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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) JIKSI (Jurnal Ilmu Komputer dan Sistem Informasi) Computatio : Journal of Computer Science and Information Systems Seminar Nasional Teknologi Informasi Komunikasi dan Industri JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JURNAL INSTEK (Informatika Sains dan Teknologi) Building of Informatics, Technology and Science Journal of Computer Networks, Architecture and High Performance Computing Jurnal Komputer, Informasi dan Teknologi Nusantara Journal of Multidisciplinary Science
Chairisni Lubis
Fakultas Teknologi Informasi Universitas Tarumanagara Jakarta - Indonesia
Religion Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Other

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STUDI KASUS SISTEM PAKAR UNTUK MENDIAGNOSA PENYAKIT PERNAPASAN Christ Bastian Waruwu; Chairisni Lubis; Agus Budi Dharmawan
Jurnal Ilmu Komputer dan Sistem Informasi Vol 4, No 1 (2016): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (86.53 KB) | DOI: 10.24912/jiksi.v4i1.140

Abstract

In coping with a disease usually go to the doctor or to a health clinic to get the healing, especially respiratory diseases. Because so many respiratory diseases and symptoms, so an expert or a doctor needs to examine more deeply the symptoms experienced by patients to be able determine the illness. Therefore made respiratory expert system using Dempster Shafer and Naïve Bayes Classifier. In the research, the results of testing both methods are respectively 90% in Dempster-Shafer method and 94,28% in Naïve Bayes Classifier method.
EKSTRAKSI CIRI FEATURE POINT UNTUK PENGENALAN TANDA TANGAN DENGAN MENGGUNAKAN BACKPROPAGATION NEURAL NETWORK Adrian Primanta S; Chairisni Lubis; Agus Budi Dharmawan
Jurnal Ilmu Komputer dan Sistem Informasi Vol 2, No 1 (2014): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v2i1.3164

Abstract

In this research, the main goal is to make an application to recognize people signature. To make this, we need the method to do our research. Backpropagation Neural Network that is used to train image sample and Feature Point Extraction for feature extraction. This method work with center point of the pixel image. The pre-processing are image binarization, Median filter, Thinning image with Zhang Suen algorithm, cropping, and  scaling for training image.. The method  for feature extraction is feature point extraction. This method works with counting the centeroid of the image. Number of total point centeroid is decide by depth value. The process will stop if the total point centroid is achived. After feature extraction, it will continue to train the sample image using Backpropagation Neural Network. Key wordsBackpropagation, Featurte Point Extraction, Image Binarization, Median Filter, Thinning, Threshold.
APLIKASI PENGENALAN KARAKTER TULISAN TANGAN DENGAN EKSTRAKSI CIRI DWT Yusten Wuntoro; Chairisni Lubis; Agus Budi Dharmawan
Jurnal Ilmu Komputer dan Sistem Informasi Vol 1, No 1 (2013): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v1i1.3100

Abstract

Some research indicates that every person's handwriting is unique and can be recognized by special software. To translate handwritten characters then made an application to the method of DWT (Discrete Wavelet Transform). The process is done in recognition of handwritten characters is done transferring pictures to a computer handwritten, pre-processing by using grayscale, thresholding, normalization size, thinning, edge detection Sobel, slant angle that is used when a character italics, the feature extraction Discrete Wavelet Transform is used and recognition using Euclidean Distance and Manhattan Distance. Test results from all capital letters to 260 data with 208 training data and 52 55% of the successful introduction of data on Haar lv 1, 52% in Haar lv 2, 48% on Daubechies lv 1, and 67% on Daubechies lv 2.
KLASIFIKASI CITRA IKAN MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK Elvin Elvin; Chairisni Lubis
Jurnal Ilmu Komputer dan Sistem Informasi Vol 10, No 1 (2022): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v10i1.17827

Abstract

Fish Image Classification Using Convolutional Neural Network is an application that helping classification process. The application is used by user for knowing an information about what is the name of fish species from image that visitor captured. The application is designed by Python programming language. Method of designing the application using System Development Life Cycle. The method used in training model is Convolutional Neural Network, Data used in training process are the species data set is more than 10 species and each species is more than 1000 images, The data collected has been divided into training data and test data. In training process, Fish Image Classifiation Program produce a train loss value of 0.189203, validation loss value of 0.033459 and accuracy value of 0.991029. The evaluation process is carried out using a Confusion Matrix where the diagonal data is the correct prediction data, while the other data is the wrong prediction. By evaluating the Confusion Matrix, predicted accuracy reaches 99.1%precision and recall is 0.98. The resulting accuracy is very good accuracy so that it can predict the image inputted by the user accurately.
SISTEM PAKAR MENDETEKSI BIBIT SAPI UNGGUL DENGAN METODE CERTAINTY FACTOR Friesky Christian Hendratama Jr.; Chairisni Lubis
Jurnal Ilmu Komputer dan Sistem Informasi Vol 9, No 1 (2021): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1882.666 KB) | DOI: 10.24912/jiksi.v9i1.11563

