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All Journal International Journal of Electrical and Computer Engineering International Journal of Reconfigurable and Embedded Systems (IJRES) Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Transmisi: Jurnal Ilmiah Teknik Elektro JURNAL SISTEM INFORMASI BISNIS Jurnal Sistem Komputer TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Informatika Disease Prevention and Public Health Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik CommIT (Communication & Information Technology) Bulletin of Electrical Engineering and Informatics Jurnal Teknologi Jurnal sistem informasi, Teknologi informasi dan komputer Sinergi Jurnal Edukasi dan Penelitian Informatika (JEPIN) JUITA : Jurnal Informatika International Journal of Advances in Intelligent Informatics Seminar Nasional Informatika (SEMNASIF) Jurnas Nasional Teknologi dan Sistem Informasi Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika JURNAL NASIONAL TEKNIK ELEKTRO KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Proceeding of the Electrical Engineering Computer Science and Informatics Fountain of Informatics Journal Jurnal Teknologi dan Sistem Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Ilmiah FIFO Emerging Science Journal JIKO (Jurnal Informatika dan Komputer) Jurnal CoreIT Bina Insani ICT Journal JURNAL MEDIA INFORMATIKA BUDIDARMA MUST: Journal of Mathematics Education, Science and Technology IT JOURNAL RESEARCH AND DEVELOPMENT Al-MARSHAD: Jurnal Astronomi Islam dan Ilmu-Ilmu Berkaitan JRST (Jurnal Riset Sains dan Teknologi) JURNAL REKAYASA TEKNOLOGI INFORMASI Jurnal Informatika Universitas Pamulang ILKOM Jurnal Ilmiah Jiko (Jurnal Informatika dan komputer) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer CYBERNETICS JURIKOM (Jurnal Riset Komputer) JUMANJI (Jurnal Masyarakat Informatika Unjani) Informatika : Jurnal Informatika, Manajemen dan Komputer Jurnal Ilmiah Mandala Education (JIME) Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Jurnal Mantik JISKa (Jurnal Informatika Sunan Kalijaga) Buletin Ilmiah Sarjana Teknik Elektro Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Genta Mulia : Jurnal Ilmiah Pendidikan Journal of Robotics and Control (JRC) Journal of Applied Engineering and Technological Science (JAETS) Indonesian Journal of Electrical Engineering and Computer Science Bubungan Tinggi: Jurnal Pengabdian Masyarakat Journal of Innovation Information Technology and Application (JINITA) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Pengabdian Masyarakat Indonesia Jurnal Nasional Pengabdian Masyarakat Techno Jurnal Informatika: Jurnal Pengembangan IT Advance Sustainable Science, Engineering and Technology (ASSET)
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Comparative analysis of Fuzzy Tsukamoto's membership functions for determining irrigated rice field feasibility status Ummi Syafiqoh; Anton Yudhana; Sunardi Sunardi
ILKOM Jurnal Ilmiah Vol 14, No 3 (2022)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v14i3.1156.255-263

Abstract

The representation of the fuzzy set membership curve consisting of trapezoidal, triangular, and linear shapes, has an important role in the fuzzy logic system. The selection of the curve's shapes determines the useable membership function and affects the fuzzy output value. Previous studies generally used curves that had been employed in predecessors or other studies that did not explain the reason for choosing a fuzzy member curve. This condition became problem because there was not a guide in selecting the appropriate membership function model for the parameters used in the fuzzy process so that most researchers only use membership functions that are commonly used in previous studies or in the same case as their research. The purpose of this study was to determine the effect of selecting trapezoidal and triangular curves on the performance of Tsukamoto's fuzzy logic for determining the rice-fields suitability status. The research methodology comprised 3 main stages. The first stage was data collecting, to collect soil pH values, soil moisture, and air temperature in rice fields. The second stage was the implementation of the Tsukamoto fuzzy. At this stage, two membership function curves were used. The third stage was a comparative analysis of Tsukamoto's fuzzy's output of trapezoidal and triangular curves. The results obtained indicate that there is no significant performance difference between the two different membership functions. The results of the research with the trapezoidal membership function have a better accuracy rate of 93% while the triangular membership function has an accuracy rate of 90%.
Optimasi Pengendalian Suhu dan Kelembapan Ruangan di Kota Yogyakarta Menggunakan Metode Fuzzy Sunardi Sunardi; Anton Yudhana; Furizal Furizal
JURIKOM (Jurnal Riset Komputer) Vol 9, No 6 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i6.5060

