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All Journal International Journal of Electrical and Computer Engineering International Journal of Reconfigurable and Embedded Systems (IJRES) 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 Jurnal Penelitian Pendidikan IPA (JPPIPA) 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) JITK (Jurnal Ilmu Pengetahuan dan Komputer) 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 SIENNA Jurnal Informatika: Jurnal Pengembangan IT Advance Sustainable Science, Engineering and Technology (ASSET) Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika JOCHAC
Sunardi, Sunardi
Universitas Ahmad Dahlan Yogyakarta
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Other

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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
Automatic Feeding System in Pond Fish Farming Based on the Internet of Things Tomy Chandra Mahendra; Sunardi Sunardi
Buletin Ilmiah Sarjana Teknik Elektro Vol. 5 No. 2 (2023): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v5i2.5784

Abstract

One of the fish commodities consumed by the Indonesian people is catfish because it tastes good. Cultivation of catfish requires special attention regarding feeding because if it is not enough it can cause the fish to become cannibals, whereas if too much feed can cause disease. Therefore, it is necessary to monitor and control the provision of fish feed on a scheduled basis. This study aims to facilitate catfish farming in automatically scheduled fish feeding by utilizing the Internet of Things (IoT). This system is built using a NodeMCU micro controller which is connected to a Real Time Clock (RTC) sensor to adjust the feeding schedule. In addition, ultrasonic sensors are used to monitor feed conditions and servo motors to open and close the fish feed storage valve. This study succeeded in providing catfish feed automatically and on time according to a predetermined schedule, namely at 06.00 am, 12.00 noon, and 18.00 pm. Timing is based on the active hours of catfish. The system has also been successfully monitored and controlled remotely via the internet using the Blynk application. In addition, the system has also been able to identify the remaining feed reserves remaining in the storage container. This automatic feeding system has been operating in accordance with the purpose of the system, which is to provide fish feed according to the feeding hours of catfish so that cannibals or fish that are sick with ammonia are not found from leftover feed that is not eaten by catfish.
An improved clustering based on K-means for hotspots data Rani Rotul Muhima; Muchamad Kurniawan; Septiyawan Rosetya Wardhana; Anton Yudhana; Sunardi Sunardi; Mitra Adhimukti
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 2: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i2.pp1109-1117

Abstract

Riau province is one of the provinces in Indonesia where forest fires frequently occur every year. Hotspot data is geothermal points and they can be utilized as an indicator of forest fires. Clustering’s method can be used to analyze potential forest fires from hotspot data’s cluster pattern. In this study, hybrid genetic algorithm polygamy with K-means (GAP K-means) was used for hotspot data clustering. GA polygamy was used to determine the initial centroid of K-means. It was used to solve the sensitivity of K-means to the initial centroid, and to find the optimal solution faster. Experimentally compared the performance of GAP K-means, GA K-means, and K-means on the hotspots data, two artificial datasets, and three real-life datasets. Sum square error (SSE), davies bouldin index (DBI), silhouette coefficient (SC) and F-measure are used to evaluation clustering. Based this experiment, GAP K-means outperforms than K-means but GAP K-means still not fast to achieve convergent than GA K-means.
IMPLEMENTASI STRATEGI TEAM ASSISTED INDIVIDUALIZATION UNTUK MENINGKATKAN PARTISIPASI SISWA DALAM PEMBELAJARAN Sunardi; Budi Santosa
Jurnal Genta Mulia Vol. 14 No. 2 (2023): JURNAL GENTA MULIA
Publisher : STKIP Bina Bangsa Meulaboh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61290/gm.v14i2.526

Abstract

Rendahnya partisipasi belajar siswa kelas XI TKR 1 SMK Muhammadiyah 2 Andong pada mata pelajaran pemeliharaan mesin kendaraan ringan. Penelitian ini bertujuan untuk meningkatkan partisipasi belajar siswa XI TKR 1 SMK Muhammadiyah 2 Andong melalui strategi Team Assisted Individualization . Penelitian ini melibatkan 36 siswa dan dilakukan dengan satu siklus meliputi perencanaan, pelaksanaan, pengamatan dan refleksi. Metode penelitian yang digunakan yaitu Penelitian Tindakan Kelas atau yang lebih dikenal dengan (Classroom Action Reseach). Teknik pengumpulan data yang dilakukan ialah observasi, wawancara dan sumber lain yang dianggap mampu mengembangkan penelitian. Data yang diperoleh kemudian diambil kesimpulan dari reduksi dan penampilan data. Hasil penelitian ini menunjukan adanya peningkatan partisipasi siswa sebelum dan sesudah menggunakan model pembelajaran Team Assisted Indivudualization (TAI) partisipasi siswa rata-rata 15 anak (43%) menjadi 19 anak (52%).
Design and Development of a IoT-Based Moisture Detection Device for Corn Seeds Guguh Makbul Rahmadani Fitra; Sunardi Sunardi
Buletin Ilmiah Sarjana Teknik Elektro Vol. 5 No. 3 (2023): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v5i3.8345

