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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Algoritma Jurnal Teknologi Informasi dan Ilmu Komputer Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) Edu Komputika Journal Sinkron : Jurnal dan Penelitian Teknik Informatika SISFOTENIKA Seminar Nasional Teknologi Informasi Komunikasi dan Industri Jurnal Ilmiah Matrik EKONOMIS : Journal of Economics and Business JITK (Jurnal Ilmu Pengetahuan dan Komputer) Pendas : Jurnah Ilmiah Pendidikan Dasar Jurnal Sisfokom (Sistem Informasi dan Komputer) Voice Of Informatics Jurnal Sistem Cerdas CSRID (Computer Science Research and Its Development Journal) SENSITEK Abdi Wiralodra : Jurnal Pengabdian Kepada Masyarakat E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi IT (INFORMATIC TECHNIQUE) JOURNAL Jurnal Scientia Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Jurnal Teknik Informatika (JUTIF) Jurnal PkM MIFTEK Jurnal Algoritma Hulondalo Jurnal Ilmu Pemerintahan dan Ilmu komunikasi (JIPIK) Jurnal Teknologi Informasi COMPETITIVE: Journal of Education Amal Ilmiah: Jurnal Pengabdian Kepada Masyarakat Jurnal Sistem Informasi dan Teknologi Informasi
Fitri Nuraeni
Institut Teknologi Garut
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Public Health Social Sciences Other

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IMPLEMENTATION OF AUGMENTED REALITY IN MOTORCYCLES INTRODUCTION LEARNING Sri Rahayu; Vernanda Adhitya Darmawan; Fitri Nuraeni; Dewi Tresnawati
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 5 (2022): JUTIF Volume 3, Number 5, October 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.5.209

Abstract

Augmented reality technology in the field of education can be used as an interactive learning media that can minimize boredom during the conventional teaching and learning process, namely by using books containing text and pictures.The advantages of augmented reality technology, it can be used to explain basic motorcycle introduction materials, which usually require a complete explanation not only from writing and pictures. Therefore, this study aims to create an interactive learning media for motorcycle engine introduction based on augmented reality. The method used in this learning media is Research and Development consisting of needs analysis, design design, design implementation, testing, expert validation, media revision, feasibility test, media improvement, and product. The results of this study are interactive learning media applications that display 3-dimensional objects regarding motorcycle engines using audio explanations for each of the existing 3-dimensional objects, as well as adding a quiz feature to increase interactivity in the teaching and learning process.
Raspberry Based Hand Gesture Recognition Using Haar Cascade and Local Binary Pattern Histogram Helfy Susilawati; Fitri Nuraeni
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 8, No 4 (2022): Desember
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i4.24643

Abstract

Many companies and even public institutions for civil servants currently use photo-taking for the attendance. However, this strategy is still considered ineffective since the employees still can hack the attendance by making their own photos and put them in their desks. Therefore, an alternative that can complement the current face detection method is highly needed so that the employee’s attendance can be directly monitored. One of the methods that can be used to detect the attendance is hand gesture detection. This research aims to detect hand gestures made by the employees to ensure whether they really come to work or not. This research make  the chance for manipulation using photo or fake GPS is quite small. For the purpose of hand gesture recognition, this study utilized Local Binary Pattern Histogram algorithm. The hand gesture image was first taken using a raspberry pi camera and then processed by the device to examine whether it matches the registered ID or not. The results showed that ID recognition by using hand gestures is detectable. The number recognition in hand gestures includes numbers 1 to 10. The test results showed that for 5 trials, the average time required for reading hand gestures using a laptop was 9.2 seconds, while that of using raspberry was 14.2 seconds. The results of this research show that the system has not been able to distinguish which hand is read first, so numbers that have the same number are considered the same, such as 81 and 18. So, the motion reading using a raspberry takes longer than that of using a laptop because the laptop's performance is higher than that of a raspberry and system cannot distinguish between numbers consisting of the same number.
COMPARISON OF FACIAL IMAGE SEGMENTATION USING K-MEANS AND FUZZY C-MEANS CLUSTERING METHODS Fitri Nuraeni; Helfy Susilawati; Yoga Handoko Agustin
Jurnal Scientia Vol. 11 No. 02 (2022): Education, Sosial science and Planning technique, November
Publisher : Sean Institute

