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All Journal CommIT (Communication & Information Technology) Jurnal Ilmiah Kursor Jurnal Teknoinfo Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Journal of Computer System and Informatics (JoSYC) Operations Research: International Conference Series Prosiding Konferensi Nasional PKM-CSR Jurnal Aplikasi Bisnis dan Komputer Journal of Engineering and Information Technology for Community Service Smart Techno (Smart Technology, Informatic and Technopreneurship) J-Icon : Jurnal Komputer dan Informatika Indonesian Journal of Statistics and Its Applications
Arie Qur’ania
Universitas Pakuan
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Nursing Public Health Social Sciences Other

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Identifikasi Pengenalan Karakter Plat Nomor Kendaraan Menggunakan Jaringan Syaraf Tiruan Berbasis Citra Digital Sufiatul Maryana; Arie Qur’ania; Agung Prajuhana Putra
KOMPUTASI Vol 15, No 1 (2018): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (719.773 KB) | DOI: 10.33751/komputasi.v15i1.1266

Abstract

Meningkatnya volume kendaraan bermotor yang terjadi saat ini membuat kebutuhan akan adanya sistem yang dapat diterapkan pada banyak aplikasi pemantauan aktivitas lalu lintas dantaranya pembayaran jalan tol elektronik, pelanggaran lalu lintas, pencurian kendaraan dan lain sebagainya. Tujuan dari peneltian ini adalah mengidentifikasi pengenalan karakter plat nomor kendaraan menggunakan Jaringan Syaraf tiruan berbasis citra digital, pengenalan karakter dan keberhasilan proses klasifikasi ditentukan dari keberhasilan ekstraksi fitur tiap karakter sehingga dengan bentuk karakter yang beragam akan menambah tingkat kesulitan dalam proses pengenalan. Pengenalan pola pada plat nomor kendaraan menggunakan métode Jaringan Syaraf Tiruan yang terdiri dari beberapa tahapan, yaitu deteksi lokasi plat nomor, praproses citra plat nomor, memilih data uji dan data latih, indentifikasi menggunkan JST diantaranya Model klasifikasi JST, pengujian JST dan Akurasi JST. Data yang diambil sebanyak 160 yang terdiri atas 40 citra wilayah Bogor (F), 40 citra wilayah Jakarta (B), 40 citra wilayah Bandung (D) dan 40 citra wilayah Purwakarta (T). Data dari masing-masing jenis plat nomor dibagi menjadi dua bagian, 30 buah untuk data latih dan 10 buah untuk data uji. Dari uji coba berdasarkan 40 data latih yang dilakukan terdapat 31 data uji yang terdefinisi atau akurasi sebesar 77,5%. Ekstraksi ciri yang digunakan dalam penelitian ini terdiri atas 6 parameter yaitu nilai entropi, variants, means, red, green dan blue, sedangkan proses identifikasi menggunakan Jaringan Syaraf tiruan. Hasil identifikasi akan menampilkan data uji dengan kode wilayahnya berdasarkan nilai yang terdekat dengan data latih, sehingga mendapatkan hasil 77,5%.Kata Kunci: Multimedia Plat Nomor, Deteksi, JST
Kamus Digital Tanaman Obat Menggunakan Algoritme Knuth Morris Pratt Berbasis Mobile Arie Qurania; Triastinurmiatiningsih -; Erika Candra
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol 19, No 1 (2022): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v19i1.4269

Abstract

Digital dictionary of medicinal plants a collection of applications a collection of names of medicinal plants. This application was developed to make it easier for users to access the use of medicinal plants based on keywords, names of common diseases such as asthma, diarrhea, fever, headache, diabetes, and so on. The obstacle in using the digital dictionary application of medicinal plants is that it is difficult to find exact information on drug searches, because the vocabulary in producing several other items is not necessarily the same as what is being sought. This study uses the Knuth Morris Pratt (KMP) algorithm search technique on a digital dictionary of medicinal plants by matching keywords as input with strings between text and patterns. This study aims to develop previous research on a digital dictionary of medicinal plants using a mobile-based Rocchio algorithm that searches medicinal plant data by querying proximity in a database that has weaknesses in words that have the same meaning with different words, using another search technique, namely KMP. is expected to get optimal results on search results based on the keyword name of the disease. The test results with 30 keywords on 640 medicinal plant data resulted in a precision value of 92.4, accuracy and recall of 100%.
SISTEM ACCESS CONTROL RUANGAN LABORATORIUM DAN PERKULIAHAN MENGGUNAKAN RADIO FREQUENCY IDENTIFICATION Dian Kartika Utami; Akbar Sugih Miftahul Huda; Arie Qur’ania; Rizki Pratama
Jurnal Teknoinfo Vol 16, No 2 (2022): Juli
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jti.v16i2.1897