Abstract

The purpose of this research is to develop an application expert system detecting superior cow seedlings by detecting the type of cow using the characteristics that exist in cows, then based on the existing criteria, in the detection of the percentage value of accuracy for a cow can be a superior cow that produces superior cow seedlings. The characteristics and criteria are obtained from the results of interviews at the Mutiara Halim Trade Business and literature studies that have been conducted. The method used is the Certainty Factor method.The result obtained is an Expert System application that can be accessed by admins and users to detect the type and percentage value of superior seedlings in cows owned. The program is run by using XAMPP as Localhost and PHPMyAdmin as Database. Based on the trial using 40 original cow data that has been done, the results of species detection have an average accuracy percentage value of 99.9% and the result of the detection of superior cow seedlings has an average percentage value of 98.4%. Then it can be concluded that the system created can be run and can help the user in detecting the type and percentage of superior cow seedlings.
PENGIMPLEMENTASIAN OCR MENGGUNAKAN CNN UNTUK EKSTRAKSI TEKS PADA GAMBAR Ivan Wijaya; Chairisni Lubis
Jurnal Ilmu Komputer dan Sistem Informasi Vol 10, No 1 (2022): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v10i1.17836

Abstract

OCR merupakan sebuah sistem yang digunakan untuk mengekstraksi tulisan yang terdapat pada sebuah gambar sehingga dapat mempercepat proses input data. Sistem OCR merupakan sebuah sistem yang terdiri dari 2 proses yaitu pendeteksian teks dan pengenalan teks. Pada perancangan ini, digunakan 2 model CNN untuk melakukan pendeteksian dan pengenalan teks. Digunakan CNN dengan struktur Feature Pyramid Network yang menggunakan Backbone VGG19 untuk mendeteksi lokasi teks pada gambar. Untuk mengenali teks pada gambar akan digunakan CNN dengan LSTM untuk melakukan pengenalan teks pada area gambar yang telah terdeteksi. Kedua CNN dilatih ddengan menggunakan dataset ICDAR 2015, COCO-Text, dan ICDAR 2019. Pada akhir pelatihan, didapatkan model pendeteksian teks dengan besaran F1-Score sebesar 49.18%, dan model pengenalan teks dengan besar Correctly Recognized Word sebesar 55.80%
KLASIFIKASI POTENSI MENDERITA PENYAKIT JANTUNG KORONER DENGAN BACKPROPAGATION NEURAL NETWORK Henri Henri; Chairisni Lubis
Jurnal Ilmu Komputer dan Sistem Informasi Vol 10, No 1 (2022): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v10i1.17850

Abstract

Maksimal 200 kata berbahasa Inggris dicetak miring dengan Times New Roman 10 point. Abstrak berisi maksud dan tujuan penelitian, metode penelitian yang digunakan serta hasil yang dicapai.Membandingkan algoritma A dan algoritma B dalam menyelesaikan sistem persamaan linier berdasarkan kecepatan proses, ketelitian hasil serta besarnya ruang memori yang digunakan. Hasil percobaan menunjukkan algoritma B lebih cepat dari algoritma A namun algoritma A menghasilkan ketelitian yang lebih baik serta ruang memori yang kecil dibandingkan algoritma B
CROPPING OTOMATIS PADA NASKAH BRAILLE Michiko Ang; Chairisni Lubis
Jurnal Ilmu Komputer dan Sistem Informasi Vol 2, No 2 (2014): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v2i2.3217

Abstract

Braille characters are characters that are used by blind persons to write and read by touching the raised dots that exist on these characters. With the use of automatic cropping process with histogram to get one cell and one single dot for the preprocessing process, this will help to get the braille cell and one single dot easily for the further recognition. The average value of automatic cropping for braille texts reached 98,16%. Key Words automatic cropping, naskah braille
PEMBUATAN APLIKASI DAN DATABASE KERUSAKAN PADA MOTOR UNTUK SISTEM PAKAR Nikolas Patrick Fernando; Chairisni Lubis; Agus Budi Dharmawan
Jurnal Ilmu Komputer dan Sistem Informasi Vol 5, No 1 (2017): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v5i1.784