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

Abstract

Accuracy in face recognition is very important, so the process always begins with image segmentation. This segmentation is how the process of dividing the image into several objects, so that the object to be analyzed can be found. The easiest image segmentation is to use the clustering method. However, with so many clustering algorithms, it is necessary to know which algorithm can produce the best image segmentation for facial image datasets taken from employee attendance applications. This study uses an experimental method with image preparation stages, segmentation with k-means and fuzzy c-means algorithms, followed by evaluation using RSME, PSNR, and SSIM. The results of this study indicate that it can be said that for facial image segmentation taken from this employee attendance application, the segmentation of the clustering results with fuzzy c-means has the RMSE, PSNR, and visual effects values ​​needed for segmentation quality. on the image that is better than the image from the k-means segmentation.
OPTIMIZATION OF MARKET BASKET ANALYSIS USING CENTROID-BASED CLUSTERING ALGORITHM AND FP-GROWTH ALGORITHM Fitri Nuraeni; Dewi Tresnawati; Yoga Handoko Agustin; Gisna Fauzi
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 6 (2022): JUTIF Volume 3, Number 6, December 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.6.399

Abstract

The proliferation of the food and beverage sales business requires the creativity of business owners to offer their flagship products to every consumer, both new and subscribed consumers. A large number of menu choices makes the ordering process long because consumers are confused about which menu will be the best choice. the seller to be able to provide the right recommendations so that orders can take place faster. Shopping cart analysis is an activity that has often been done to find out the items found that are sold simultaneously. The FP-Growth association method is a faster algorithm for generating association rules, but the association process in large dataset sizes tends to add large items so that the accuracy value of association rules decreases. So that in this study, the grouping of datasets was carried out using a clustering model with a centroid-based algorithm, namely k-means, k-medoids, and fuzzy c-means. This research was conducted through dataset collection, dataset preparation, clustering modeling, evaluation of clustering models using DBI and silhouette index, association modeling, and evaluation of association models using lift ratio. The results of this study showed that the clustering model with the best DBI and silhouette index values ​​was at k=3 for k-means, k=2 for k-medoids, and k=7 for fuzzy c-means. The number of association rules is generated from the grouped data set using fuzzy c-means, but the highest average lift ratio is in the association rules generated from the grouping data set using k-means. From the association model using k-means and FP-Growth, 32 unique association rules were found with the 4 most frequently found items, namely cireng chili oil, regal milk coffee, banana cheese, and vietnam drip.
Pemetaan Karakteristik Mahasiswa Penerima Kartu Indonesia Pintar Kuliah (KIP-K) menggunakan Algoritma K-Means++ Fitri Nuraeni; Dede Kurniadi; Gisna Fauzian Dermawan
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 11, No 3 (2022): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v11i3.1439

