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All Journal Jurnal Teknologi dan Manajemen Informatika TEKNOLOGI: Jurnal Ilmiah Sistem Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Kursor Jurnal Teknologi dan Sistem Komputer Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer INTEGER: Journal of Information Technology Teknika: Engineering and Sains Journal Knowledge Engineering and Data Science JICTE (Journal of Information and Computer Technology Education) SMARTICS Journal Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Konvergensi Jurnal Sisfokom (Sistem Informasi dan Komputer) INTECOMS: Journal of Information Technology and Computer Science Antivirus : Jurnal Ilmiah Teknik Informatika Journal of Information System,Graphics, Hospitality and Technology Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jurnal Teknologi Informasi dan Terapan (J-TIT) Jurnal Teknika Teknika Journal of Electrical Engineering and Computer (JEECOM) Best : Journal of Applied Electrical, Science and Technology Insyst : Journal of Intelligent System and Computation J-Intech (Journal of Information and Technology) Joutica : Journal of Informatic Unisla Jurnal Nasional Teknik Elektro dan Teknologi Informasi JOINCS (Journal of Informatics, Network, and Computer Science) Insand Comtech : Information Science and Computer Technology Journal Jurnal Indonesia Sosial Teknologi JEECS (Journal of Electrical Engineering and Computer Sciences) Eksplorasi Teknologi Enterprise & Sistem Informasi (EKSTENSI) EduTech Journal
Endang Setyati
Institut Sains Dan Teknologi Terpadu Surabaya
Aerospace Engineering 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 Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Physics Social Sciences Other

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Extraction of Eye and Mouth Features for Drowsiness Face Detection Using Neural Network Fitrianingsih, Elis; Setyati, Endang; Zaman, Luqman
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 3, No 2, May-2018
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (626.909 KB) | DOI: 10.22219/kinetik.v3i2.589

Abstract

Facial feature extraction is the process of searching for features of facial components such as eyes, nose, mouth and other parts of human facial features. Facial feature extraction is essential for initializing processing techniques such as face tracking, facial expression recognition or face shape recognition. Among all facial features, eye area detection is important because of the detection and localization of the eye. The location of all other facial features can be identified. This study describes automated algorithms for feature extraction of eyes and mouth. The data takes form of video, then converted into a sequence of images through frame extraction process. From the sequence of images, feature extraction is based on the morphology of the eyes and mouth using Neural Network Backpropagation method. After feature extraction of the eye and mouth is completed, the result of the feature extraction will later be used to detect a person’s drowsiness, being useful for other research.
Hand Gesture Recognition Sebagai Pengganti Mouse Komputer Menggunakan Kamera Yunita, Helda; Setyati, Endang
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol 3 No 2 (2019)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (985.475 KB) | DOI: 10.31961/eltikom.v3i2.114

Abstract

Akhir-akhir ini perkembangan teknologi semakin pesat, metode interaksi dan komunikasi antara pengguna dengan komputer adalah salah satu tuntutan perkembangan teknologi. Berbagai macam pembaharuan teknologi mengusahakan untuk meminimalisir berbagai macam perangkat menjadi satu agar lebih mudah digunakan. User lebih membutuhkan peralatan komunikasi yang bersifat alami karena tidak membutuhkan kontak langsung dengan peralatan input. Misalnya dengan gerakan dari tubuh manusia didepan kamera komputer sudah bisa menginterpretasikan. Untuk mengatasi masalah tersebut maka dilakukan suatu penelitian tentang deteksi isyarat tangan. Inputan berupa isyarat dan gerakan tangan didepan kamera dapat memberikan aksi pergerakan pada mouse yang diistilahkan dengan kamera mouse. Metode yang digunakan adalah convexhull algorithm. Melalui convexhull algorithm bisa didapatkan jumlah jari tangan yang kemudian dapat dijadikan acuan dalam pengerjaan aksi mouse. Sebenarnya sudah banyak penelitian tentang camera mouse, tetapi implementasinya masih banyak yang bergantung dengan peralatan tambahan. Penelitian ini mengembangkan penelitian yang sudah ada, yaitu hand gesture recognition dengan implemen-tasi pergerakan mouse dari video secara realtime. Dengan hand gesture recognition dan menggunakan metode convexhull algorithm pengenalan tangan akan lebih mudah hanya dengan menggunakan kamera, hanya dengan hitungan detik aksi mouse pada komputer dapat berjalan dengan baik yaitu dengan tingkat akurasi sebesar 68 % dari 75 kali percobaan
Klasifikasi Topeng Pandawa dengan SVM Sanjaya, Andi; Setyati, Endang; Budianto, Herman
INTEGER: Journal of Information Technology Vol 5, No 1: April 2020
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (236.222 KB) | DOI: 10.31284/j.integer.2020.v5i1.910

