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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal SPEKTRUM SINTECH (Science and Information Technology) Journal Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Journal of Computer Science and Informatics Engineering (J-Cosine) Journal of Electrical, Electronics and Informatics SPEKTA (Jurnal Pengabdian Kepada Masyarakat : Teknologi dan Aplikasi) Jurnal Ilmiah Wahana Pendidikan Journal of Law and Social Politics Jurnal SPEKTRUM
Duman Care Khrisne
Program Studi Teknik Elektro, Fakultas Teknik, Universitas Udayana
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Social Sciences Other

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RANCANG BANGUN ALAT MONITORING TANAMAN HIDROPONIK PAKCOY MEMANFAATKAN MIKROKONTROLER DAN TEKNIK COMPUTER VISION I Gusti Made Andi Dipayana; Duman Care Khrisne; Widyadi Setiawan
Jurnal SPEKTRUM Vol 9 No 1 (2022): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (331.002 KB) | DOI: 10.24843/SPEKTRUM.2022.v09.i01.p3

Abstract

Technology in agriculture is growing, one of them is hydroponic techniques because it uses anInternet of Things (IoT) based system. One of the plants used in hydroponic techniques is thepakcoy vegetable plant. Pakcoy is one of the vegetables that has the widest distribution in Asia.In addition, the characteristics of pakcoy vegetables are almost the same as mustard greens.Pakcoy vegetables are also easy to cultivate because they only require a small amount of landand a short harvest period. This system is built using a microcontroller and computer visiontechniques as a control center and uses a Raspberry Pi 4 type B mini PC as a visual notificationand is equipped with a dc motor gearbox, L298N motor driver and webcam camera. Thissystem works automatically to control which plants are healthy and which plants are sick. Thisstudy aims to detect diseased plants and healthy plants on pakcoy plants with a hydroponicpakcoy plant monitoring tool that uses a microcontroller and computer vision techniques. Thistool works by taking pictures directly through a webcam camera, then processing them with atrained model. The output of this tool displays the probability value of pakcoy plants showinghealthy plants and sick plants. From the results of testing the validation data using 60 validationdata, based on the accuracy of the detection tool healthy and sick plants were able to correctlyidentify 38 validation data and 22 data were not recognized properly, so the accuracy of thevalue was 63%. and produces an f1-score of 0,87
Rancang Bangun Aplikasi Augmented Reality Sebagai Media Promosi Model Tatanan Rambut Pada Barbershop Berbasis Android Putu Adistyanda Timoti Raja Karda; I Made Arsa Suyadnya; Duman Care Khrisne
SINTECH (Science and Information Technology) Journal Vol. 1 No. 1 (2018): SINTECH Journal Edition April 2018
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v1i1.226

Abstract

The development of barbershop makes business competition becomes increasingly tight. Currently, information and communication technology is very important in the field of barbershop marketing. But this technology only shows details of the existence of barbershop. In addition, the catalog of hairstyles that are provided only in the form of 2-dimensional images. Therefore, more advanced technology is needed to promote the model of hairstyle available in barbershop. One of the technology applied in smartphone applications is Augmented Reality on the Android operating system. In this research will be developed an Augmented Reality based promotion media to promote hair model model with 3 dimensional object visualization using marker based tracking method. Development of this application starts from the stage of concept creation, application design, 3-dimensional object creation, application assembly, application testing, until the application distribution stage. This application was created using C # programming language, Vuforia Qualcomm, virtual and Unity Autodeks Maya software. The application that has been produced is tested by 2 methods that is by black-box testing and by usability scale system test, on the test of black -box AugmentedReality application of functional barbershop that exist in the application has been successfully executed according to their respective function. Based on survey results on Usabilty ScaleSystem(SUS) test on Augmented Reality Barbershop application, 20 respondents gave average score of 73.35 with Grade Scale C.
RANCANG BANGUN SISTEM INFORMASI GEOGRAFIS PENGEPUL KOPI BERBASIS ANDROID I Dewa Gede Shunu Kendrawan; Duman Care Khrisne; Gede Sukadarmika
SINTECH (Science and Information Technology) Journal Vol. 1 No. 2 (2018): SINTECH Journal Edition Okctober 2018
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v1i2.233