Abstract

Pengetahuan baru mengenai pemetaan karakteristik mahasiswa penerima KIP-K pada perguruan tinggi dapat menggunakan penggalian data yaitu teknik clustering. Pemetaan karakteristik ini dilakukan dari hasil pengelompokan mahasiswa berdasarkan atribut akademik dan non-akademik menggunakan algoritma K-Means++ yang dapat menurunkan jumlah perulangan dalam proses pengelompokan datanya. Dengan menggunakan metode Cross-Industry Standard Process for Data Mining (CRIPS-DM) dan algoritma clustering yaitu k-means++. Dari penelitian ini, dihasilkan model clustering dengan nilai k=2 berdasarkan grafik metode elbow dengan  nilai silhouette coefficient terbesar yaitu 0.7523 dan davies bouldine index (DBI) terkecil yaitu 0.49053. Dari hasil pemetaan karakteristik mahasiswa penerima KIP-K ini, didapatkan pengetahuan yang dapat menjadi bahan pengambilan keputusan perguruan tinggi penyelenggaran dalam penyeleksian pendaftar KIP-K sehingga meminimalisir masalah akademik mahasiswa penerima KIP-K di kemudian hari.
PERBANDINGAN IMPLEMENTASI ALGORITMA K-MEANS++ DAN FUZZY C-MEANS PADA SEGMENTASI CITRA WAJAH Fitri Nuraeni; Helfy Susilawati; Yoga Handoko Agustin
JuTI "Jurnal Teknologi Informasi" Vol 1, No 2 (2023): Februari 2023
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (524.617 KB) | DOI: 10.26798/juti.v1i2.722

Abstract

Dalam pengenalan wajah menggunakan metode pengolahan citra, dibutuhkan proses segmentasi citra agar dapat dilakukan proses analisis citra selanjutnya. Segmentasi citra dapat dilakukan dengan metode clustering yang memiliki beberapa algoritma berbasis centroid, seperti k-means dan fuzzy c-means. Algoritma k-means sendiri memiliki beberapa varian, salah satunya k-means++ dimana varian ini lebih cerdas dalam memilih inisial centroid dibanding k-means yang memilih inisial centroid secara acak. Algoritma fuzzy cmeans sendiri telah memiliki keunggulan dalam  engelompokan objek yang tersebar secara tidak teratur. Untuk mendapatkan segmentasi yang baik untuk pengenalan wajah, perlu dicari algoritma mana yang dapat menghasilkan segmentasi citra dengan kualitas baik. Sehingga pada penelitian ini, dilakukan penelitian ekspresimen dengan menggunakan citra wajah yang disegmentasi dengan algoritma k-means++ dan fuzzy c-means, kemudian dilakukan evaluasi menggunakan RSME, PSNR dan SSIM. Dari penelitian ini dihasilkan segmentasi citra dengan fuzzy c-means lebih baik dibandingkan hasil k-means++ berdasarkan nilai RSME, PSNR dan SSIM
HAND GESTURE AND DETEKSI WAJAHDETECTION USING RASPBERRY PI Helfy Susilawati; Ade Rukmana; Fitri Nuraeni
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 1 (2023): JUTIF Volume 4, Number 1, February 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.1.635

Abstract

Face detection is currently used for various purposes, one of which is to record employees attendance. This strategy is ineffective since the employees still can hack the attendance by making their own photos and put them in their desks. If they are unable to come to the office,they can always ask their colleagues to submit their already available photos.Therefore, an alternative that can complement the current face detection method is highly needed.One of the methods that can be used is hand gesture detection.This study aims to detect hand gestures made by the employees to ensure whether they really come to work or not,so the chance for manipulation is quite small.For the purpose of hand gesture recognition, this study utilized Local Binary Pattern Histogram algorithm. LBPH is an algorithm used for the image matching process between images that have been given training and images taken in real time.The hand gesture image was first taken using a raspberry pi camera and then processed to examine whether it matches the registered ID or not.The results showed that ID recognition by using hand gestures is detectable and is in accordance with the registered ID.The number recognition in hand gestures includes numbers 1 to 10. The test results showed that, the average time required for reading hand gestures using a laptop was 9.2 seconds, while that of using raspberry was 14,2 seconds.Motion reading using a raspberry takes longer than that of using a laptop because the laptop's performance is higher than that of a raspberry.
Rancang Bangun Sistem Informasi Geografis Pendataan Jalan di Kabupaten Garut Berbasis Web Fitri Nuraeni; Raden Erwin Gunadhi Rahayu; Moch. Lutfhi Waliyul Fahmi
Jurnal Algoritma Vol 20 No 1 (2023): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.20-1.1228