Abstract

The dry season is a season where most regions in Indonesia experience an increase in temperature. This unstable temperature can have a negative effect on the human body, so a control device is needed according to the needs of the body automatically. This study focuses on optimizing room temperature and humidity control in Yogyakarta City using a fan duty cycle unit with the Fuzzy Tsukamoto method. The ideal temperature and humidity range is obtained from measurements by the Indonesian Board of Meteorology, Climatology, and Geophysics (BMKG). The purpose of this study is to reduce the hot temperature in the room to normal temperature conditions. The calculation results with a temperature of 28.29°C and humidity of 79.06% resulted in a duty cycle of 40.92%. Based on 50 sample data taken each fan rotated for five minutes showed that the average change in temperature was -0.01°C and humidity -0.032%, meaning it could lower 0.01°C and humidity 0.032% every five minutes. This result is considered inefficient considering the very small changes, so in subsequent studies it is recommended to use technology such as air conditioning as a control tool
The Application of The Manhattan Method to Human Face Recognition Sunardi; Abdul Fadlil; Novi Tristanti
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 6 (2022): Desember 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v6i6.4265

Abstract

In face recognition, the input image used will be converted into a simple image, which will then be analyzed. The analysis was carried out by calculating the distance of data similarity. In the process of measuring data similarity distances, they often experience problems implementing complex algorithm formulas. This research will solve this problem by implementing the Manhattan method as a method of measuring data similarity distances. In this study, it is hoped that the Manhattan method can be used properly in the process of matching test images and training images by calculating the proximity distance between the two variables. The distance sought is the shortest distance; the smaller the distance obtained, the higher the level of data compatibility. The image used in this study was converted into grayscale to facilitate the facial recognition process by thresholding, namely the process of converting a grayscale image into a binary image. The binary image of the test data is compared with the binary image of the training data. The image used in this study is in the Joint Photographic Experts Group (JPEG) format. Testing was carried out with 20 respondents, with each having two training images and two test images. The research was conducted by conducting experiments as many as 20 times. Facial recognition research using the Manhattan method obtains an accuracy of 70%. The image lighting used as the dataset influenced the accuracy results obtained in this study. Based on the results of this study, it can be concluded that the Manhattan method is not good for use in facial recognition research with poor lighting.
Best Employee Decision Using Multi Attribute Utility Theory Method Sunardi; Rusydi Umar; Dewi Sahara
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 6 (2022): Desember 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v6i6.4318

Abstract

Selection of the best employee is a form of appreciation that can be shown by the company for the achievements of its employees. This appreciation can motivate employees to be more enthusiastic in improving their performance at work. Appropriate evaluation and decision-making methods need to be taken so that the best employee selection process runs objectively, transparently, and in accordance with established standards. This study aimed to select the best employee candidates at PT Kerry Express Indonesia using the multi attribute utility theory (MAUT) method. The criteria for the selection process as follows: attendance (weight = 2), output obtained (weight = 3), discipline (weight = 3), and reporting (weight= 2). The employees in this study were 30 respondents from 150 populations. The assessment was carried out for three months from January to April 2022. The calculations were carried out using the Microsoft Access tool. The results of calculations using the MAUT method show that the highest rank among all candidates has a score of 7.75 while the lowest rank had a score of 3.25. It can be concluded that the MAUT method can be used to select the best employees at PT. Kerry Express Indonesia effectively and efficiently.
IoT-Based Chili Plant Watering Automation Using NodeMCU ESP8266 and Blynk when the Pump is Running Nuril Mustofa; Sunardi Sunardi
Buletin Ilmiah Sarjana Teknik Elektro Vol. 5 No. 1 (2023): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v5i1.6164