Abstract

Sistem pakar adalah sistem yang mengambil pengetahuan manusia dan memasukanya ke komputer sehingga komputer dapat menyelesaikan masalah seperti yang biasa dilakukan oleh para ahli Aplikasi komputer ditujukan untuk membantu mengambil keputusan persoalan dalam bidang tertentu. Pengambilan keputusan tersebut dengan cara menggabungkan kesimpulan dengan basis pengetahuan yang diberikan oleh satu atau lebih pakar dalam bidang tertentu.
PENGENALAN BENTUK TANGAN DENGAN METODE PCA DAN NFL SEBAGAI PENGGANTI MOUSE KOMPUTER Willy Wijaya; Chairisni Lubis; Agus Budi Dharmawan
Jurnal Ilmu Komputer dan Sistem Informasi Vol 5, No 1 (2017): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v5i1.795

Abstract

Humans who always do the daily activities with computers, need some ways and means to be able to interact (give inputs and receive outputs) with the computers. This program is made so the people can interact with the computers, using their hand gestures instead of a computer mouse. The program uses the hand image as an input. And then the program uses Principal Component Analysis and Nearest Feature Line methods to recognize user’s hand gestures. The testing of the program is carried out with four scenarios. The first and second scenario with Database of the hand images of one man, show hand gesture recognition success rate of 92% and 76%, respectively. Then the follow-up testing is carried out with two more additional scenarios. The third and fourth scenario is hand gesture recognition testing with Database of the hand images of two people combined (balanced composition).
Co-Authors Abdi Praja Adrian Primanta S Adrian Primanta Suciadi Agus Budi Dharmawan Agus Budi Dharmawan Agus Budi Dharmawan Agus Budidharmawan Albert Albert Anak Agung Gede Sugianthara Athalia, Kensa bagus Mulyawan Bagus Mulyawan Benny Karnadi Bertrand Ferrari Bezaliel Rumengan Bezaliel Rumengan, Bezaliel Bobby Tumbelaka Bobby Tumbelaka Bowo Setiadi Budianto Lomewa Lo Budiyanto Lomewa Lo Bunardi Budiman Calvin Geraldy Carlos, Daniel Christ Bastian Waruwu Christian Dwi Mardiyanto Dedi Trisnawarman Devid Sumarlie Dewi Sartika DEWI SARTIKA Donni Suharyanto Dony, Dony Dyah Erny Herwindiati Dyah Erny Herwindiati Eddy Sutedjo El Primo Gemilang Elvin Elvin Ery Dewayani Ery Dewayani Excelcis Oroh Fabrian Ivan Prasetya Fabyo Hartono Tamin Fanjie Hidayat Fanjie Hidayat, Fanjie Ferdinand Iskandar Friesky Christian Hendratama Jr. Helmy Thendean Hendra Liana Henri Henri Ilham Samuel Ilham Samuel, Ilham Immanuel Chandra Immanuel Chandra Ivan Wijaya Janson Hendryli Jeanny Pragantha Jefry Jefry Jefta Gani Hosea Jourdan Stanley Judah Suryaputra Kelvin Samuel Kevin Adhi Dhamma Setiawan Keyza Novianti Kristina Erlinda, Kristina Kurniawan Sulianto Kurniawan, Darryl Matthew Lely Hiryanto Listovie Cavito Lucy Komala Lucy Komala Lucy Komala, Lucy Marta Lisa, Marta Matthew Patrick Michael Antoni Michael Antoni, Michael Michiko Ang Michiko Ang Michiko Ang, Michiko Ni Putu Diah Ayu Vita Widia Murti Ni Putu Diah Ayu Vita Widia Murti, Ni Putu Diah Ayu Vita Widia Nikolas Patrick Fernando Novario Jaya Perdana Oktavianus Oktavianus Olivia Prima Putri Olivia Prima Putri, Olivia Prima Prawito Prayitno Prinzky Randy Sukanda Wijaya Renaldi Bong Riyandi Riyandi Roberto Davin Ronald Arifin Ronald Kurniawan Lawidjaya Ronald Ronald Saddhananda Sandy Danish Arkansa Sifra M.B. Pattiasina Sindy . Sindy Sindy Stevanndy Trisdiyanto Stevanndy Trisdiyanto Indrajaya Suki, Steven Sullivan Sullivan Sullivan Sullivan, Sullivan Sunardi Suwito Syawal Ludin Teny Handhayani Tiffany Tjandra, Vincent Geraldy Tony . Tony Tony Tony Tony TRI SUTRISNO Veronica Santoso Khalim Veronica Santoso Khalim, Veronica Santoso Vincent Geraldy Tjandra William Mulyadi William William Willy Wijaya Yegar Sahaduta Yoestinus Yoestinus Yuliana Soegianto Yusten Wuntoro Yusten Wuntoro Zyad Rusdi Zyad Rusdi