Abstract

Lately the planting of corn has increased and increased in several areas. The increasing popularity of corn is due to its high economic value. Corn that has been harvested cannot be sold immediately because it must meet certain moisture content requirements. Farmers must know the maximum value of the moisture content in the corn kernels resulting from the harvest to meet one of the standards set by the industry. The water content contained in corn kernels can have a big influence on determining its quality or selling value. This study aims to design and implement a device for detecting the moisture content of corn kernels as a tool to help farmers produce dry and good quality corn kernels. This research uses an Internet of Things (IoT) based method by sending the corn moisture content and ambient air temperature values to a mobile phone via the Blynk application. The components used are the NodeMCU ESP2866 microcontroller, YL-69 sensor, DHT-22 sensor, 16x2 I2C LCD, and battery. The results of this study have been able to make a water content detector tool on corn kernels based on IoT that can work well. From several tests carried out at night and in the morning, a low error rate of 2.3% was found on the DHT-22 sensor, while on the YL-69 sensor the tests were carried out on three types of corn samples, namely dry, medium, and dry corn kernels. and wet obtained a low error rate of 3.1%.
Medical External Wound Image Classification Using Support Vector Machine Technique Syifa'ah Setya Mawarni; Murinto Murinto; Sunardi Sunardi
Khazanah Informatika Vol. 9 No. 2 October 2023
Publisher : Department of Informatics, Universitas Muhammadiyah Surakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v9i2.22541

Abstract

Diagnosis is an activity that refers to the examination of something. Diagnosis is often associated with medical activities as a determinant of a person's condition, in the health sector diagnosis means a procedure performed by a doctor to determine a patient's condition. Unfortunately, it is rare to diagnose disease using an object wound, whereas if the wound is not treated immediately it can lead to more serious illnesses such as ulcers and tetanus or in some cases it can cause infection which then becomes a complication, in the worst case amputation occurs. The skin protects the body from various threats, the skin is also the first fortress for the body. Before implementing a prototype external wound diagnosis, it is necessary to test the accuracy of the algorithm to be used. The algorithm that can be used for diagnosis or classification is the Support Vector Machine or SVM which in the process goes through 3 stages, namely data collection, preprocessing, and classification. This research obtained the results of feature extraction on the wound image test data using GLCM with a contrast value of 0.0082, a correlation value of 0.9769, an energy value of 0.6391, and a homogeneity value of 0.9959 as well as the accuracy of using the SVM algorithm which was measured using a confusion matrix to get an accuracy value of 96.39%, 93.06% precision, recall 92.85%, and F1-score 92.58%. The results of the accuracy of the classification of external wound images using the SVM algorithm are 92.85%.
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 Ariful Aziz Arizona Firdonsyah Asep Setyaji Azrul Mahfurdz Azrul Mahfurdz Azrul Mahfurdz Bambang Subana Budi Santosa Deco Aprilliansyah Denis Prayogi Denis Prayogi Dewi Sahara Dewi Sahara Nasution Dewi Soyusiawaty 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 Herman Herman Herman Yuliansyah 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 Irhash Ainur Rafiq Jafri Din Janu Prasetyo januari audrey January Audrey Joko Supriyanto Joko Triyanto Kemal Thoriq Al-Azis Khoir, Syaiful Amrial Krisna Astianingrum Lina Handayani Luh Putu Ratna Sundari Lukman Reza Lukman Reza M Murinto M. Ihya A. Elfatih Mardhiatul Ihsaniah Miftahuddin Fahmi Mirza Sutrisno 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 Rajunaidi Rajunaidi 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 Salsabilla Azahra Putri Saputro, Mochammad Yulianto Andi Septiyawan Rosetya Wardhana Sharipah Salwa Mohamed Son Ali Akbar Sri Rahayu Astari Sri Rahayu Astari Sri Winiarti 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 Tri Antoro Tristanti, Novi Ummi Syafiqoh Virasanty Muslimah Wahyu S Aji Watra Arsadiando Wawan Darmawan Wijaya, Setiawan Ardi Yana Mulyana Yuniarti Lestari Yuwono Fitri Widodo