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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics International Journal of Advances in Intelligent Informatics Jurnal Inspiration Panrita Abdi - Jurnal Pengabdian pada Masyarakat JOIV : International Journal on Informatics Visualization Journal TEPAT: Teknologi Terapan untuk Pengabdian Masyarakat EPI International Journal of Engineering Jurnal Penelitian Enjiniring Fakultas Teknik Unhas Jurnal Teknologi Elekterika Indonesian Journal of Electrical Engineering and Computer Science Community Development Journal: Jurnal Pengabdian Masyarakat JURNAL SIPISSANGNGI: Jurnal Pengabdian Kepada Masyarakat Jurnal INFOTEL
Indrabayu Indrabayu
Departemen Teknik Informatika, Fakultas Teknik, Universitas Hasanuddin
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Public Health Other

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Prediksi Nilai Tukar Valuta Asing Menggunakan Metode Genetic Algorithm-Neural Network (Euro Terhadap US Dollar) Sespajayadi, Ary; Rushadah, Nur Indriani; Indrabayu, Indrabayu; Warni, Elly
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol 3, No 1 (2013): Jurnal Inspiration Volume 3 Issue 1
Publisher : STMIK AKBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35585/inspir.v3i1.28

Abstract

Memiliki penghasilan tinggi secara continue dan aman dalam trading Forex secara real adalah impian bagi para trader, hampir kebanyakan para trader pemula , terutama trader yang baru terjun atau baru belajar di dunia Forex berusaha semaksimal mungkin untuk menemukan sistem yang holygrail secara teknik baik secara fundamental maupun teknikal Penelitian ini bertujuan untuk membuat sistem prediksi harga nilai tukar mata uang Euro terhadap US Dollar dengan metode Genetic Algorithm-Neural Network. Metode Genetic Algorithm digunakan untuk mendapatkan nilai Feed Forward Neural Network terbaik dari output yang dihasilkan. Selanjutnya dilakukan pelatihan terhadap Feed Forward Neural Network terbaik yang didapatkan dengan metode Neural Network untuk membentuk sebuah net yang akan digunakan untuk memprediksi. Data pergerakan nilai tukar Euro terhadap US Dollar dapat diperoleh dari software Metatrader yang berupa data history forex timeframe jam (H1). Dimana hasil uji prediksi adalah nilai open, high, low dan close yang mengalami perubahan setiap jam. Validasi hasil uji prediksi harga EUR/USD pada nilai harga Open, High, Low dan Close dengan metode Genetic Algorithm-Neural Network terhadap data real history time-frame H1 keempat variabel dari Metarader memiliki nilai RMSE dan tingkat akurasi sebagai berikut: Open memiliki nilai RMSE sebesar 0,0071 dengan tingkat akurasi sebesar 95,00%, High memiliki nilai RMSE sebesar 0,0261 dengan tingkat akurasi 59,17%, Low memiliki nilai RMSE sebesar 0,0328 dengan tingkat akurasi sebesar 50,00% dan Close meiliki nilai RMSE sebesar 0,0119 dengan tingkat akurasi sebesar 83,33%.
A real-time data association of internet of things based for expert weather station system Indrabayu Indrabayu; Intan Sari Areni; Anugrayani Bustamin; Rizka Irianty
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i2.pp432-439

Abstract

The wind carries moisture into an atmosphere and hot or cold air into a climate, affecting weather patterns. Knowing where the wind is coming from gives essential insight into what kind of temperatures are to be expected. However, the wind is affected by spatial and temporal variabilities, thus making it difficult to predict. This study focuses on finding data associations from the weather station installed at Hasanuddin University Campus based on internet of things (IoT) using Raspberry Pi as a gateway that associated all the meteorological data from sensors. The generation of association rules compares the Apriori and FP-growth algorithms to determine relations among itemsets. The results show that high humidity and warm temperature tend to associate with a westerly wind and occur at night. In contrast, conditions with less humid and moderate temperatures tend to have southerly and southeasterly wind.
Support Vector Machine Method to Reduce the Execution Time of Vehicle Plate Recognition System Muhammad Ismail; Indrabayu Indrabayu; Intan Sari Areni
EPI International Journal of Engineering Vol 1 No 1 (2018): Volume 1 Number 1, February 2018
Publisher : Center of Techonolgy (COT), Engineering Faculty, Hasanuddin University

