. For that required comparison algorithm which is able to find the shortest route accurately and efficiently. In this journal, the algorithm to be compared is the genetic algorithm and greedy algorithm to find the shortest route on a map. Some aspects to be compared are aspects of the accuracy, speed, and complexity of genetic algorithms and greedy algorithms for the shortest route search.
Algorithm Model of K-means for Poor Households Classifying Panggih Pawenang; Nova El Maidah
INFORMAL: Informatics Journal Vol 4 No 2 (2019): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v4i2.14469

Abstract

Poverty is a complex problem experienced by majority of world’s nations especially in the developing countries such as Indonesia. Poverty countermeasure has become the main country development program as one of the indicators of development success is the decrease of poverty rate. Various programs either in national or regional scale have been made as the government’s attempt to reduce the poverty rate. However, there have been a lot of news reports covering the government’s programs which are less precise and even not on the target. Thus, it is essential to have a method which can be implemented to help the planning process of those poverty alleviation programs. This study aims at explaining the formation of K-means algorithm model for classifying poor households; taking a study case in Banyumas Regency, Central Java. The result of this study was K-means algorithm model which has been adapted to the poverty concept from the Statistics Indonesia (BPS) as well as the factors affecting the household poverty. The information obtained from each cluster formed is household characteristics, estimation of household number, and estimation of population experiencing poverty.
Perbandingan Metode Analytical Hierarchy Process (AHP) dan Himpunan Keanggotaan Fuzzy pada Penilaian Kinerja Dosen Noni Namida Oliviani; Haris Rafi; Mochammad Febri Hariyadi; Nova El Maidah
INFORMAL: Informatics Journal Vol 3 No 2 (2018): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v3i2.9985

Abstract

Utilization of artificial intelligence has been imposed into many things, one of them on the assessment of lecturer's performance, one of them on the lecturer's performance assessment. Artificial intelligence can help and facilitate a person to solve a particular problem. In general, the purpose of lecturer performance assessment is to determine the best lecturer's order through predetermined criteria. Decision Making Method (AHP) and Function Membership Fuzzy is a method often used to determine lecturer performance assessment. There is a method that is a form of calculation whose output is the value of several lecturers who entered the assessment list. The purpose of the comparison is to know which artificial intelligence method is best applied to the lecturer's performance assessment. The method used to test the artificial intelligence applied to the lecturer's performance assessment is to use a comparison scenario. Based on the analysis that has been done, the result that artificial intelligence using AHP method and Membership Sets Fuzzy have balanced result. Based on the document can be concluded that in this study AHP method is a superior method in terms of accuracy, while the Fuzzy method is superior in terms of effectiveness.
Analisis Sentimen Opini Publik Terhadap Program Vaksinasi Covid-19 Di Indonesia Pada Twitter Menggunakan Metode Naive Bayes Classifier Priza Pandunata; Kukuh Tri Winarno N; Yanuar Nurdiansyah; Nova El Maidah
INFORMAL: Informatics Journal Vol 7 No 3 (2022): Informatics Journal (INFORMAL)
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v7i3.34930

Abstract

The COVID-19 virus emerged in December 2019 in China and actively spread throughout the world including Indonesia in early 2020. Its spread is very fast and has caused millions of deaths. Therefore, the Indonesian government is actively holding a COVID-19 vaccination program to prevent the spread of the virus and make the public immune to the virus. But the program invites pros and cons among the community. Twitter is one of the social media that is famous for being a medium of opinion from the general public. The process of sentiment analysis can find and solve problems based on public opinion on social media such as Instagram. The classification method used in this research is Naïve Bayes Classifier. The dataset can be obtained from data crawling process using Google Collabs and python programming language. The total dataset obtained is 2000. The data the labelled as positive, neutral, or negative. The labelling process result showed 1579 positive data, 277 negative data, and 144 neutral data. Then pre-processing is carried out on the data that has been labeled before, also word weighting process using TF-IDF. After that modelling is carried out using Naïve Bayes Classifier and the last process is evaluation-testing. The high accuracy of the result from fourth experiment which compare 90% data training with 10% data testing produce 86% accuracy. While the result of sentiment test show that positive sentiment more than negative sentiment and neutral sentiment.
Co-Authors Achmad Maududie Agfianto Eko Putra Alanfansyah Ghozy Santoso Amalia, Karina Nine Diksy M Firmansyah Dini Kurniawati Erika Neferia Laurentina Furqon, Muhammad Ariful Hanny Rasni, Hanny Hardja, Ivan Haris Rafi Ivan Hardja Kukuh Tri Winarno N Kurniawan Dwi Yulianto M. Sadid Tafsirul Hadi MHD. Reza M.I. Pulungan Mochammad Febri Hariyadi Mohammad Zarkasi Noni Namida Oliviani Oktalia Juwita Pandunata, Priza Panggih Pawenang Priza Pandunata Rizky Berlia Oktaviandi S Slamin Vida Komaria Yanuar Nurdiansyah