Abstract

Klasifikasi merupakan tahapan tingkat lanjut dari sebuah keilmuan computer vision. Karena tujuan dari sebuah aplikasi rekognisi yaitu mengenali. Cara mengenali yaitu dengan cara klasifikasi. Banyak metode klasifikasi yang ada, namun pada penelitian ini menggunakan Support Vector Machine (SVM). SVM dipilih karena bisa mengatasi data dengan dimensi yang sangat besar tanpa mereduksi data, bekerja dengan data linier atau nonlinier dan membuat sebuah hyperplane yang memisahkan data antar kelas. Pada penelitian ini menggunakan data patung pandawa dengan lima kelas. Lima kelas terdiri dari kelas yudhistira, bima, arjuna, nakula dan sadewa. Kernel yang digunakan pada penelitian ini menggunakan  Radial Basis Function (RBF). Hasil ujicoba pada penelitian mempunya rata-rata akurasi sebesar 0,848.
Desain dan implementasi wireless sensor network (WSN) menggunakan LoRa untuk pemantauan tingkat pencemaran udara di kota Surabaya Arafat, Yasir; Setyati, Endang
Teknologi: Jurnal Ilmiah Sistem Informasi 2020: Articles in press
Publisher : Universitas Pesantren Tinggi Darul 'Ulum (Unipdu) Jombang

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

Abstract

Pencemaran udara merupakan hal yang tidak dapat dihindarkan pada setiap daerah. Sumber pencemaran udara tersebut bermacam-macam, seperti gas kendaraan bermotor, limbah pabrik, dan sampah yang dibuang sembarangan. Penelitian ini mengusulkan pembuatan sebuah sistem pemantauan kualitas udara di kota Surabaya. Zat pencemar yang menjadi tolak ukur untuk menentukan tingkat pencemaran udara dalam penelitian ini adalah CO (Carbon monoxide), SO2 (Sulfur dioxide), O3 (Ozone), dan NO2 (Nitrogen dioxide). Sensor yang digunakan untuk mengetahui kadar zat pencemar tersebut adalah MQ-7 dan MQ-135. Penelitian ini memanfaatkan wireless sensor network (WSN) dan teknologi LoRa sebagai media pengiriman data. Empat titik pengujian dan dua papan ISPU (Indeks Standar Pencemar Udara) sebagai ground truth digunakan untuk mengetahui tingkat pencemaran udara di kota surabaya. Pengukuran dan perbandingan antara sensor dengan ground truth dilakukakan untuk mengetahui hasil penelitian ini. Hasil pemantauan tingkat pencemaran udara didapatkan dengan menggunakan sensor MQ-7 dan MQ-135 yang mampu membaca keadaan zat pencemar dengan tingkat error paling besar 5,77%. Sistem pengiriman data menggunakan teknologi LoRa pada jarak terjauh 2,97 km dapat mengirimkan data dengan baik dengan RSSI (Received Signal Strength Indication) -92 dBm pada ketinggian 12 mdpl dan frekuensi 433 Mhz. Data hasil pemantauan tersebut dapat dipantau melalui aplikasi ThingSpeak secara online. Everywhere, air pollution isn't avoidable. The source of pollution could be anything, such as gas emitted from vehicles, toxic waste, and garbages that are thrown not to their places. In this study, a system to monitor air quality will be built in Surabaya. The pollutants that will be the benchmark to measure the level of air pollution are CO (Carbon Dioxide), SO2 (Sulfur Dioxide), O3 (ozone), and NO2 (Nitrogen Dioxide). The sensor that will be used to detect the level of pollutants is called MQ-7 and MQ-135. This study takes Wireless Sensor Network (WSN) into use while LoRa technology is being used as a media to send data. To know the level of pollution in Surabaya, 4 test points are taken, and AQI (Air Pollution Index) are used as ground truth. After measuring and comparing the sensor and ground truth, the result that is taken using MQ-7 sensor and MQ-135 could read the status of pollutants with 5.77% as its highest sensor range. After that, the system that is sending the data using LoRa technology with 2.97 km as its highest distance could send the data well with RSSI -92dBm in 12m MSL height and 433 Mhz frequency. The result of this monitoring could be seen through thingspeak application online.
DROWSY DETECTION FROM VIDEO DRIVER FACE BASED ON EYE AND MOUTH FEATURES EXTRACTION USING THE CONVOLUTION NEURAL NETWORK METHOD Solikin, Akhmad; Setyati, Endang
BEST Vol 2 No 1 (2020): BEST
Publisher : Program Studi Teknik Elektro Universitas PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/best.vol2.no1.2584