Abstract

Access control adalah suatu cara untuk pengendalian terhadap akses seseorang dalam memasuki ruangan. Pengendalian ini berfungsi untuk membatasi seseorang yang memiliki hak atau tidak dalam memasuki sebuah ruangan. Resiko keamanan yang dapat terjadi adalah kerusakan aset didalam ruangan yang timbul karena ada orang yang dapat mengakses ruangan dan menggunakan aset didalamnya. Penyebab kerusakan atau kehilangan ini akan dapat dilacak dengan menggunakan log book yang diisi pada setiap mengakses ruangan. Dengan resiko kerusakan dan kehilangan akibat lemahnya pengendalian akses ruangan. Dibutuhkan sebuah sistem yang dapat mengunci dan terbuka secara otomatis dengan pengenal yang dimiliki oleh orang-orang yang berhak mengakses ruangan. Selain itu diperlukan sebuah sistem yang dapat mencatat akses setiap orang yang memiliki hak sehingga resiko kerusakan dan kehilangan aset dapat dilacak.
PKM PAUD Annisa Rumpaka Dan PAUD Al Ikhlas Kecamatan Ciampea Kabupaten Bogor Dalam Mengimplementasikan Smart PAUD Melalui Penyediaan Aplikasi, Pelatihan Dan Pendampingan Pengelolaan Administrasi PAUD Bebasis Komputer Iyan Mulyana; Arie Qur’ania; Andi Chairunnas
Prosiding Konferensi Nasional Pengabdian Kepada Masyarakat dan Corporate Social Responsibility (PKM-CSR) Vol 1 (2018): Prosiding PKM-CSR Konferensi Nasional Pengabdian kepada Masyarakat dan Corporate Socia
Publisher : Asosiasi Sinergi Pengabdi dan Pemberdaya Indonesia (ASPPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (412.936 KB)

Abstract

Di Kecamatan Ciampea Kabupaten Bogor terdapat sekitar 46 PAUD .Permasalahan yang dihadapi oleh pengelola PAUD di Kecamatan Ciampea seperti di PAUD ANNISA RUMPAKA dan PAUD Al IKHLAS adalah belum memiliki komputer dan belum mempunyai aplikasi untuk mengelola adminitrasi PAUD berbasis Komputer (SMART PAUD). Semua pengelolaan adminitrasi siswa maupun kegiatan pembelajaran masih dilakukan dengan pencatatan secara manual. Sehingga menghambat dalam memberikan layanan kepada siswa dan orang tua serta dalam pembuatan laporan PAUD yang sangat dibutuhkan untuk pengisian Portal DAPODIK PAUD. Keterlambatan dan ketidak tepatan dalam pengisian administrasi PAUD di Portal DAPODIK PAUD akan berdampak kepada tidak diperolehnya bantuan Operasional PAUD dari Pemerintah. Dengan kondisi tersebut di atas maka salah satu solusi adalah dengan dilaksanaakn Program Kemitraan Masyarakat ( PKM) dengan membantu meningkatkan kemampuanya para pengelola dan Guru PAUD khususnya di PAUD Annisa Rumpaka dan PAUD AL Ikhlas dalam bidang Pengelolaan adminitrasi PAUD berbasis komputer yang disebut SMART PAUD. Yaitu melalui kegiatan penyediaan sarana komputer beserta aplikasi komputer SMART PAUD termasuk kegiatan pelatihan dan pendampingannya. Sehingga apabila akan mengisi data dan laporan ke Portal DAPODIK PAUD tinggal mengambil dan mentransfer dari Aplikasi yang telah tersedia dengan cepat dan tepat. Melalui Program Kemitraan Masyarakat yang terdiri dari penyediaan Aplikasi, pelatihan dan pendampingan ini diharapkan dapat menunjang meningkatakan kualitas pengelolaan dan proses pengajaran di PAUD khususnya PAUD Annisa Rumpaka dan PAUD Al Ikhlas yang akan menjadi percontohan PAUD-PAUD lainnya di Kecamatan Ciampea
Pengenalan Canva Sebagai Media Promosi Lingkungan Hidup di SMP-IT Bina Masyarakat Mandiri Lita Karlitasari; Gustian Rama Putra; Arie Qur'ania; Irma Anggraeni; M. Iqbal Suriansyah; Boldson H. Situmorang; Agus Ismangil; Dinar Munggaran Akhmad; Siska Andriani; Mulyati Mulyati; Erniyati Erniyati
Journal of Engineering and Information Technology for Community Service Vol 1, No 3 (2023): Volume 1, Issue 3, January 2023
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jeit-cs.v1i3.194