Abstract

The low income of coffe farmers in Indonesia is caused several factor, large production cost, non standart prices and high transport costs. In this paper we try to overcome this problem by establishing a geographic information system for coffe collectors, that will help farmers find an appropriate buyer with minimal shipping costs to maximized their profits. This research has been successfully implemented using Google Maps API for mapping the location and built as an Android based mobile devices application. Application on the side of the collectors can input different types of coffe prices to be purchased. While the system is on the side of farmers can search for coffe collectors location. The test results using the system usability scale (SUS), the respondents gave a score on the farmer’s average of 74.7 and the side of the collector of 71.1 which means it has value adjective rating = excellent, grade scale = c and acceptability ranges = acceptable.
APLIKASI ASISTEN UNTUK LANSIA DENGAN MEMANFAATKAN SMARTPHONE BERBASIS ANDROID Gede Edy Purna Sastriya; Duman Care Khrisne; Made Surdarma
SINTECH (Science and Information Technology) Journal Vol. 2 No. 2 (2019): SINTECH Journal Edition October 2019
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v2i2.315

Abstract

This study aims to design and build an android based elderly assistant application using Android Studio Software to help the elderly in performing its activities. There are two features in this elderly assistant application that are Exercise feature and Map Feature. Exercise feature aims to assist elderly in exercising by utilizing accelerometer and gyroscope sensors to read and calculate exercise movement performed by elderly and the Map feature aims to track the location where the elderly are snd also receive the notification when the elderly out of radius. From the results of trials of elderly assistant applications, accelerometer and gyroscope sensors on exercise features have been able to calculate and read the exercise movement that performed by the elderly and the map feature have been able to track the elderly location using GPS on Smartphone.
ASALTAG : Automatic Image Annotation Through Salient Object Detection and Improved k-Nearest Neighbor Feature Matching Theresia Hendrawati; Duman Care Khrisne
Journal of Electrical, Electronics and Informatics Vol 2 No 1 (2018): JEEI (February 2018)
Publisher : Institute for Research and Community Services Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JEEI.2018.v02.i01.p02

Abstract

Image databases are becoming very large nowadays, and there is an increasing need for automatic image annotation, for assiting on finding the desired specific image. In this paper, we present a new approach of automatic image annotation using salient object detection and improved k-Nearest Neigbor classifier named ASALTAG. ASALTAG is consist of three major part, the segmentation using Minimum Barirer Salienct Region Segmentation, feature extraction using Block Truncation Algorithm, Gray Level Co-occurrence Matrix and Hu’ Moments, the last part is classification using improved k-Nearest Neigbor. As the result we get maximum accuracy of 79.56% with k=5, better than earlier research. It is because the saliency object detection we do before the feature extraction proccess give us more focused object in image to annotate. Normalization of the feature vector and the distance measure that we use in ASALTAG also improve the kNN classifier accuracy for labeling image.
Indonesian Alphabet Speech Recognition for Early Literacy using Convolutional Neural Network Approach Duman Care Khrisne; Theresia Hendrawati
Journal of Electrical, Electronics and Informatics Vol 4 No 1 (2020): JEEI (February 2020)
Publisher : Institute for Research and Community Services Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JEEI.2020.v04.i01.p06

Abstract

Games are considered capable of being used as a learning medium that can help teachers to teach children how to pronounce the Indonesian alphabet in early literacy, we try to build one aspect of the game in this study. The approach we use is a speech recognition approach that uses the convolutional neural network method. The results of this study indicate that CNN can recognize speech, with input data is in the form of sound. We use the MFCC feature vector sound feature to make a 3-dimensional matrix of input sound into CNN input. We also use the Sequential CNN architecture made from a simple 10 layer neural network, which produces a model with a small size, approximately only about 6 MB, with high accuracy (84%) and an F-Measure of 0.91.
Geographic Information System of Potential Tsunami Impact Areas and Safe Gathering Places for Coastal Tourism Area in Badung Regency, Bali Province I Made Arsa Suyadnya; Duman Care Khrisne
Journal of Electrical, Electronics and Informatics Vol 1 No 2 (2017): JEEI (September 2017)
Publisher : Institute for Research and Community Services Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JEEI.2017.v01.i02.p07