Abstract

This research was conducted in an effort to minimize the occurrence of road traffic accidents. In this study detected the level of fatigue and sleepiness from the driver's face video based on the extraction of eye and mouth features using the CNN method. The dataset in this study is 300 data with 3 different classes namely drowsiness 100 data, sleepy 100 data and normal 100 data. The number of epochs used in research to achieve high accuracy is as much as 50. In the test results it is known that the validation of accuracy has increased in each of the input layer results.
Utilization Of Augmented Reality In Automotive Subjects For Basic Competencies Of Four-Wheeled Vehicle Brake Systems Farkhan, Muhammad; Setyati, Endang; Haryanti Chandra, Francisca
BEST Vol 3 No 2 (2021): BEST
Publisher : Program Studi Teknik Elektro Universitas PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/best.vol3.no2.4243

Abstract

In automotive learning, teachers generally use books and teaching aids as learning media. Automotive learning outcomes show the low value of learning outcomes. Thus a learning media is needed that can help improve learning outcomes. One way to overcome this problem is to use learning media that utilize augmented reality technology. In this study, a learning media using augmented reality technology based on android was developed to simulate the brake system on four-wheeled vehicles in 3 dimensions. The Augmented Reality work system used is marker based tracking, and uses 3D Max software and the Vuforia plug-in. In terms of pedagogy, this learning system uses the Modality Principle. Participants are class XI students of SMK YPM 4 Taman. This research uses experimental research. The students involved were 44 students divided into 2 groups, with each group consisting of 22 students. Both groups received a pre-test and a post-test. The experimental group was given treatment with Augmented Reality-based learning media, while the control group did not use conventional learning media. After making comparisons, the results show less than optimal due to the pandemic period. The results showed that the pre-test result between the control group and the experimental group was 49.32, and the post-test result for the control group was 62.73, while for the experimental group it was 73.18. So that from the difference in the difference in post-test scores between the experimental group and the control group shows that the treatment factor by providing Augmented Reality-based learning media in the experimental group has an influence. From observations and interviews, students were more active in learning activities and students were eager to take part in learning. This proves that students are interested in this media which can generate motivation to learn.
Desain dan implementasi Wireless Sensor Network menggunakan LoRa untuk pemantauan tingkat pencemaran udara di Kota Surabaya Arafat, Yasir; Setyati, Endang
TEKNOLOGI: Jurnal Ilmiah Sistem Informasi Vol 10, No 2 (2020): July
Publisher : Universitas Pesantren Tinggi Darul 'Ulum (Unipdu) Jombang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/teknologi.v10i2.2070