Abstract

Automatic plant watering system can help users in caring for plants. Along with the development of technology, it is possible to monitor and control using the Internet of Things (IoT) from anywhere and anytime as long as the device is connected to the internet. The system designed in this study performs watering on chili plant automatically and in real time monitored through the Blynk application on a smartphone. Automation is carried out based on the moisture value parameter obtained from the capacitive soil moisture sensor as input and the NodeMCU ESP8266 as the controller. The output of the system is water sprinkling that comes out through a 12V DC water pump as an actuator and the Blynk application as a monitor and controller via IoT. Automation and monitoring through smartphones using the Blynk application in this study have been successfully carried out. Watering can be done regularly according to predetermined time intervals automatically and the amount of water given to plants according to their needs. At a humidity that is less than 60% and the schedule is appropriate, the pump will run for 4 seconds with a water discharge of 116.32 ml which has been adjusted to the volume of soil and water needs of chili plant.
Pemilahan Sampah Menggunakan Model Klasifikasi Support Vector Machine Gabungan dengan Convolutional Neural Network Miftahuddin Fahmi; Anton Yudhana; Sunardi Sunardi
JURIKOM (Jurnal Riset Komputer) Vol 10, No 1 (2023): Februari 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i1.5468

Abstract

Waste sorting is a vital process in waste management. The problem with the waste sorting process is that humans feel uncomfortable with the smell of garbage for too long. The problem can be solved by creating a machine learning system to identify the waste type. The purpose of this research is to solve waste management problems using machine learning using the most accurate classification model. The types of wastein this research are limited to only two types: organic and inorganic. Data was collected and revised from the Kaggle dataset. Data were imported into the system using Python. Data was trained and used for classifying the waste based on the image source. Waste images will be determined in their category using the Support Vector Machine model with feature extraction using the Convolution layer. The system successfully performs waste classification using the Support Vector Machine model combined with the Convolutional Neural Network with an accuracy of 96,16% and a loss of 7,25% on the overall category
Comparison of Forensic Tools on Social Media Services Using the Digital Forensic Research Workshop Method (DFRWS) Ghufron Zaida Muflih; Sunardi Sunardi; Imam Riadi; Anton Yudhana; Himawan I Azmi
JIKO (Jurnal Informatika dan Komputer) Vol 6, No 1 (2023)
Publisher : JIKO (Jurnal Informatika dan Komputer)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v6i1.5872

Abstract

Social media applications currently play a role and become part of various human activities, on the other hand social media is also very vulnerable to various crimes. Some crimes on social media can be in the form of hate speech, defamation, fraud, gambling, pornography, and other harmful actions. This research applies the Digital Forensic Research Workshop (DFRWS) method to search for all data on twitter social media services running on the Android operating system using MOBILedit Forensic Express and Belkasoft Evidence Center tools. Twitter social media services in this research are used for activities by utilizing all the features in it. Activities carried out by twitter users become evidence that will be acquired using MOBILedit Forensic Express and Belkasoft Evidence Center tools. From the two tools used, a comparison was obtained that MOBILedit Forensic Express found more data on twitter social media than Belkasoft Evidence Center, the findings in these two tools made several contributions to social media investigations that run on the android operating system
Monitoring the Performance of Lecturers Using Behaviorally Anchor Rating Scale and Management by Objectives Method Muhammad Sabiq Dzakwan; Sunardi Sunardi; Anton Yudhana
JUITA: Jurnal Informatika JUITA Vol. 11 No. 1, May 2023
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v11i1.15354

