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All Journal Indonesian Journal of Electronics and Instrumentation Systems Jurnal Edukasi Elektro Jurnal Ilmu Komputer JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Manajemen Informatika Buletin Ilmiah Sarjana Teknik Elektro International Journal of Advances in Data and Information Systems Journal of Soft Computing Exploration Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Jarlit Aurelia: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia Adopsi Teknologi dan Sistem Informasi
Faisal Fajri Rahani
Universitas Ahmad Dahlan
Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Social Sciences

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Chatbot Menggunakan Metode Levenshtein Distance Dalam Pencarian Mobil Bekas Arsianto, Muhammad Alif Rahmat Novian; Rahani, Faisal Fajri
Jurnal Ilmu Komputer Vol 16 No 2 (2023): Jurnal Ilmu Komputer
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIK.2023.v16.i02.p01

Abstract

Car as private transportation has an important role as a means to carry out daily activities including going to work, shopping, and other activities. The potential buyer of its vehicle often faces some difficulties related to the price and condition of the car. They were confused about finding information for the required car. Nowadays, technology is used to solve these problems. One of the methods is by using a chatbot application that applies artificial intelligence. Chatbot is a software application that replaces a live human agent to conduct a conversation via text or text to speech. Population in this research are 235 data of used car in 2020. The variables that used are brand, built year, petroleum, transmission, milestone, engine capacity, and price. The natural language programming using levenshtein distance algorithm that can be measured of difference between two strings. The stages including data preparation, cleaning, selection, transformation, grouping questions, implementation of levenshtein distance algorithm, and system testing. The aim to determine whether Chatbot using Levensthein distance algorithm is good enough to help potential buyer of used car. The accuracy value of this method reaches 69% with a total of 40 grouping questions from 2050 data.
Prediction of Planning Value School Shopping Income Budget with Multiple Linear Regression Cahyani Hana Bestari; Faisal Fajri Rahani
International Journal of Advances in Data and Information Systems Vol. 4 No. 1 (2023): April 2023 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i1.1285

Abstract

The School Expenditure Budget Plan or RAPBS is the pillar of school management for allocating the revenue budget and use of school funds to meet all school needs for one year. However, there are problems that occur in the management of the RAPBS, namely the difficulty of grouping the RAPBS data annually, making it difficult to predict the budget for the coming year. This research was conducted to study and implement the Multiple Linear Regression algorithm in predicting the value of data on income and expenditure budget plans which are a reference in planning future budgets. To support predictions of planned school budgets and income, BUMS data, Aid data, School Program Cost data, Original School Revenue data, Other Sources data, and Total Budget data are used. The prediction system method used consists of the planning stage, the analysis stage, the modeling stage, interface design, and implementation using the PHP and MySQL programming languages for database management and system testing and analysis. The results of testing the data analysis using the multiple linear regression method with SPSS software have a 100% result according to the manual calculations performed.
Air quality monitoring using multi node slave IoT Rahani, Faisal Fajri; Fathurrahman, Haris Imam Karim
Journal of Soft Computing Exploration Vol. 5 No. 1 (2024): March 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i1.292

Abstract

Jakarta is the city with the second poorest air quality in the world. IQAir data show that Jakarta's air quality is 159. In addition, the concentration of air particles in Jakarta is 14.2 times higher than the annual guidelines of the World Health Organization (WHO). According to the WHO, exposure to air pollution causes around 7 million premature deaths and millions of years of lost health time each year. Air pollution also stunts children's growth, impairs lung function, etc. Therefore, we need a system that can be used to combine air quality to determine how dangerous a place is with air quality. Knowing air quality, certain policies or actions being taken to overcome this danger. This research aims to build and test a prototype air quality monitoring system using multi-node slaves with the Internet of Things. The prototype development process was carried out by adapting the architectural framework of the air quality monitoring system with the Internet of Things. The testing of prototype results is carried out to sound sensor values and functional success. The results of the test show that the system can run well according to the design made. The DSM501A sensor device functions to detect particles of a size larger than one micrometer, which usually include cigarette smoke, house dust, ticks, spores, pollen, and mildew, and works well so that the controller can read the surrounding air conditions well.
Quadrotor height control system using LQR and recurrent artificial neural networks Rahani, Faisal Fajri; Rosyida, Miftahurrahma
Journal of Soft Computing Exploration Vol. 5 No. 2 (2024): June 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i2.379

