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INDONESIA
Indonesian Journal of Electronics and Instrumentation Systems
Published by Universitas Gadjah Mada
ISSN : 20883714     EISSN : 24607681     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems), a two times annually provides a forum for the full range of scholarly study. IJEIS scope encompasses all aspects of Electronics, Instrumentation and Control. IJEIS is covering all aspects of Electronics and Instrumentation including Electronics and Instrumentation Engineering.
Arjuna Subject : -
Articles 300 Documents
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Seleksi Fitur dengan Artificial Bee Colony untuk Optimasi Klasifikasi Data Teh menggunakan Support Vector Machine Suhaila Suhaila
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 12, No 1 (2022): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijeis.63902

Abstract

Teh dapat dikenal kualitasnya melalui aroma yang dihasilkan. Penelitian klasifikasi teh menggunakan e-nose umumnya hanya mendeteksi kualitas aroma menggunakan general sensor gas. Namun, adanya redundansi fitur sensor dapat menyebabkan penurunan performa sistem e-nose. Oleh karena itu diperlukan sebuah sistem yang dapat menyeleksi fitur sehingga performa klasifikasi menjadi lebih optimal. Pada penelitian ini dibentuk sistem perangkat lunak yang mampu menyeleksi fitur untuk mengoptimalkan performa klasifikasi. Data input untuk sistem adalah respon sensor e-nose terhadap 3 kualitas teh hitam dengan jumlah sampel 300. Fitur yang diseleksi berupa sensor-sensor pada instrumen e-nose. Proses seleksi fitur dilakukan dengan pendekatan wrapper, algoritma ABC digunakan untuk seleksi fitur, kemudian hasil fitur yang terpilih dievalusi dengan klasifikasi menggunakan SVM. Hasil sistem ABC-SVM kemudian dibandingkan dengan sistem SVM tanpa seleksi fitur. Hasil penelitian menunjukkan bahwa dari 12 sensor e-nose, sensor yang paling mencirikan teh hitam kualitas 1-3 yaitu sensor TGS 2600, TGS 813, TGS 825, TGS 2602, TGS 2611, TGS 832, TGS 2612, TGS 2620 dan TGS 822. Sedangkan untuk sensor MQ-7, TGS 826 dan TGS 2610 merupakan sensor yang redundant pada sistem dikarenakan gas yang dideteksi oleh 3 sensor tersebut dapat diwakili oleh sensor lainnya. Dengan berkurangnya fitur menjadi 9, performa akurasi klasifikasi meningkat 16,7%.
Pembelajaran Mesin untuk Sistem Keamanan - Literatur Review Nuruddin Wiranda; Fal Sadikin; Wanvy Arifha Saputra
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 12, No 1 (2022): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijeis.69022

Abstract

Security systems are one of the crucial topics in the era of digital transformation. In the use of digital technology, security systems are used to ensure the confidentiality, integrity, and availability of data. Machine learning techniques can be applied to support the system's adaptability to the environment, so that prevention, detection and recovery can be carried out. Given the importance of these things, it is necessary to review the literature to find out how machine learning is applied to security systems. This paper presents a summary of 31 research papers to determine what machine learning techniques or methods are the most promising for prevention, detection and recovery. The research stages in this paper consist of 6 stages, namely: formulating research questions, searching for articles, documenting search strategies, selecting studies, assessing article quality, and extracting data obtained from articles. Based on the results of the study, it was found that the K-means method was the most promising for prevention, while for detection, SVM could be used, and for security recovery, machine learning could be implemented using NLP-based features.
Sistem Peringatan Tingkat Kerentanan Bangunan Berbasis Sensor IMU dengan Metode Fuzzy Muhammad Fikri Ahsanandi; Lukman Awaludin
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 12, No 1 (2022): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijeis.70141

