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All Journal International Journal of Electrical and Computer Engineering Emitor: Jurnal Teknik Elektro Jurnal Komtika (Komputasi dan Informatika) Integrated Science Education Journal Jurnal Nasional Teknik Elektro dan Teknologi Informasi Prosiding Simposium Nasional Rekayasa Aplikasi Perancangan dan Industri Prosiding University Research Colloquium Riwayat: Educational Journal of History and Humanities Emitor: Jurnal Teknik Elektro Jurnal Komtika (Komputasi dan Informatika)
Muhammad Kusban
Universitas Muhammadiyah Surakarta
Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Medicine & Pharmacology Social Sciences

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Pengenalan Corak Sidik Tapak Tangan Dengan Menggunakan Algoritme Warkac Kusban, Muhammad; Budiman, Aris; P, Bambang Hari
Jurnal Komtika Vol 1 No 2 (2017): Jurnal Komtika
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (896.083 KB)

Abstract

Pengenalan corak sidik tapak tangan merupakan bagian dari bidang biometrik yang terus melengkapi penggunaan sidik jari karena bukti kejahatan saat ini lebih banyak ditemukan dari bekas guratan tapak tangan dibanding pola jari. Gabungan pilihan algoritme dari kecerahan citra, pilihan parameter Gabor, penggunaan metode pencocokan hingga aplikasi reduksi dimensi sangat berperan dalam  memperoleh  sistem biometrik yang optimal.  Dari uji coba yang telah dilakukan, peneliti  telah berhasil memilih empat algoritme tersebut hingga mencapai nilai akhir yang sangat menjanjikan untuk ditelaah lebih lanjut.
Pengenalan Corak Sidik Tapak Tangan Dengan Menggunakan Algoritme Warkac Kusban, Muhammad; Budiman, Aris; P, Bambang Hari
Jurnal Komtika Vol 1 No 2 (2017)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (896.083 KB) | DOI: 10.31603/komtika.v1i2.1791

Abstract

Pengenalan corak sidik tapak tangan merupakan bagian dari bidang biometrik yang terus melengkapi penggunaan sidik jari karena bukti kejahatan saat ini lebih banyak ditemukan dari bekas guratan tapak tangan dibanding pola jari. Gabungan pilihan algoritme dari kecerahan citra, pilihan parameter Gabor, penggunaan metode pencocokan hingga aplikasi reduksi dimensi sangat berperan dalam  memperoleh  sistem biometrik yang optimal.  Dari uji coba yang telah dilakukan, peneliti  telah berhasil memilih empat algoritme tersebut hingga mencapai nilai akhir yang sangat menjanjikan untuk ditelaah lebih lanjut.
Combination a Skeleton Filter and Reduction Dimension of Kernel PCA Based on Palmprint Recognition Muhammad Kusban; Adhi Susanto; Oyas Wahyunggoro
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 6: December 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3999.933 KB) | DOI: 10.11591/ijece.v6i6.pp3255-3261

Abstract

Palmprint identification is part of biometric recognition, which attracted many researchers, especially when fusion with face identification that will be applied in the airport to hasten knowing individual identity. To accelerate the process of verification feature palms, dimension reduction method is the dominant technique to extract the feature information of palms.The mechanism will boost if the ROI images are processed prior to get normalize image enhancement.In this paper with three sample input database, a kernel PCA method used as a dimension reduction compared with three others and a skeleton filter used as a image enhancement method compared with six others. The final results show that the proposed method successfully achieve the target in terms of the processing time of $ 0.7415 $ second, the EER performance rate of 0.19 % and the success of verification process about 99,82 %.
Verifikasi dan Identifikasi Telapak Tangan dengan Kernel Gabor Muhammad Kusban
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 4 No 2: Mei 2015
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (568.796 KB)

Abstract

In recent years, biometric recognition has been rapidly developed and still continues to grow. Researchers are combining several algorithms to obtain a more robust feature. In this study, Gabor kernel methods, principle component analysis (PCA), detection error trade-off (DET), expected performance curves (EPC), and cumulative match characteristic (CMC) is combined and used to obtain the features of palm print. This experiment shows that the combination of Gabor and PCA methods, using 240 items of data, gives an optimum result in palms identification and authentication.
Prototipe Detektor Gejala COVID-19 Berbasis IoT Muhammad Chafidh Dinulloh; Muhammad Kusban
Emitor: Jurnal Teknik Elektro Vol 22, No 2: September 2022
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/emitor.v22i2.19441