Abstract

Pencemaran udara merupakan hal yang tidak dapat dihindarkan pada setiap daerah. Sumber pencemaran udara tersebut bermacam-macam, seperti gas kendaraan bermotor, limbah pabrik, dan sampah yang dibuang sembarangan. Penelitian ini mengusulkan pembuatan sebuah sistem pemantauan kualitas udara di kota Surabaya. Zat pencemar yang menjadi tolak ukur untuk menentukan tingkat pencemaran udara dalam penelitian ini adalah CO (Carbon monoxide), SO2 (Sulfur dioxide), O3 (Ozone), dan NO2 (Nitrogen dioxide). Sensor yang digunakan untuk mengetahui kadar zat pencemar tersebut adalah MQ-7 dan MQ-135. Penelitian ini memanfaatkan wireless sensor network (WSN) dan teknologi LoRa sebagai media pengiriman data. Empat titik pengujian dan dua papan ISPU (Indeks Standar Pencemar Udara) sebagai ground truth digunakan untuk mengetahui tingkat pencemaran udara di kota surabaya. Pengukuran dan perbandingan antara sensor dengan ground truth dilakukakan untuk mengetahui hasil penelitian ini. Hasil pemantauan tingkat pencemaran udara didapatkan dengan menggunakan sensor MQ-7 dan MQ-135 yang mampu membaca keadaan zat pencemar dengan tingkat error paling besar 5,77%. Sistem pengiriman data menggunakan teknologi LoRa pada jarak terjauh 2,97 km dapat mengirimkan data dengan baik dengan RSSI (Received Signal Strength Indication) -92 dBm pada ketinggian 12 mdpl dan frekuensi 433 Mhz. Data hasil pemantauan tersebut dapat dipantau melalui aplikasi ThingSpeak secara online. Everywhere, air pollution isn't avoidable. The source of pollution could be anything, such as gas emitted from vehicles, toxic waste, and garbages that are thrown not to their places. In this study, a system to monitor air quality will be built in Surabaya. The pollutants that will be the benchmark to measure the level of air pollution are CO (Carbon Dioxide), SO2 (Sulfur Dioxide), O3 (ozone), and NO2 (Nitrogen Dioxide). The sensor that will be used to detect the level of pollutants is called MQ-7 and MQ-135. This study takes Wireless Sensor Network (WSN) into use while LoRa technology is being used as a media to send data. To know the level of pollution in Surabaya, 4 test points are taken, and AQI (Air Pollution Index) are used as ground truth. After measuring and comparing the sensor and ground truth, the result that is taken using MQ-7 sensor and MQ-135 could read the status of pollutants with 5.77% as its highest sensor range. After that, the system that is sending the data using LoRa technology with 2.97 km as its highest distance could send the data well with RSSI -92dBm in 12m MSL height and 433 Mhz frequency. The result of this monitoring could be seen through thingspeak application online.
HYBRID JOB RECOMMENDATION SYSTEM PADA PERGURUAN TINGGI Kartika, Bara Alpa Yoga; Setyati, Endang
KONVERGENSI Vol 17 No 2 (2021)
Publisher : Informatics, Universitas 17 Agustus 1945 Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30996/konv.v17i2.5463

Abstract

ABSTRACT Job vacancies are information that is needed by all job seekers, especially students and alumni of a college, many universities already have a career center system, but most of the systems are just information without any processing in it. In this paper, we will discuss how job recommendations are made and presented back to job seekers by combining the Cosine Similarity and Alternating Least Squares algorithms. Based on the experiments conducted, the average Precision value is 0.75. Keywords: Vacancies, Jobs, Hybrid Recommendation, Alternating Least Squares ABSTRAKLowongan pekerjaan merupakan suatu informasi yang sangat diperlukan oleh semua para pencari kerja terlebih lagi para mahasiswa maupun alumni suatu perguruan tinggi, banyak perguruan tinggi yang sudah mempunyai suatu sistem career center namun kebanyakan dari sistem hanya sebagai informasi saja tanpa ada suatu pemrosesan didalamnya. Dalam paper ini akan membahas tentang bagaimana rekomendasi pekerjaan dibuat dan ditampilkan kembali kepada para pencari kerja dengan menggabungkan algoritma Cosine Similarity dan Alternating Least Squares. Berdasarkan percobaan yang dilakukan dihasilkan rata – rata nilai Precesion sebesar 0.75 Kata Kunci: Lowongan, Pekerjaan, Hybrid Recommendation, Alternating Least Squares
Detection of Militia Object in Libya by Using YOLO Transfer Learning Yosi Kristian; Hatem Alsadeg Ali Salim; Endang Setyati
Jurnal Teknologi dan Manajemen Informatika Vol 6, No 1 (2020): Juni 2020
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v6i1.4025