Abstract

Negara Indonesia merupakan salah satu negara yang memiliki potensi besar terhadap terjadinya gempa bumi. Bangunan yang merupakan salah satu infrastruktur yang sangat penting bagi kehidupan manusia, merupakan sasaran utama bagi bencana alam gempa bumi yang sering terjadi dan dapat menimbulkan kerusakan yang tidak terduga. Oleh karena itu, diperlukan sebuah sistem peringatan yang dapat mengukur dan mengamati getaran yang terjadi dengan besar tertentu untuk mengetahui tingkat kerentanan bangunan tersebut.Sistem ini menggunakan metode logika fuzzy Mamdani dengan proses defuzzyfikasi centroid. Logika fuzzy tersebut digunakan pada sistem peringatan untuk menentukan tingkat bahayanya. Masukan dari sistem terdiri dari nilai resonansi bangunan dan nilai simpangan bangunan. Masukan tersebut diperoleh dari pembacaan sensor IMU MPU6050. Proses defuzzyfikasi menghasilkan nilai keluaran crisp berupa rentang keputusan alarm. Data yang diolah dari pembacaan sensor ditampilkan dalam web server sebagai antarmuka.    Berdasarkan hasil pengujian sistem peringatan tingkat kerentanan pada purwarupa bangunan yang telah dilakukan, akurasi logika fuzzy mencapai 95% dari 20 kali pengambilan data. Sistem peringatan yang dirancang dapat berjalan secara real time. Secara keseluruhan proses mulai dari pembacaan sensor hingga akuisisi data dapat berjalan dengan baik.     
Klasifikasi Suara Paru-Paru Berdasarkan Ciri MFCC Dody Rafiqo; Yohanes Suyanto; Catur Atmaji
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 12, No 1 (2022): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijeis.70813

Abstract

The lungs are an important organ in the human respiratory system, which functions to exchange carbon dioxide from the blood with oxygen in the air. Detection of respiratory disorders and lung disorders can be done in various ways; view medical records, physical examination, detection by x-ray and also auscultation of breathing. Digital signal processing can be used as a method to detect lung disorders based on the sound produced. In this study, lung sounds were classified into normal, crackle, wheeze, and crackle-wheeze classes using the Mel Frequency Cepstral Coefficient (MFCC) and Convolutional Neural Network (CNN) methods.Observations were made by varying the MFCC feature extraction using MFCC 8 and 13 coefficients, the number of frames are 50 and 60, and the width of the frames used was 0,1, 0,15 and 0,2 seconds. The result of feature extraction is then applied to the CNN classification system, and the confusion matrix is used to get the accuracy and precision values. The highest accuracy and precision values were obtained at 71,85% and 65,70% on the MFCC 13 coefficient with an average of 71,18%. Based on these results, the system that has been created can classify normal lung sounds, crackle, wheeze and crackle-wheeze quite well.
Sistem Pengawasan Physical Distancing di Tempat Umum Menggunakan Kamera Berbasis Deep Learning Rizqy Arya Dinata; Ika Candradewi; Bambang Nurcahyo Prastowo
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 12, No 1 (2022): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijeis.70886

Abstract

Pembatasan jarak fisik merupakan salah satu cara yang diterapkan untuk mencegah penyebaran virus pada tempat umum. Pelaksanaan pembatasan jarak fisik tersebut memerlukan pengawasan agar berhasil sesuai harapan. Pengawasan yang dilakukan secara manual terutama pada tempat dengan tingkat keramaian tinggi kurang efektif karena memerlukan banyak petugas di lokasi yang justru akan menambah keramaian.Pada penelitian ini dikembangkan purwarupa sistem pengawasan pembatasan jarak fisik dengan memanfaatkan kamera CCTV dengan pemrosesan citra digital berbasis computer vision dan deep learning. Metode yang digunakan adalah kombinasi pendeteksian dan pelacakan pedestrian dengan YOLOv4 dan DeepSORT. Metode trigonometri digunakan dalam proses estimasi jarak untuk mendeteksi pelanggaran pembatasan jarak oleh pedestrian. Pada penelitian ini didapatkan hasil pengujian dengan nilai terbaik recall 0,86; precision 0,69 dan mean average precision (mAP) sebesar 0,83 dengan metode pelatihan transfer learning model YOLOv4 dengan maksimum batch 6000 menggunakan 473 data latih dan 119 data validasi. Keseluruhan sistem mencapai kecepatan rata-rata proses real-time yakni pada 24 sampai 26 FPS.
Pemodelan Harmonik untuk Pelafalan Makhraj Huruf Hijaiah Muhammad Fadhlullah; Catur Atmaji
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 12, No 1 (2022): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijeis.71664

Abstract

Learning to pronounce hijaiah letters needs to be assessed objectively, so it is necessary to form digital audio resulting from the synthesis of Harmonic Plus Residual (HPR) modeling, which conducted with two pronunciation methods, taskin and tasydid. The experiment consists data acquisition, signal cutting, framing and windowing, detection of fundamental and harmonic frequencies, synthesis of HPR, to produce synthetic signals. The results of the synthetic signals then analyzed qualitatively by signal spectrogram analysis and scoring.From the experimental results, it can be concluded that this study was ultimately unable to determine the best HPR parameters, but concluded that the tasydid method was the best method for learning pronunciation and for the HPR model synthesis. This is because the tasydid method with different parameters but all of them can produce good synthetic signal, both in terms of comparative analysis of similar signal spectrograms and from the results of scoring with an average value of 10. On the other hand, the taskin method harf shows unsatisfactory results, where the synthetic sound is mostly just noise, so the scoring results is under 9, and is reinforced by the results of the spectrogram comparison between the original and synthetic signals which visually different.
Prediksi Diabetes Berdasarkan Pengukuran Mean Amplitude Glycemic Excursion (MAGE) Menggunakan Naïve Bayes Lailis Syafa’ah; M Syaiful Ma’arif; Amrul Faruq
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 12, No 1 (2022): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijeis.72608