Abstract

The quadorotor is a type of unmanned flying vehicle known as Unmanned Aerial Vehicle (UAV). In recent years, quadrotors have attracted much attention from researchers around the world due to their excellent maneuverability. A good control system in this quadrotor system is needed for ease of use of this quadrotor. One control system that is often used is the Linear Quadratic Regulator (LQR) control system. This control system has challenges for dynamic system disturbances in quadrotor control. Researchers proposed a recurrent artificial neural network (RNN) system to address these challenges.RRN is used to change the value of the feedback component in the LQR control system. The nature of the feedback component in LQR, which is static, is changed based on the system error value based on changes in the error value entered into the RNN. The result of this RNN is a change in the value of the LQR feedback component based on the input of the system. The results of this research show that LQR control with RNN produces a faster system response of 0.075 seconds and a faster settling time of 0.221 seconds. Compensation for the system response speed produces a higher overshot value.
Automated Hydroponics System using the Internet of Things Yulianto, Dinan; Nugraha, Abiema Febrian; Rahani, Faisal Fajri
Jurnal Edukasi Elektro Vol. 8 No. 2 (2024): Jurnal Edukasi Elektro Volume 8, No. 2, November 2024
Publisher : DPTE FT UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jee.v8i2.76816

Abstract

The Indonesian government has instituted urban farming regulations to bolster food security and catalyze economic growth. However, implementing urban farming initiatives across various regions of Indonesia is expected to face challenges in the quality and availability of arable land, along with deficiencies in community knowledge. Hydroponics represents a sustainable agricultural approach proposed as a viable solution to address land quantity and quality limitations. This paper presents the comprehensive design and deployment of an automatic monitoring and control system tailored to hydroponic parameters using Internet of Things (IoT) technologies. This system integrates web technology with a NodeMCU microcontroller and sensor devices, such as DHT22 Sensor, SEN011 Sensor, TDS SEN0244 Sensor, DS18820 Sensor, and HC-SR04 Sensor. Web technology was successfully built to display eight hydroponic environmental data variables in real time, including nutrient levels, water pH, water level, water temperature, air temperature, air humidity, and pump performance status. The pH threshold value of water on a scale of 5.0 to 6.5 will automatically control the pH pump, the nutrient threshold value on a scale of 500 to 800 ppm will automatically control the nutrient pump, and the water height threshold value on a scale of 30 to 10 cm will automatically control the water pump. Through web technology, users can also intervene in system performance based on natural plant conditions. The entire system functionality was tested with 25 scenarios through a black box test approach, demonstrating that the hydroponic environment was monitored and controlled efficiently.
Klasifikasi Kesegaran Ikan Pada Citra dengan VGG19 Putri, Arisda Dwi; Rahani, Faisal Fajri
Adopsi Teknologi dan Sistem Informasi (ATASI) Vol. 4 No. 1 (2025): Adopsi Teknologi dan Sistem Informasi (ATASI)
Publisher : Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/atasi.v4i1.2888