Abstract

This Community Service activity is entitled Introduction to Canva as a Media for Environmental Promotion, which is carried out in a partner environment, namely Tepadu Islamic Junior High School Bina Masyarakat Mandiri (BMM IT Middle School). The purpose of this PkM activity is to provide partners with knowledge about using Canva as a medium for promoting the environment, encourage school members to plant medicinal plants in the school environment and be able to use them in an effort to create an environmentally friendly school as well as establishing cooperation between the Computer Science Study Program, Faculty of Mathematics and Natural Sciences, Unpak and SMP IT BMM.
Desain Canva Sebagai Media Promosi Usaha Mikro dan Media Informasi di Desa Bantarsari Gustian Rama Putra; Arie Qurania; Yusma Yanti; Puspa Citra; Syarif Hidayatullah; Hermawan Hermawan; Victor Ilyas Sugara; Asep Saepulrohman; Agung Prajuhana Putra; Kotim Subandi; Adriana Sari Aryani; I Wayan Sriyasa
Journal of Engineering and Information Technology for Community Service Vol 1, No 3 (2023): Volume 1, Issue 3, January 2023
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jeit-cs.v1i3.210

Abstract

Digital information media in this era has very good potential, especially in developing micro-businesses to introduce their products, besides that information media is also needed to provide education and information to socialize, this is very necessary for the government in the district to develop village results and information that can be conveyed clearly to the community. Community service carried out by the Computer Science Study Program of Pakuan University aims to provide training to village office staff and junior and senior high school students in Bantarsari Village to be able to apply Canva as a medium for promoting micro-business and related information media, socialization, disaster prevention, appeals and other notifications in Bantarsari Village
Sentiment Analysis of Opinions on the Use of Devices in Students Using the Support Vector Machine (SVM) Method Muhammad Zuhri; Arie Qur'ania; Mulyati Mulyati
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol 20, No 1 (2023): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v20i1.6558

Abstract

Sentiment Analysis is a field of science in analyzing a sentiment or opinion on a particular object or problem and the opinion can be divided into several purposes (classes) that lead to negative, neutral or positive opinions. Gadgets (gadgets) are human aids in many fields including work, entertainment, communication and information, the use of gadgets themselves encompasses all ages including school students who use gadgets excessively that affect the mental, physical and attitudes of users. Twitter social media is one of the social media that is used by the public in making opinions about the influence of gadgets, especially parents, these opinions are useful for other users in determining the granting of access rights and direction for children, especially students in using gadgets. Opinion classification is needed in making it easier for other users to see whether opinions from the influence of gadgets fall into the negative, neutral or positive classes. The method used in the classification of opinion is Support Vector Machine (SVM). The data used in this study amounted to 1354 taken in 2019 using web scraping techniques on the Twitter site which are then pre-processed so that it can be processed into the program and classified into 3 classes of sentiments, namely negative, neutral and positive sentiments. In finding the average value of accuracy in the distribution of training data and test data using k-fold cross validation of 10-fold produces an average value of 85.3%. Then testing is done to measure the performance of the SVM method using confusion matrix in the percentage of training data and different test data and produces the highest accuracy value of 83.3%.
IDENTIFIKASI DEFISIENSI UNSUR HARA PADA TANAMAN CABAI MENGGUNAKAN SUPPORT VECTOR MACHINE Arie Qur’ania; Lita Karlitasari; Sufiatul Maryana; Cecep Sudrajat; Zolla Zolla
J-ICON : Jurnal Komputer dan Informatika Vol 11 No 1 (2023): Maret 2023
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v11i1.9803

Abstract

Plants, like other living things, need a combination of nutrients to live, grow and reproduce. Nutrients in plants can also be divided into two, namely mobile nutrients and immobile nutrients (non-moving nutrients). The condition of plants that are deficient or lacking in nutrients will experience growth disturbances and affect the yield of leaves or fruit. Leaf color can be a characteristic of plants under normal conditions or experiencing nutrient deficiencies. Deficiency of nutrients in plants will affect leaf shape, fruit production and plant age which results in stunted growth and rapid death of plants, in fruit production there will be loss of flowers or ovaries so that production will decrease. So far, plant maintenance has been done manually. Each plant is seen for later analysis of the results and it takes time to identify nutrient deficiencies. The aim of the study was to identify nutrient deficiencies in image-based chili plants based on the characteristics of the Red, Green, Blue (RGB) color and texture analysis using the Support Vector Model (SVM). The benefit of the research is to make machine learning-based applications to identify nutrient deficiencies which are divided into four classes, namely nitrogen (N) and phosphorus (P) deficiencies, P and potassium (K) deficiencies, N and K deficiencies, and chili leaves with normal class. .There are 120 plant data with an accuracy of 84.4%.
KAMUS DIGITAL TANAMAN OBAT MENGGUNAKAN ALGORITMA ROCCHIO BERBASIS MOBILE Arie Qurania
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol 17, No 2 (2020): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v1i1.2063