Abstract

Kesehatan sangatlah berperan penting dalam kehidupan kita, sehat adalah salah satu kunci awal untuk meraih kedamaian, keamanan, dan kebebasan untuk melakukan apapun didalam hidup. Namun, meskipun kita semua sudah mengetahui hal tersebut, fenomena COVID-19 yang terjadi beberapa tahun terakhir menambah lagi kepekaan kita tentang seberapa berharga dan pentingnya kesehatan. Menurut data WHO, telah tercatat 6,2 juta kasus COVID-19 di Indonesia sedang 156 ribu diantaranya tidak dapat diselamatkan. Menurut beberapa penelitian, COVID-19 memiliki tiga gejala utama, yaitu demam, batuk, dan sulit bernafas atau sesak sehingga butuh penanganan secepatnya dari pihak kesehatan. Dari beberapa permasalahan tersebut, penulis membuat sebuah alat yang dapat mengukur suhu, denyut jantung, dan kadar saturasi oksigen yang dapat dimonitoring dari jarak jauh menggunakan aplikasi Blynk pada smartphone. Pada pembuatan alat ini penulis menggunakan dua buah mikrokontroler yaitu Arduino UNO dan NodeMCU juga menggunakan dua buah sensor yaitu sensor MLX90614 dan sensor MAX30100. Sensor MLX90614 akan digunakan untuk mengukur suhu tubuh, sedangkan sensor MAX30100 digunakan untuk mengukur denyut jantung dan saturasi oksigen. Hasil pengukuran nantinya akan ditampilkan pada LCD 20x4 dan juga akan ditampilkan pada smartphone menggunakan aplikasi Blynk. Hasil pengujian secara keseluruhan menunjukkan bahwa alat bekerja cukup baik dengan persentase error 3,4% pada suhu tubuh, 1,8% pada denyut jantung, dan 3,21% pada saturasi oksigen.
Alat Penghitung Biaya Pemakaian Air Berbasis IOT Kurniawan Adhi Yulianto; Muhammad Kusban
Emitor: Jurnal Teknik Elektro Vol 23, No 2: September 2023
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/emitor.v22i2.19448

Abstract

Pada kehidupan masa kini air sangatlah penting untuk kebutuhan dalam sehari hari. Kadang penggunaan air ini tidak perhatikan sehingga biaya yang dibutuhkan melebihi dari harga biasanya. Dalam hal ini penulis ingin membuat sebuat alat pengukur debit air lalu ditampilkan dalam bentuk Rupiah. Alat ini memiliki fungsi untuk memantau pemakaian air secara real time. Dengan menggunakan alat yaitu Arduino, Flowmeter, Solenoid Valve, LCD. NodeMCU adalah sebuah board elektronik yang berbasis chip ESP8266 dengan kemampuan menjalankan fungsi mikrokontroler dan juga koneksi internet (WiFi). Flow Meter Sensor adalah alat yang digunakan untuk menentukan keberadaan bahan aliran (cair) dalam jalur aliran, dengan semua aspek aliran itu sendiri, termasuk kecepatan atau laju aliran dan massa atau total volume material yang mengalir dalam lorong. Solenoid valve adalah elemen kontrol yang paling sering digunakan dalam fluidics. Tugas dari solenoid valve adalah untuk mematikan, release, dose, distribute atau mix fluids. Flowmeter akan mengukur aliran air yang nilainya akan ditampilkan pada Display LCD. Dan untuk data real timenya akan ditampilkan pada aplikasi Blynk. 
Image enhancement in palmprint recognition: a novel approach for improved biometric authentication Kusban, Muhammad; Budiman, Aris; Hari Purwoto, Bambang
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i2.pp1299-1307

Abstract

Several researchers have used image enhancement methods to reduce detection errors and increase verification accuracy in palmprint identification. Divergent opinions exist among experts regarding the best method of image filtering to improve image palmprint recognition. Because of the unique characteristics of palmprints and the difficulties in preventing counterfeiting, image-filtering techniques are the subject of this current research. Researchers hope to create the best biometric system possible by utilizing various techniques. These techniques include image enhancement, Gabor orientation scales, dimension reduction techniques, and appropriate matching strategies. This study investigates how different filtering approaches might be combined to improve images. The palmprint identification system uses a 3W filter, which combines wavelet, Wiener, and weighted filters. Optimizing results entails coordinating the 3W filter with Gabor orientation scales, matching processes, and dimension reduction methods. The research shows that accuracy may be considerably increased using a 3W filter with a Gabor orientation scale of [8×7], the kernel principal component analysis (KPCA) dimension reduction methodology, and a cosine matching method. Specifically, a value of 99.722% can be achieved. These results highlight the importance of selecting appropriate settings and techniques for palmprint recognition systems.
Design and Development of Object Detection Radar with IoT-Based Matlab Software Visualization Ihsan, Dias Khairul Ihsan; Fadlilah, Umi; Kusban, Muhammad
Emitor: Jurnal Teknik Elektro Vol 24, No 2: July 2024
Publisher : Universitas Muhammadiyah Surakarta