Abstract

Mutiara Mahakam Samarinda Institute of Health Sciences (STIKES-MM Samarinda) has a system for monitoring and evaluating the performance of lecturers or education staff. This system measures performance achievements in terms of teaching, research, and community service. . Nevertheless, since every segment of the system is not yet fully computerized, this then raises several obstacles in the process of monitoring and evaluating the performance, length of time to obtain the final assessment results and the low accuracy level of the assessment. This study aims to seeks solutions to these obstacles and offers an educator performance monitoring system that combines the Behaviorally Anchor Rating Scale (BARS) and Management by Objectives (MBO) methods to be assessed quantitatively based on the rating scores in measuring the two methods. The BARS method was focused on evaluating behaviour that would affect overall performance with an average score of 4.14%, while the MBO method was focused on evaluating according to Tri Dharma of higher education, namely teaching, research and community service.  The assessment system was then implemented to evaluate the performance of lecturers and education staff. Subsequently, the data obtained were analyzed to get the final result of the assessment. In particular for data from the MBO method, the analysis was carried out using step with and without KRA. This exploratory research succeeded in presenting the final results of the performance assessment of each lecturer who was assessed for both the value of the BARS and MBO methods. Data analysis from the MBO method ,  when calculated with and without KRA and KRA, showed some significant differences in MBO. For all lecturers, the difference in scores, if the average was 3.48%, then this assessment was more inclined to the BARS assessment, which had a better rating than MBO.
Penentuan Penerimaan Karyawan Menggunakan Metode Simple Additive Weighting dan Weight Product Ermin Al Munawar; Sunardi Sunardi; Abdul Fadlil
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 11, No 2 (2021): Volume 11 Nomor 2 Tahun 2021
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol11iss2pp117-124

Abstract

Recruitment errors influence in a decrease of quality, performance, and company revenue. One of the causes is the absence of a method that is applied as a systematically of information system in determining the acceptance of the best prospective employees. This study uses the Simple Additive Weighting (SAW) and Weight Product (WP) methods to build an objective, fast, and accurate of Decision Support System (DSS) in determining employee acceptance. This research case study was applied to the Indonesian Market Traders Cooperative (KOPPI) Sorong City, West Papua Province by involving a number of 10 alternative applicants. This study aims to produce an objective information system and provide convenience in determining the best employees, referring to the determination of 9 criteria obtained from interviews, namely education, work experience, motivation, intrapersonal ability, achievement orientation, sales ability, self-confidence, trustworthy, and work ethic by weighting each. SAW and WP methods are both used to determine the best ranking of all alternative applicants and get the best prospective employees. The information system was built using the Waterfall development method with the PHP programming language and Mysql database. Based on the results of research that has been carried out, it is found that the information system built has 100% conformity of functionality and compatibility between manual and application system. Both methods provide the same highest alternative to be used as the determination of the best employee acceptance, however it is found that the WP method provides better accuracy and validity than SAW.
Comparison Analysis of Brain Image Classification Based on Thresholding Segmentation With Convolutional Neural Network Alwas Muis; Sunardi Sunardi; Anton Yudhana
Journal of Applied Engineering and Technological Science (JAETS) Vol. 4 No. 2 (2023): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v4i2.1583