Abstract

The Southern part of Bali especially Badung regency, in addition to having natural beauty and popular tourist attraction, it has a high potential for disaster. The fact is the coastline of Bali in the south is prone to tsunami because Bali is located close to the colliding zone between the Indo-Australian plate and the Eurasia plate, which presents the main source of the local tsunami that could hit the island of Bali. This research undertakes the design and development of a Geographic Information System (GIS) that can provide information and socialization of potential tsunami impact areas and safe gathering places for coastal tourism area in Badung regency. This application is built web-based by using Google Maps API v3. In this Geographic Information System, users can identify potential tsunami impact areas, obtain information on evacuation methods in the event of a tsunami disaster and can find the nearest safe gathering places to do an evacuation. By utilizing geolocation and direction services from Google Maps API v3, simulation of the nearest evacuation route has been successfully built. Evacuation is done by considering two possible evacuation sites. The first possibility is to evacuate to the nearest vertical high building, and the second evacuation site is away from the danger zone (red zone) and towards the safe zone (yellow zone or outside the yellow zone).
Android Based Application for Rhizome Medicinal Plant Recognition Using SqueezeNet Krisna Hany Indrani; Duman Care Khrisne; I Made Arsa Suyadnya
Journal of Electrical, Electronics and Informatics Vol 4 No 1 (2020): JEEI (February 2020)
Publisher : Institute for Research and Community Services Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JEEI.2020.v04.i01.p02

Abstract

Rhizome is modification of stem that grows below the surface of the soil and produce new bud and roots from its segments. Besides being used as spices, rhizome also used by people as ingredients of traditional medicine to treat various diseases. This proves that rhizome has many benefits. However, the ability to recognize types of rhizome can only be done by certain people because rhizome has variety of types, aromas, and different colors. This study was designed to build an Android based application to recognize the types of rhizome, so that people can recognize types of rhizome without having special knowledge. The application was built using Convolutional Neural Network (CNN) methods with SqueezeNet architecture model. This study used 9 class of rhizome with Zingiberaceae Family, namely Bangle, Jahe, Kunyit Kuning, Kencur, Lengkuas, Temu Kunci, Temu Ireng, Temu Mangga, and Temulawak. Testing is carried out to know the performance of application such as accuracy level of application in recognize types of rhizome. Based on the results of testing with 54 rhizomes sample images, the application is capable of recognizing rhizomes types by obtaining a top-1 accuracy value of 41% and top-5 accuracy value of 81%.
Detecting the Ripeness of Harvest-Ready Dragon Fruit using Smaller VGGNet-Like Network I Made Wismadi; Duman Care Khrisne; I Made Arsa Suyadnya
Journal of Electrical, Electronics and Informatics Vol 3 No 2 (2019): JEEI (August 2019)
Publisher : Institute for Research and Community Services Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JEEI.2019.v03.i02.p01

Abstract

This study has a purpose to develop an application to detect the ripeness of the dragon fruit with the deep learning approach using the Smaller VGGNet-like Network method. In this study, the dragon fruit are classified into two classes: ripe or ready for harvest and still raw, by using the Convolutional Neural Network (CNN). The training process utilize the hard packages in python with the backend tensorflow. The model in this research is tested using the confusion matrix and ROC method with the condition that 100 new data are tested. Based on the test conducted, the level of accuracy in classifying the ripeness of the dragon fruit is 91%, and the test using 20 epoch, 50 epoch, 100 epoch, and 500 epoch produced an AUROC value of 0,95.
Automatic Cigarette Object Concealment in Video using R-CNN Kadek Utari Widiarsini; Duman Care Khrisne; I Made Arsa Suyadnya
Journal of Electrical, Electronics and Informatics Vol 5 No 1 (2021): JEEI (February 2021)
Publisher : Institute for Research and Community Services Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JEEI.2021.v05.i01.p04