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

Abstract

This research aims to create a vehicle plate detection and recognition system with Cascade Classifier, Support Vector Machine (SVM) and Optical Character Recognition (OCR). Cascade Classifier with Local Binary Patterns (LBP)descriptor is used todetectthe carlicence plate (Coarse Location). SVM is used to reduce plate candidate detection error andthe execution time. Optical Character Recognition (OCR) is used to recognize characters in plates. The system test is performed using 19 video data of moving vehicles at night and rain conditions. Each video has a duration of 30 seconds and contains 4-10 cars per video. The testing results reduce the execution time of vehicle plate recognition systemreached60% with the average accuracy of plate recognition is 61.94%.
Pengaruh Image Engagement pada Aplikasi Parasit Malaria Muhammad Irsan Sabir; Muhammad Niswar; Indrabayu Indrabayu
Jurnal Penelitian Enjiniring Vol 22 No 1 (2018)
Publisher : Center of Techonolgy (COT), Fakultas Teknik, Universitas Hasanuddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (250.929 KB) | DOI: 10.25042/jpe.052018.06

Abstract

The mosquito's parasite is a group of single-celled microorganisms in the plasmodium type that can cause malaria by attacking human blood cells. In this study, a parasitic detection application of Plasmodium Falciparum type at thropozoite, scizont and gametocyte stage was designed using Android Studio 2.2.2 and OpenCV 2.4.9 library. Image detection process begins with preprocessing, then feature extraction and classification phase using Haar Cascade Classifier, then the last stage 3 types of boost compared, namely Gentle Adaboost, Discrete Adaboost, and Real Adaboost. Image Enhancement is one of the preliminary processes in preprocessing that aims to clarify certain features or features of the image to be more easily analyzed carefully in the feature selection process. The results of this study prove that image enhancement can be used to improve image quality so that the information available on the image can be seen more clearly.
Optimasi Seleksi Fitur dengan Teknik Reduksi Dimensi pada Klasifikasi Abstrak Jurnal Syukriyanto Latif; Indrabayu Indrabayu; Intan Sari Areni
Jurnal Penelitian Enjiniring Vol 22 No 1 (2018)
Publisher : Center of Techonolgy (COT), Fakultas Teknik, Universitas Hasanuddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (291.625 KB) | DOI: 10.25042/jpe.052018.08

Abstract

The purpose of this research is to know dimension reduction parameter value at feature selection so as to improve accuracy and reduce computation time. This system uses text mining technology that extracts text data to find information from a set of documents. Word weighting and Term Reduction Technique The term Frequency Thresholding is used in the feature selection process, while in the classification process using the Naive Bayes algorithm. the abstract of the journal is categorized into 3 namely Data Mining (DM), Intelligent Transport System (ITS) and Multimedia (MM). The total number of test data and training data is 150 data. The best classification results are obtained when the dimension reduction parameter value is 30%. At that condition obtained an average accuracy of 87.33% with a computation time of 4 minutes 12 seconds.
Optimasi Perhitungan Jarak antara Kendaraan Nurul Fathanah Mustamin; Indrabayu Indrabayu; Intan Sari Areni
Jurnal Penelitian Enjiniring Vol 22 No 2 (2018)
Publisher : Center of Techonolgy (COT), Fakultas Teknik, Universitas Hasanuddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1168.406 KB) | DOI: 10.25042/jpe.112018.02