Abstract

Roads can be said to be a transportation infrastructure that connects one place to another. Roads of different lengths have different surface layers and their respective conditions. At present the road data collection carried out by the Public Works and Spatial Planning Office (PUPR) is still being carried out by inputting and storing data that is still written in the document. Based on this problem, the Geographic Information System is one of the solutions that can be used, this system will later become a service tool for the Office (PUPR) in collecting data and converting spatial data into digital maps to make it easier to visualize road conditions to the public. The methodology used is the Rational Unified Process with the stages or phases in it, while the application development uses the Laravel framework and the mapping uses Leaflet JS. The results of this study obtained a Web-Based Road Data Collection Graphic Information System. This system is expected to be able to assist the Office (PUPR) when working on road data collection and visualizing road conditions to the public.
The IMPLEMENTASI CAESAR CIPHER & ADVANCED ENCRYPTION STANDAR (AES) PADA PENGAMANAN DATA PAJAK BUMI BANGUNAN Fitri Nuraeni; Yoga Handoko Agustin
Jurnal Ilmiah Matrik Vol 22 No 2 (2020): Jurnal Ilmiah Matrik
Publisher : Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/jurnalmatrik.v22i2.949

Abstract

Abstract : Property tax as one source of local revenue has an important role in the progress of the village. Management of property Tax data in general at the village level still uses the usual number management application. While the property tax data needs to be secured because it is classified as confidential data, which has the potential to cause damage if accessed by unauthorized persons. To maintain the security aspects of the information, a cryptographic system can be used which provides encryption and data description facilities. The cryptographic system used is Caesar Cipher's super encryption and Advanced Encryption Standard (AES) -128-EBC. To test the encryption quality of this cryptographic system an experimental method is used, by comparing the ciphertext file size, encryption time, entropi value, correlation value, histogram graph and avalanche effect. The test results obtained by Caesar Cipher and Advanced Encryption Standard (AES) -128-EBC cryptographic systems, have good correlation and entropy values ​​with better avalanche effect values ​​compared to the AES algorithm alone. Keywords: aes-128-ebc, caesar cipher, confidential, encryption, tax Abstrak : Pajak Bumi dan Bangunan sebagai salah satu sumber pendapatan asli daerah memiliki peranan penting dalam kemajuan desa. Pengelolaan data Pajak Bumi dan Bangunan secara umum di tingkat desa masih menggunakan aplikasi pengelola angka biasa. Sedangkan data Pajak Bumi dan Bangunan (pbb) perlu diamankan karena tergolong ke dalam data confidential, yang mana berpotensi menimbulkan kerusakan apabila diakses oleh orang yang tidak berwenang. Untuk menjaga aspek kemananan informasi tersebut, dapat digunakan sistem kriptografi yang didalamnya menyediakan fasilitas enkripsi dan deskripsi data. Sistem kriptografi yang digunakan adalah super enkripsi Caesar Cipher dan Advanced Encryption Standart (AES)-128-EBC. Untuk menguji kualitas enkripsi sistem kriptografi ini digunakan metode eksperimen, dengan membandingkan ukuran file cipherteks, waktu enkripsi, nilai entropi, nilai korelasi, grafik histogram dan avalanche effect. Hasil pengujian didapat sistem kriptografi Caesar Cipher dan Advanced Encryption Standart (AES)-128-EBC ini, memiliki nilai korelasi dan entropi yang tergolong bagus dengan nilai avalanche effect yang lebih baik dibandingkan dengan algoritma AES saja. Kata kunci: aes-128-ebc, caesar cipher, enkripsi, pajak, rahasia
Decision Support System for The Program Indonesia Pintar Scholarship Using Simple Additive Weighting Method Septiana, Yosep; Nuraeni, Fitri; Anisa, Kamelia
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 4 (2022): Article Research: Volume 6 Number 4, October 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i4.11786