Abstract

Cigarettes are packaged processed tobacco products, produced from the Nicotiana Tabacum, Nicotiana Rustica plants and other species or synthetics that contain nicotine with or without additives. Smoking is known to the public as one of the causes of death in the world that is quite large such as asthma, lung infections, oral cancer, throat cancer, lung cancer, heart attacks, strokes, dementia, erectile dysfunction (impotence), and so on. This research aims to build an application that can recognize cigarettes automatically and conceal pictures so that people especially minors are not affected by cigarettes. The application is built using the Region-based Convolutional Neural Network (R-CNN) method. The study uses images that have cigarette objects in them. The test is carried out to find out the application performance such as the level of application accuracy in recognizing cigarette objects. Based on the test results with a sample of 126 cigarette images, the application built is able to recognize cigarette objects by obtaining an accuracy value of 63%.
Co-Authors A.A Ngurah Amrita ADITYA PRATAMA Agma Tinoe Mauludy Agus Wisnu Kusuma Nata Ahmad Sulton Anak Agung Dewi Sintyarianti Ardy Wijaya Arya Mertasana , Putu Arya Ramadhan, Fauzul Boy Aribana Depari Budi Dharma Prabhawa, I Dewa Gede Cokorda Gde Wahyu Pramana Damayanti, Dewi Ayu Sulistyo Darma Putra Dewa Made Wiharta Dwika Prihambodo, Prakoso Fajar Purnama Faridzky, Fadel Ferry Angga Irawan Gede Edy Purna Sastriya Gede Sukadarmika Gusman Saleh, Arya Hartawan, I Gusti Agung Komang Dlafari Djuni Hendrawati, Theresia I Dewa Gede Shunu Kendrawan I G. A. K. Diafari Djuni Hartawan I Gede Agus Satya Dharma I Gusti Made Andi Dipayana I Kadek Agung Bagus Satria Bumi Kelana I Kadek Arya Wiratama I Kadek Yuda Setiadi I Ketut Putra Swastika I Ketut Wijaya I Made Arsa Suyadnya I Made Cakra Pustaka1 I Made Rian Yuliawan I MADE SUDARMA I Made Sukarsa I Made Wismadi I Made Yudi Adnyana Putra I Nyoman Sumitra Tanaya I Putu Gede Mahendra Sanjaya I Putu Prasna Mahardika I Wayan Adi Setyadi I Wayan Shandyasa Ida Ayu Dwi Giriantari Ida Bagus A. Swamardika Jaelani, Maulana Jauzaa Maylia Suhendro Kadek Utari Widiarsini Karda, Putu Adistyanda Timoti Raja Kendrawan, I Dewa Gede Shunu Komang Oka Saputra Krisna Hany Indrani Lie Jasa Made Ngurah Satya Wibawa Putra Made Sudarma Made Sudarma Made Surdarma Made Surdarma Mkwawa, Is-haka Ni Made Ary Esta Dewi Wirastuti Nunut Asihanna, Ester Nur Adl, Waliyin Nyoman Putra Sastra Purna Sastriya, Gede Edy Putra Dharma, Wisnu Wardhana Putra Sentana, Kadek Wibawa Putra, I Made Yudi Adnyana Putri Sintya Dewi Putu Adistyanda Timoti Raja Karda Putu Agus Indra Purnama Putu Arya Mertasana Putu Aryasuta Wicaksana Putu Pande Deva Ryana Putra Risqa Purma Pratama Salsabila, Unik Hanifah Sebayang, Deo Armanta Suartama, Putu Dandy Surya Puja Anggara Tjok Gede Indra Partha Widyadi Setiawan Wijaya Kusuma Yasa, Kadek Yogi Prawira Putra