Abstract

Brain tumor is one of the most fatal diseases that can afflict anyone regardless of gender or age necessitating prompt and accurate treatment as well as early discovery of symptoms. Brain tumors can be identified using Magnetic Resonance Imaging (MRI) to detect abnormal tissue or cell development in the brain and surrounding the brain. Biopsy is another option, but it takes approximately 10 to 15 days after the inspection, so technology is required to classify the image. The goal of this study is to conduct a comparative analysis of the greatest accuracy value attained while classifying using segmentation with thresholding versus segmentation without thresholding on the CNN method. Images are assigned threshold values of 150, 100, and 50. The dataset consists of 7023 MRI scans of four types of brain tumors: glioma, notumor, meningioma, and pituitary. Without utilising thresholding segmentation, the classification yielded the highest degree of accuracy, 92%. At the threshold of 100, classification by segmentation received the highest score of 88%. This demonstrates that thresholding segmentation during CNN model preprocessing is less effective for brain image classification
Co-Authors Abd. Rasyid Syamsuri Abdul Djalil Djayali Abdul Fadlil Abdul Fadlil Abdul Fadlil Abdul Fadlil Abdul Fadlil Abdul Fadlil Abdul Hadi Achmad Dito Ahmad Azhar Kadim Ahmad Ikrom Ahmad Raditya Cahya Baswara Ahmad Syahril Mohd Nawi Aldi Bastiatul Fawait Fawait Alfian Ma’arif Alwas Muis Anggit Pamungkas Anton Yudhana Anton Yudhana Anton Yudhana Anton Yudhana Apik Rusdiarna Indra Praja Ardiansyah Ardiningtias, Syifa Riski Ardiningtias Arief Setyo Nugroho Arif Wirawan Muhammad Ariful Aziz Arizona Firdonsyah Asep Setyaji Azrul Mahfurdz Azrul Mahfurdz Azrul Mahfurdz Bambang Subana Budi Santosa Denis Prayogi Denis Prayogi Dewi Sahara Dewi Sahara Nasution Doddy Teguh Yuwono Dwi Aryanto Dwi Aryanto Eko Aribowo Eko Handoyo Ermin Al Munawar Ermin Ermin Evrynda Widyasari Puspa Dewi Faqihuddin Al-anshori Fatma Nuraisyah, Fatma Fiftin Noviyanto Fijaya Dwi Bima Sakti Putra Fijaya Dwi Bima Sakti Putra Fijaya Dwi Bimasakti Firdonsyah, Arizona Fitriyani Tella Fitriyanto, Rachmad Furizal Furizal Furizal Furizal Gema Kharismajati Guguh Makbul Rahmadani Fitra H. Ahmad Hartanta, Agus Jaka Sri Hartini, Sri Haryani Alamsyah Herman Herman Herman Herman Hernawan Aji Nugroho Heru Hermawan Hikmatyar Insani Himawan I Azmi Ibnu Muakhori Ihyak Ulumuddin Iif Alfiatul Mukaromah Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Irhash Ainur Rafiq Jafri Din Janu Prasetyo januari audrey January Audrey Joko Supriyanto Joko Triyanto Kemal Thoriq Al-Azis Khoir, Syaiful Amrial Lina Handayani Luh Putu Ratna Sundari Lukman Reza Lukman Reza M Murinto M. Ihya A. Elfatih Mardhiatul Ihsaniah Miftahuddin Fahmi Mitra Adhimukti Muchamad Kurniawan Muchlas, Muchlas Muchrisal Muchrisal Muchrisal Muflih, Ghufron Zaida Muh. Hajar Akbar Muhammad Amirul Mu'min Muhammad Fauzan Gustafi Muhammad Fauzan Gustafi Muhammad Kunta Biddinika Muhammad Kunta Biddinika Muhammad Nashiruddin Darajat Muhammad Nur Ardhiansyah Muhammad Sabiq Dzakwan Muhammad Sabiq Dzakwan Muntiari, Novita Ranti Murinto Murinto Musri Iskandar Nasution Muzakkir Pangri Nasirudin Nasirudin Nazuki Nazuki Nugroho, Hernawan Aji Nur Makkie Perdana Kusuma Nur Ratnawati Nuril Mustofa Pahlevi, Ryan Fitrian Panggah Widiandana Pradana Ananda Raharja Priyatno Priyatno Puji Ristianto Puriyanto, Riky Dwi Rachmad Fitriyanto Rachmad Very Ananda Saputra Raja Bidin Raja Hassan Rani Rotul Muhima Restu Prima Yudha Restu Prima Yudha Rezki Ramdhani Ricky Irawan Putra Rifkan Firdaus Rio Dwi Listianto Rio Ikhsan Alfian Rosmini Rosmini Rusydi Umar Rusydi Umar Rusydi Umar Rusydi Umar Saberi Mawi Sahiruddin Sahiruddin Saifullah, Shoffan Saputro, Mochammad Yulianto Andi Septiyawan Rosetya Wardhana Sharipah Salwa Mohamed Son Ali Akbar Sri Rahayu Astari Sri Rahayu Astari Sri Winiarti Subrata, Arsyad Cahya Sukma Aji Supriyanto Syaiful Khoir Syed Abdullah Syed Abdullah Syifa Riski Ardiningtias Syifa'ah Setya Mawarni Syifa’ah Setya Mawarni Tole Sutikno Tomy Chandra Mahendra Tresna Yudha Prawira Tresna Yudha Prawira Tri Antoro Tristanti, Novi Ummi Syafiqoh Ummi Syafiqoh Virasanty Muslimah Wahyu S Aji Watra Arsadiando Wawan Darmawan Wijaya, Setiawan Ardi Yana Mulyana Yuniarti Lestari Yuwono Fitri Widodo