Abstract

 The mean amplitude of glycemic excursions (MAGE) is an important indicator in the assessment of glycemic variability (GV) which is used as a reference for continuous blood glucose control. In this case, quantitative considerations in monitoring blood sugar in diabetes are very important for diagnosis and then proceed with clinical treatment. This study focuses more on strengthening the training and testing data processing system and reducing the independent variables that occur during the classification process. To support this purpose, this study uses Cross Validation as a training and testing data processing with the number of K-Fold is 10 and Naïve Bayes as a classification method. The resulting accuracy is 93% which is an increase from previous studies with an RMSE value (error value) of 0.267. It was concluded that patients in the pre-diabetic and diabetic groups tend to have more varied blood glucose values than patients from the normal class.
Analisis Gap Evaluasi Kualitas Sistem E-Learning di Universitas Ibn Khaldun Bogor Ritzkal Ritzkal; R. Fitria Rachmawati
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 12, No 1 (2022): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijeis.72631

Abstract

A GAP analysis has been conducted on the evaluation of E-Learning systems of LMS UIKA Bogor. Five (5) subjects of discussion in this study, namely include Structured Learning Methods, Unstructured Learning Methods, Population and Samples, E-learning User Activity Record, Evaluation of Results. Process of evaluating the results of a calculation of the System Usability Scale (SUS). Judging from usability or usefulness the e-learning system is feasible. With the following details: a. Based on acceptability ranges, the e-learning falls into the accepted category, b. Based on the grade scale, included in grade C where the SUS score produced is 79, c. Based on adjective ratings, the value is between a score of 70-80 which means it falls into the range of good categories. The results of the usability evaluation of LMS UIKA Bogor products stated that overall, were acceptable or feasible.
Controlling and Monitoring of Temperature and Humidity of Oyster Mushrooms in Tropical Climates I Gusti Made Ngurah Desnanjaya; Putu Sugiartawan
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 12, No 1 (2022): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijeis.73346

Abstract

Controlling the temperature and humidity of oyster mushroom cultivation is done manually by spraying air on the mushroom container so it takes a lot of time and effort. This is done to meet the requirements for growing oyster mushrooms which are strongly influenced by temperature and humidity conditions so that they can grow well. In this study, a device for controlling and monitoring the temperature and humidity of oyster mushroom cultivation was made automatically based on Arduino UNO. This tool can regulate and monitor the temperature and humidity in oyster mushroom cultivation automatically so that the temperature and humidity can be maintained without having to spend a lot of time and effort. The components used in building the automatic temperature and humidity controller for mushroom cultivation based on the Arduino UNO are the dht11 sensors, Arduino UNO, L298N driver, relay, and 16x2 I2C LCD. From the results of the tests that have been carried out, it can be concluded that the temperature and humidity control and monitoring device for automatic oyster mushroom cultivation based on Arduino UNO has been able to work well in regulating and monitoring temperature and humidity as expected.
Penempatan Posisi Transduser Ultrasonik Pada Penampang Pipa untuk Pengukuran Laju Aliran Fluida Lalu Febrian Wiranata; I Wayan Raka Ardana
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 12, No 1 (2022): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijeis.74151

Abstract

Fluid flow rate measurement is important in industries, especially determining fluid flow rate. This process requires a good level of precision and accuracy because it refers to each volumetric's price or custody transfer processor. Many devices are used to measure flow rates, but from some devices, ultrasonic flowmeters are considered, which have more advantages than others. Ultrasonic flowmeters also have some problems, especially in installation, so this research aims to simulate the position of path configuration. The method refers to the weighting process of multi-path configuration and the simulation of track performance, which includes three-factor, hydrodynamic (H), orientation sensitivity (S) and orientation range (T). Each trajectory pattern is rotated 1ᴼ at each angle. In addition, there are also parameter functions that are used to image the profile. The test uses 7 path configurations, so an ideal form is obtained to be implemented. After multiplying weighting factors, the obtained value of hydrodynamic (H) for Area weighting method (1.002), the best value 1. Orientation sensitivity (S), with Area weighting method (0.019), the best result is 0. Meanwhile, with orientation range (T) 1%, with Area weighting method (163,2), the best value is 180.

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