Abstract

Ikan merupakan sumber makanan yang sangat bernutrisi dan berprotein tinggi untuk tubuh manusia, Sebagai konsumen memilih ikan dengan mutu yang baik untuk dikonsumsi baik oleh diri sendiri atau keluarga sangatlah penting, apalagi bagi ibu-ibu yang memiliki anak-anak yang masih dalam masa pertumbuhan. Ikan yang tidak segar mempengaruhi rasa dan nutrisi dari ikan tersebut, bahkan dapat membuat keracunan dan mempengaruhi kesehatan pencernaan konsumen. Penelitian ini mengadopsi algoritma Convolutional Neural Network (CNN) dan pendekatan Transfer Learning untuk melakukan klasifikasi tingkat kesegaran ikan berdasarkan citra digital. Jaringan VGG19 seperti arsitektur AlexNet, dengan lapisan konvolusional berurutan dengan filter yang semakin meningkat saat masuk lebih dalam ke dalam jaringan. Penelitian bertujuan untuk membuat sebuah system yang diharapkan dapat mengatasi permasalahan tentang mengklasifikasikan tingkat kesegaran dengan menggunakan CNN dengan pendekatan transfer learning. Evaluasi performa dilakukan dengan menghitung accuracy, precision, recall, f1-score menggunakan metode confusion matrix, untuk mencari nilai terbaik. Hasil penelitian ini system klasifikasi kesegaran ikan menggunakan dua model yaitu Convolutional Neural Network (CNN) dan VGG19 dengan transfer learning. Pengujian dengan menggunakan 1220 data citra diperoleh nilai akurasi sebesar 86% untuk model VGG19.
Pelatihan Pengembangan Konten Digital Dakwah Islam di PRM Bangunharjo I oleh Universitas Ahmad Dahlan Robi'in, Bambang Robi'in,; Prayudha, Prayudha; Rahani, Faisal Fajri; Prathisara, Gibbran; Sari, Eka Anisa
AURELIA: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia Vol 5, No 1 (2026): January 2026
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/aurelia.v5i1.6532

Abstract

AURELIA: Program Pengabdian kepada Masyarakat (PkM) yang dilaksanakan oleh Universitas Ahmad Dahlan (UAD) bertujuan untuk meningkatkan kapasitas anggota Pimpinan Ranting Muhammadiyah (PRM) Bangunharjo I dalam memanfaatkan teknologi digital untuk dakwah Islam. Pelatihan ini mencakup perencanaan konten dakwah digital, pembuatan konten dakwah digital, pengelolaan media sosial, serta strategi komunikasi dakwah berbasis digital. Metode pelatihan meliputi beberapa tahapan yaitu sosialisai, penerapan teknologi, pelatihan, pendampingan, evluasi dan rencana tindak lanjut.  Hasil kegiatan menunjukkan adanya peningkatan yang signifikan dalam pemahaman dan keterampilan peserta dalam membuat serta mengelola konten digital untuk keperluan dakwah. Hasil pre-test menunjukkan bahwa pemahaman peserta berkisar antara 40% hingga 60%, dengan rata-rata keseluruhan 52%. Setelah pelatihan, hasil post-test menunjukkan peningkatan pemahaman menjadi 80% hingga 100%, dengan rata-rata keseluruhan 92%. Peningkatan rata-rata sebesar 40% ini menunjukkan efektivitas pelatihan dalam meningkatkan pemahaman peserta. Dengan adanya program ini, diharapkan PRM Bangunharjo I dapat lebih aktif dan efektif dalam menyampaikan pesan-pesan Islam melalui media digital.
Co-Authors Arsianto, Muhammad Alif Rahmat Novian Ayunita Agustin Baswara, Ahmad Raditya Cahya Cahyani Hana Bestari Cahyani Hana Bestari Fathurrahman, Haris Imam Karim Fitri Indra Indikawati Gibbran Prathisara Miftahurrahma Rosyda Muhammad Iqbal Hadiwibowo Nugraha, Abiema Febrian Oktaf Agni Dhewa Phisca Aditya Rosyady Prayudha, Prayudha Putri, Arisda Dwi Robi'in, Bambang Robi'in, Rosyady, Phisca Aditya Rosyida, Miftahurrahma Sari, Eka Anisa Tri Kuntoro Priyambodo Yulianto, Dinan