Abstract

The Program Indonesia Pintar (PIP) is an educational scholarship from the government for students who lack funds to continue their education, one of which is at the junior high school level. It is still done manually when selecting students who are eligible to receive the PIP scholarship at the junior high school level. This is less efficient because the selection process will take a long to analyze, and the reporting process is not yet computerized. To overcome these problems, a decision support system is needed to assist schools in selecting students who receive PIP assistance. The method used for the development of a decision support system is Simple Additive Weighting (SAW). The choice of this method is because the decision-making process is carried out by searching for the highest alternative from all alternatives so that the assessment is more accurate based on the provisions of the criteria values and preference weights. With the construction of this system, it is expected to be able to provide a solution so that the student selection decision-making process can be carried out quickly and accurately.
Co-Authors Ade Rukmana Ade Sutedi, Ade Aflaah, Gina Ramadhantie Afridha Laily Alindra Ajif, Arvin Muhammad Alamsyah, Hadi Algi Muhammad Sahrin Alindra, Afridha Laily Amarullah Bachtiar Amrulloh, Muhammad Fawaz Andi Sanjaya Anisa Devisa Putri Anisa, Kamelia Arindawati , Weni A. Asep Deddy Supriatna Asri Mulyani Astri Yuliastri Ati Nursahati Ayu Utami, Neng Riski Azhari, Sonia Nada Nur Azzahra, Elvyn Kemala Budhiharti, Tri Widiya Dani Kustiawan Dede Kurniadi Dewi Tresnawati Dewi Tresnawati dewi, rinanda Diazki, Moch Haiqal Diki Jaelani Dini Destiani Siti Fatimah Egi Badar Sambani, Egi Badar Elsen, Rickard Faturrohman, Nadhif Fauza Rohman Firdaus Al Anwari, M Riadi Firmansyah, Marshal Gisna Fauzi Gisna Fauzian Dermawan Hadi Wijaya, Tryana Hafiziani Eka Putri, Hafiziani Eka Hazar, Aura Fitria Helfy Susilawati HELFY SUSLAWATI Hikmatunisa, Nenden Permas Ilmasik, Heryaman Saptahadi Imas Dewi Ariyanti Indra Nurfajri Inna Risdiani Jaelani, Jaka Muhammad Jatnika, Rijal Ajji Kahfi, Mochammad Leni Fitriani, Leni Liptia Venica Maulana Firdaus, Muhammad Hasby Maulana Ramdani Maulana Yusuf Moch. Lutfhi Waliyul Fahmi Muhamad Rifki Renaldi Muhammad Arief Sobirin Muhammad Farhan Muhammad Syauqi Mubarok nanang nanang Nashier, Luthfi Abdurahman Nopi Krisnawati Nurhajati, Ayu Rahayu Nurussama, Alfiana Permata Ayu, Metaninda Puspa Rahayu Putra, Yuda Pratama Putri, Puput R. Mujahid Al-Haq Rachmatullaily Tinakartika Rinda Raden Erwin Gunadhi Rahayu Raharja, Indra Trisna Rahayu, Diva Nuratnika Reftiana Rohman, Ripan Ridwan Setiawan Ridwan Setiawan Ridzky Ichlasul Amal Rijal Ajji Jatnika Rika Lestari Rinda Cahyana Risa Aisyah Rizky Febriana Salis Elmadani Siti Wahyuni, Yayu Sofyan Iskandar, Sofyan Sri Mulyani Lestari Sri Rahayu Suryani, Isma Susanto Susanto Syahrum Agung Tanpidzia, Mochammad Kahfi Tazqia Aulia Rahmawati Ujang Falah Purnama, Ujang Falah Vernanda Adhitya Darmawan Wahyu Sindu Prasetya Wijdan Nurhakim Yoga Handoko Agustin Yoga Handoko Agustin Yogiarni, Tiara Yosep Septiana Yuda Pratama Putra Yuda Purnama Putra Yusuf , Alifa Witri Alfahira Yusuf, Alifa Witri Alfahira Zaelani, Jaka Muhammad Zaputra, Ali Rahman Reza