Abstract

Penelitian ini bertujuan untuk merancang sebuah sistem estimasi jarak relatif antara kendaraan sebagai penelitian awal untuk konsep pengemudi tanpa awak agar berkendara dengan aman dan terhindar dari tabrakan. Sistem deteksi ini terdiri atas tahap deteksi dengan metode Histogram of Oriented Gradients (HOG) dan tahap estimasi jarak antara kendaraan dengan metode Width Based. Kendaraan yang digunakan pada penelitian ini adalah jenis city car dan van. Hasil deteksi kendaraan untuk jenis city car diperoleh persentase rata-rata TPR (True Positive Rate) sebesar 92% sedangkan mobil jenis van mendapatkan persentase rata-rata TPR sebesar 64% untuk 5 video yang di uji. Untuk hasil estimasi jarak relatif antara kendaraan diperoleh untuk jenis mobil city car menunjukkan hasil yang lebih baik dengan nilai MSE 0,29 dan untuk mobil jenis van dengan nilai MSE 0,55.
Analisis Performansi Protokol Routing Proaktif pada Jaringan Mobile Adhoc Rohmah Nur Hidayah; Indrabayu Indrabayu; Intan Sari Areni
Jurnal Penelitian Enjiniring Vol 22 No 2 (2018)
Publisher : Center of Techonolgy (COT), Fakultas Teknik, Universitas Hasanuddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (867.626 KB) | DOI: 10.25042/jpe.112018.04

Abstract

Intelligent Transportation Systems (ITS) menawarkan paradigma pemodelan baru yang mendukung komunikasi antar kendaraan secara real time menggunakan routing protocol yang disebut Vehicular Ad Hoc Network (VANET). Pada dasarnya kinerja routing protocol dipengaruhi oleh arus dan aturan lalu lintas yang bersifat dinamis sehingga perubahan tersebut akan menyebabkan perubahan pada kinerja routing protocol juga. Untuk itu, penelitian ini mengusulkan rancangan mobilitas realistis berdasarkan data makroskopis dan mikroskopis jalan perkotaan. Rancangan mobilitas dibagi menjadi 2 skenario berdasarkan kepadatan kendaraan, yaitu 125 dan 200 node. Penelitian ini bersifat simulasi dan dibagi menjadi 2 tahap. Tahap pertama yaitu simulasi mobilitas yang menunjukkan pergerakan kendaraan serta aturan lalu lintas yang disesuaikan dengan kondisi realistis. Tahap kedua adalah simulasi jaringan yang bertujuan untuk mengevaluasi kinerja routing protocol DSDV dan OLSR terhadap rancangan model mobilitas. Untuk menguji kinerja kedua routing protocol, maka digunakan 3 metrik pengujian yaitu Packet Delivery Ratio (PDR), Overhead Ratio (OR) dan End to End Delay (E2ED). Hasil simulasi menunjukkan OLSR unggul pada metrik PDR dan OR, yaitu masing-masing 88.62% dan 57.11%. Sedangkan E2ED terbaik ditunjukkan oleh DSDV dengan nilai 0.523 detik. Kinerja terbaik kedua routing protocol ditunjukkan pada skenario 125 node. Hal ini menunjukkan kedua routing protocol belum mampu mengatasi kondisi lalu lintas perkotaan yang sangat padat.
Sistem Deteksi Lubang pada Pedesterian dengan Teknik Pengolahan Citra Intan Sari Areni; Indrabayu Amirullah; Ingrid Nurtanio; Anugrayani Bustamin; Ahmad Rifaldi
Jurnal Penelitian Enjiniring Vol 23 No 2 (2019)
Publisher : Center of Techonolgy (COT), Fakultas Teknik, Universitas Hasanuddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (424.283 KB) | DOI: 10.25042/jpe.112019.04

Abstract

Pothole Detection System on Pedesterian using Image Processing Techniques. The pedestrian areas in Indonesia are still far from optimal in facilitating the users or the pedestrians. Potholed pedestrian areas are found in many parts of the street. This issue can harm pedestrians, especially blind people. For this reason, research has been carried out to create a system that can detect and estimate hole distances by processing images using mono cameras that can help blind people. The methods used to detect holes are the Threshold + Blob Analysis method and the HSV method. The obtained results indicate the level of accuracy of hole detection using the Threshold + Blob Analysis method is better than the HSV method. The average accuracy level of Threshold + Blob Analysis is 88.91%, while for the HSV method is 86.82%.
Klasifikasi Kematangan Stroberi Berbasis Segmentasi Warna dengan Metode HSV Intan Sari Areni; Indrabayu Amirullah; Nurhikma Arifin
Jurnal Penelitian Enjiniring Vol 23 No 2 (2019)
Publisher : Center of Techonolgy (COT), Fakultas Teknik, Universitas Hasanuddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (309.517 KB) | DOI: 10.25042/jpe.112019.03