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

Abstract

Radar is an abbreviation for Radio Detection and Ranging, which means an electromagnetic wave system that functions to detect, measure and map objects in the surroundings. So far, the development of radar technology has tended to focus on object detection without considering effective integration and connectivity. Therefore, this research aims to develop a radar that can detect, measure and differentiate between moving and stationary objects. This research does not only pay attention to the detection aspect, but also integrates Matlab R2022a for visualization, Internet of Things (IoT) for centralized connectivity and the Blynk mobile application to increase the efficiency of object monitoring. This research uses ultrasonic sensors and Passive Infra-Red (PIR) sensors, ultrasonic sensors to read distance parameters and PIR sensors to detect moving or stationary objects. The ultrasonic and PIR sensors will be controlled by the ESP32 and serve as a centralized connectivity system that will connect to a Web server and mobile devices, while the Matlab R2022a software will visualize the environment around the radar at a 180o angle and connect with Thingspeak and the PushBullet mobile application. The results of the test are compared with a standard measuring instrument, namely a meter. In this research analysis, error calculations are used to see the uncertainty value of the sensor readings used. Based on research, the ultrasonic sensor reading accuracy results were 98.99% and for the PIR sensor the sensor could read every test angle starting from 30, 60, 90 120 and 150 degree, however at angles 30 and 150 degree it had quite a long delay.
Prototype Automatic Chicken Feeding Equipment at Putri Ungul Sentosa Farm Kusban*, Muhammad; Kumala, Citra Nur
Riwayat: Educational Journal of History and Humanities Vol 6, No 4 (2023): Educational, Historical Studies and Humanities
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jr.v6i4.35221

Abstract

Indonesia has various economic sectors, including animal husbandry. One of the most numerous farms in Indonesia is chicken farming. One type of chicken farming is laying hens. The success of the breeding itself has various factors, including feeding. With the increasing need for quality feed and efficient feeding systems, there is a need for smarter and more automated chicken feeders. This farm has a problem with uneven feeding, therefore this research will develop automatic chicken feed so that the distribution of chicken feed can be made evenly using an IoT control system. This tool uses the main components in the form of stepper motors and stervo motors, where stepper motors are used as drivers of chicken feed containers while servo motors are used to open or close chicken feed doors. This tool will work with the time that has been set via a smartphone on the bylnk application in the morning and evening. The test results of this automatic feeder take approximately less than 2 minutes, and the weight is reduced between 1.2 - 1.6 kg.
The Impact of Extreme Data Imbalance on Evaluation Metrics of Deep Learning Models for Loan Default Prediction Budiyanto, Irfan; Hermawan, Arief; Avianto, Donny; Kusban, Muhammad
Emitor: Jurnal Teknik Elektro Vol 25, No 2: July 2025
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/emitor.v25i2.10719

Abstract

The growth of financial technology has made online loans more accessible, but it has also increased the risk of borrowers failing to repay. Developing a reliable system to predict loan defaults is therefore very important. A common problem in these predictions is an imbalance in the data – there are far fewer cases of loan defaults (the minority class) than loans that are paid back on time (the majority class). This imbalance can cause the prediction models to be biased. This research specifically investigates the effect of an extremely increased data imbalance ratio (from 1:170 to 1:33,612) on the evaluation metrics of a Deep Neural Network (DNN) model, particularly when using the Adaptive Synthetic Sampling (ADASYN) oversampling technique. The method used involves adopting a previous research approach that combines ADASYN to handle data imbalance and DNN for prediction, applied to an updated Lending Club dataset with a more severe level of imbalance. The results demonstrate a critical breakdown in key evaluation metrics. Compared to previous research, Accuracy remains high (0.9515) and Specificity is strong (0.9516). However, there is a catastrophic decrease in Precision to almost zero (0.0001), a very low Recall (0.1667), and a resulting F1-Score that is also nearly zero (0.0002). A visual analysis using Principal Component Analysis (PCA) reveals that this decline in Precision is caused by synthetic minority samples generated by ADASYN completely overlapping with the original majority cluster, leading to a massive number of false positives. In conclusion, ADASYN fails to maintain a usable performance level under extreme imbalance conditions, rendering the model ineffective for its intended purpose and highlighting the critical need for alternative strategies when dealing with severe minority class scarcity.
Co-Authors Adhi Susanto Aris Budiman Bambang Hari Purwoto Budiyanto, Irfan Donny Avianto Eko Purnomo Firmansyah, Roby Achmad Hasyim Asyari Ihsan, Dias Khairul Ihsan Kumala, Citra Nur Kurniawan Adhi Yulianto Muhammad Chafidh Dinulloh Oyas Wahyunggoro P, Bambang Hari P, Bambang Hari P, Bambang Hari Raihan, Muhammad Akbar Ramadhan Putra, Rafigo Rohmatulloh, Abidin Umi Fadlilah, Umi Wibowo, Tegar Satrio