Abstract

Humans can recognize and classify shapes, names, and provide responses to object that are received by visually quickly and accurately. More importantly, it is expected that the system created is able to help provide response in all tasks and time, for example when driving, walking in the crowd even when patrolling as a member of the military on dangerous terrain.This has become a problem in the system used on the battlefield. In the proposed system, the object detection model must be able to sort out the objects of armed humans (militia) with unarmed human objects. To overcome the problem the author uses the YOLO transfer learning algorithm which currently has the third version. It is stated that YOLOv3 has very extreme speed and accuracy. In mean Average Precision (mAP) obtained by 0.5 IOU, YOLOv3 is equivalent to 4x faster than Focal Loss. Moreover, YOLOv3 also offers optimal speed and accuracy simply by changing the size of the model, without the need for retraining. DOI: https://doi.org/10.26905/jtmi.v6i1.4025
Adaptive Background Extraction for Video Based Traffic Counter Application Using Gaussian Mixture Models Algorithm Raymond Sutjiadi; Endang Setyati; Resmana Lim
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 13, No 3: September 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v13i3.1772

Abstract

The big cities in the world always face the traffic jam. This problem is caused by the increasing number of vehicle from time to time and the increase of vehicle is not anticipated with the development of new road section that is adequate. One important aspect in the traffic management concept is the need of traffic density data of every road section. Therefore, the purpose of this paper is to analyze the possibility of optimization on the use of video file recorded from CCTV camera for the visual observation and the tool for counting traffic density. The used method in this paper is adaptive background extraction with Gaussian Mixture Models algorithm. It is expected to be the alternative solution to get the data of traffic density with a quite adequate accuracy as one of aspects for decision making process in the traffic engineering
Co-Authors Abdur Rouf Achmad Firman Choiri Agung Adi Saptomo Agung Dewa Bagus Soetiono Ajeng Restu Kusumastuti Akhmad Solikin Andi Sanjaya Andi Sanjaya Andriyanto, Pyepit Rinekso Anggay Luri Pramana Arif Priyambodo Azis Suroni Bambang Widodo Devi Dwi Purwanto Dicka Y Kardono Edwin Pramana Eko Mulyanto Yuniarno Elis Fitrianingsih Elkana Lewi Santoso Esther Irawati Setiawan Fachrul Kurniawan Farkhan, Muhammad Febriantoro, Erfan Fery Satria Kristianto Fitrianingsih, Elis Francisca H Chandra Francisca Haryanti Chandra Gunawan Gunawan Gunawan Hans Keven Budi Prakoso Hatem Alsadeg Ali Salim Hendrawan Armanto Herman Budianto Honoris Setiahadi Ine Juniwati Joan Santoso Kartika, Bara Alpa Yoga Kholilul Rohman Kurniawan Lilis Setyaningsih Luhfita Tirta Lukman Zaman Luqman Zaman M. Najamudin Ridha Masrur Anwar Mauridhi Hery Purnomo Maysas Yafi' Urrochman Miftah Farid Mochamad Hariadi Muhammad Farkhan Muhammad Turmudzi Nanang Wahyudi Novi Duwi Setyorini Peter Winardi Pranama, Edwin Rafliana Natalia da Silva Raymond Sugiarto Raymond Sutjiadi Reddy Alexandro Harianto Resmana Lim Rizal Budi Rusina Widha Febriana Salim, Shierly Kartika San, Joan Soetiono, Agung Dewa Bagus Subroto Prasetya Hudiono Suharyono Az Suhatati Tjandra Supandik, Ujang Joko Surya Sumpeno Suyuti, Mahmud Tjwanda Putera Gunawan Tri Septianto Tuesday saka gustaf Udkhiati Mawaddah Uliontang Uliontang Yasir Arafat, Yasir Yosi Kristian Yuliana Melita Pranoto Yunita, Helda Zaman, Luqman