Abstract

Classification of Strawberry Maturity Based on Color Segmentation using HSV Method. Manual fruit maturity classification has many limitations because it is influenced by human subjectivity. Hence, the application of digital image processing and artificial intelligence becomes more effective and efficient. This study aims to create a classification system that automatically divides strawberry maturity into three categories, namely not ripe, half-ripe, and ripe. The process of identifying the level of fruit maturity is based on the color characteristics Red, Green, Blue (RGB) value of the image. The method used for color segmentation is Hue, Saturation, Value (HSV) and for the classification of strawberry maturity using the Multi-Class Support Vector Machine (SVM) algorithm with a Radial Basic Function (RBF) kernel. Strawberry image data was retrieved using the Logitech C920 camera. The dataset consisted of 158 images of strawberries. The results showed that the classification of strawberry maturity using the multi-class SVM algorithm with kernel parameters RBF cost (C) = 10 and gamma (γ) = 10-3 produced the highest accuracy of 97%.
Blob adaptation through frames analysis for dynamic fire detection Indrabayu Indrabayu; Rahmat Hardian Putra; Ingrid Nurtanio; Intan Sari Areni; Anugrayani Bustamin
Bulletin of Electrical Engineering and Informatics Vol 9, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (642.639 KB) | DOI: 10.11591/eei.v9i5.2622

Abstract

This study was aiming at helping visually impaired people to detect and estimate the fire distance. Blind people had difficulty knowing the existence of fire at a safe distance; hence the possibility of burning could occur. The color models and blob analysis methods were used to detect the presence of fire in the blind path. Before the fire detection stage, the cascade of the HSV and RGB color models was applied to segment the reddish fire color. The size and shape of a dynamic fire were the parameters used in this paper to distinguish fire from non-fire objects. Changes in the area of the fire object obtained at the Blob analysis stage per 10 frames were the main contributions and novelty in this paper. After the fire is detected, the calculation of the fire distance to a blind person was completed using a pinhole model. This research used 35 data videos with a resolution of 480x640 pixels. The results showed that the fire detection system and the distance estimation achieved an accuracy of 88.86% and the MSE of 0.0358, respectively.
Co-Authors A. Ais Prayogi Alimuddin A.Ais Prayogi Abdul Razak Munir Adnan Adnan Ady Wahyudi Paundu Ahmad Rifaldi Amil A. Ilham Amil Ahmad Ilham Andani Achmad Andani Achmad Andini D. Achmad Andri Anto Aman Andri Anto Aman, Andri Anto Anugrayani Bustamin Anugrayani Bustamin Anugrayani Bustamin Aqfir Areni, Intan Sari Arifin, Nurhikma Aulia Darnilasari Bake, Sabda Ansari Basri Basri Bustamin, Anugrayani Christoforus Yohanes Dewi, Andi Ratna Sari Edi Yanto Elly Warni Elly Warni Elyas Palantei Fakhriyah, Sitti Fakhriyah Ibrahim, Rafiqa Nurcahyani Ida Ayu Putu Sri Widnyani Ifwan, Ichsanul Al Ingrid Nurtanio Intan Sari Areni Intan Sari Areni Intan Sari Areni Intan Sari Areni Iqra Aswad Marindah, Tyanita Puti Muh Anshar Muh Niswar Muh Niswar, Muh Muh. Alief Fahdal Imran Oemar Muhammad Abdillah Rahmat, Muhammad Abdillah Muhammad Irsan Sabir Muhammad Ismail Muhammad Niswar Mukarramah Yusuf Nurul Fathanah Mustamin Rahayu, Mesra Rahmat Hardian Putra Rhiza S. Sadjad Rieka Zalzabillah Putri Rizka Irianty Rohmah Nur Hidayah Rushadah, Nur Indriani Salam, Andi Ejah Umraeni Sespajayadi, Ary Sidehabi, Sitti Wetenriajeng Siska Anraeni Syafruddin Syarif Syafruddin Syarif Syahputra, Rendy Aziz Syukriyanto Latif Usman Umar Warni, Elly Yohannes, Christoforus Zaenab Muslimin Zaenab Muslimin Zahir Zainuddin Zulfajri Basri Hasanuddin Zulkifli Tahir