Abstract

Medicinal plants are known since the days of ancestors used as natural ingredients for various diseases such as diarrhea, colds, hypertension, diabetes, malaria, dengue fever, stomach ache, intestinal inflammation, cholesterol, and toothache. Medicinal plants can not replace the existence of medical drugs that have been clinically tested but the efficacy of medicinal plants can be used as an alternative treatment. Medicinal plants can be used in several parts of the plant, including leaves, stems, tubers, fruit, roots, and bark. Society generally knows the efficacy and how to mix medicinal plants from the experience of previous parents or through books and writings. Search through books or writings requires a short time compared to searches through digital media such as mobile phones. The research aims to create a digital dictionary of mobile-based medicinal plants which has a search facility based on the words entered, for example, the contents of the medicinal plants. Digital dictionary application of medicinal plants using the pecarian technique with Rocchio algorithm with a total data of 200 medicinal plants.KAMUS DIGITAL TANAMAN OBAT MENGGUNAKAN ALGORITMA ROCCHIO BERBASIS MOBILE
EKSTRAKSI CITRA MENGGUNAKAN METODE LAPLACIAN DAN SVM (SUPPORT VECTOR MACHINE) UNTUK IDENTIFIKASI JENIS TANAMAN PAKU BERDASARKAN CITRA SPORA Sufiatul Maryana; Herfina Herfina; Arie Qurania; Herlinda Herlinda
Jurnal Teknoinfo Vol 17, No 2 (2023): Vol 17, No 2 (2023) : JULI
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jti.v17i2.2579

Abstract

Spores are a breeding tool for ferns (Pteridophyta) which are generally found under the surface of each leaf. Research on the characteristics of Pteridophyta spores is generally done by observing their size and shape to see the type of spore. The method that will be carried out in this study requires a lot of understanding, experience, accuracy and time to achieve high accuracy in determining the type. Based on these reasons, it is necessary to develop another technique with modeling to help identify the type of Pteridophyta in the spore. This paper discusses image extraction for fern identification based on spore images using the Laplacian method and SVM. Laplacian method is used to extract features from spore images, while SVM is used to classify ferns. This method requires a lot of understanding, experience, accuracy and time to achieve high accuracy in determining the type. Based on these reasons, it is necessary to develop another technique with modeling to help identify the type of Pteridophyta in the spore. The purpose of this research is to make Support Vector Machine (SVM) modeling to identify fern species based on spore images in Eigen space. The data used are spore images with four classes, each of which has 24 data per class with a total of 96 images. The method used in this research is Laplacian method for feature extraction and SVM for data classification using Gaussian RBF and Polynomial kernel function experiments. The result of this research is the accuracy of each extraction that has been tried. The best result lies in the RBF kernel function with 70% feature extraction and 10 parameters with an accuracy of 98.96%.
Co-Authors Abhishek R Mehta Achmad Noerkhaerin Putra Adriana Sari Aryani Agung Prajuhana Putra Agung Prajuhana Putra Agus Ismangil Ahmad Ari Aldino Akbar Sugih Miftahul Huda Alexander A. S. Gunawan, Alexander A. S. Alexander Agung Santoso Gunawan Andi Chairunnas Anggraeni, Ade Irma Asep Saepulrohman Boldson H. Situmorang Dedi Darwis Dian Kartika Utami Dinar Munggaran Akhmad Erika Candra Erniyati Erniyati Gustian Rama Putra Gustian Rama Putra Hakiim, Reyhan Herfina Herfina Herlinda Herlinda Hermawan Hermawan Hidayat, Ari I Wayan Sriyasa Indra Fauzi Rahman Irma Anggraeni Iyan Mulyana Iyan Mulyana Kotim Subandi Lili Ayu Wulandhari Lita Karlitasari Lita Karlitasari M. Iqbal Suriansyah M. Irfan Ariandi Maryanto, Dani Aisak Mohamad Iqbal Mohamad Iqbal Suriansyah Iqbal Muhammad Zuhri Mulyati Mulyati Mulyati Mulyati Nazar Muhamad Ikhbal Negara, Teguh Puja Perdi Yansyah perdi Prihastuti Harsani Puspa Citra Rahman, Indra Fauzi Rizki Pratama Saputri, Cita Suci Sesilia Novita R Setiawansyah Setiawansyah Siska Andriani Sitna Hajar Hadad Sudrajat, Cecep Sufiatul Maryana Syarif Hidayatullah Tjut Awaliyah Triasti nurmiatiningsih Triastinurmiatiningsih, Triastinurmiatiningsih Victor Ilyas Sugara Wulandhari, Lili Ayu Yuri Rahmanto Yusma Yanti Zakiyah Humaira Zolla Zolla