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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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PENGENALAN TULISAN TANGAN DENGAN PERBAIKAN GORESAN MENGGUNAKAN INTERPOLASI BEZIER DAN SMOOTHING Ronald Ronald; 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.v1i1.3087

Abstract

This system can process images in the form of letters handwriting into digital text writing and at the time of processing, the damage from the handwriting image repaired first in order to be a form letter similar to the actual shape of the letter so that it can add recognition accuracy in using Bezier interpolation and smoothing scratches on image which is then carried handwriting feature extraction process with Global Histogram and then calculated the distance of the feature extraction with Manhattan distance or Euclidean Distance.Test results using Manhattan Distance that can achieve 80% recognition rate on number reognition, greater than the Euclidean Distance that can achieve 70% recognition rate on number recognition. The successful recognition of many affected by the similarities in the character of handwriting. In particular the test database and test images are split between uppercase, lowercase and numbers, it appears that the percentage of the recognition  improved quite a lot.
PENDETEKSIAN DAN PENGENALAN JENIS MOBIL MENGGUNAKAN ALGORITMA YOU ONLY LOOK ONCE DAN CONVOLUTIONAL NEURAL NETWORK Calvin Geraldy; Chairisni Lubis
Jurnal Ilmu Komputer dan Sistem Informasi Vol 8, No 2 (2020): 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.v8i2.11495

Abstract

Car Type Detection and Recogniton system is an application that is developed using You Only Look Once (YOLO) and Convolutional Neural Network (CNN) algorithm. This application purpose is to detect and recognize the car image from the data input. In this application the input image will be divided into two parts, namely the training image and test image. For the training image, the first step, the training image will be divided into two process stages, namely detecting the image of a car and searching for the unique features of a car.To detect the image of the car, the image will be processed to detect parts of the image of the car and not the car using the YOLO method. After obtaining a part of the car image, the image of the car will be saved as a detection model. The image that has been detected will be learning the car image by the CNN method. For the test images of the stages carried out as in the training image, after the image of the car is detected, an introduction will be made based on learning that has been done with the CNN method to obtain output in the form of a car that is successfully recognized and detected will be labeled by the application.
PERANCANGAN APLIKASI SISTEM PAKAR UNTUK MENDIAGNOSIS PENYAKIT KULIT PADA KUCING DENGAN MENGUNAKAN METODE BAYESIAN PROBABILITY Michael Antoni; Chairisni Lubis; Tony Tony
Jurnal Ilmu Komputer dan Sistem Informasi Vol 3, No 2 (2015): 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.v3i2.3321

Abstract

This application created to diagnose skin diseases on cat using Bayesian Probability method which user have to input sympthoms that they pet feel to the application. This application can also give information about the diseases that this application cover. The disaeser are Seborrhea, Malassezia, Ringworm, Scabies, Psoroptes, Demodecosis, Acutemoist Dhermatitis, Atopic Dhermatitis, dan Acnespot. Based on the test result Bayesian Probability give accuracy up to 95.55%. Key wordspenyakit kulit, kucing, bayesian probability, sistem pakar
PENGENALAN PEMBICARA DENGAN METODE MEL FREQUENCY CEPSTRUM COEFFICIENTS, MANHATTAN DISTANCE DAN EUCLIDEAN DISTANCE Immanuel Chandra; Chairisni Lubis; Agus Budi Dharmawan
Jurnal Ilmu Komputer dan Sistem Informasi Vol 1, No 2 (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.v1i2.3135

Abstract

Teknologi  biometrik merupakan suatu teknik pengenalan diri menggunakan bagian tubuh atau perilaku manusia.Sistem biometrik yang akan digunakan berbasis pengenalan pembicara yang dapat memprediksi suara seseorang. Dengan menginput suara yang direkam, akan dilakukan pengekstraksian ciri, pengenalan terhadap input dengan tahap pelatihan. Sehingga dapat mengetahui suara dari individu yang direkam.Karena itu sebagai solusinya dibuatlah perangkat lunak untuk pengenalan biometrik khususnya bagian suara dengan menggunakan metode Mel Frequency Cepstrum Coefficients (MFCC), Manhattan Distance dan Euclidean Distance. Proses pertama pada sistem ini yaitu dilakukan ekstraksi ciri pada suara yang diinput untuk mendapatkan ciri penting dari setiap suara yang kemudian disimpan kedalam basis data. Pengenalan dilakukan dengan Manhattan Distance dan Euclidean Distance dengan menghitung jarak antara nilai bobot yang didapatkan pada proses pembelajaran dengan nilai yang telah diekstraksi oleh MFCC dengan yang berada di dalam basis data. Kata Kunci:Mel Frequency Cepstrum Coefficeints, Euclidean distance, Manhattan Distance, Pengenalan Suara
PREDIKSI KURS MATA UANG DENGAN METODE LONG SHORT TERM MEMORY (LSTM) BERBASIS ATTENTION Zyad Rusdi; Chairisni Lubis; Vincent Geraldy Tjandra
Computatio : Journal of Computer Science and Information Systems Vol 5, No 2 (2021): COMPUTATIO : JOURNAL OF COMPUTER SCIENCE AND INFORMATION SYSTEMS
Publisher : Faculty of Information Technology, Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/computatio.v5i2.13117

Abstract

Currency exchange is the exchange rate for current or future payments between two currencies of each country. In Indonesia, there are frequent fluctuations in the exchange rate of USD against IDR which causes instability in economic growth. This has resulted in reduced interest from foreign investors in investing in Indonesia, and has resulted in degeneration of development because the position of foreign investors is very important for economic growth. Therefore, predictions are needed to anticipate exchange rate fluctuations using the Long Short - Term Memory (LSTM) method. Some of the steps taken are collecting data, preprocessing, splitting data, build the LSTM model architecture, training the model, and testing. From the test results, the best results were obtained for the LSTM and LSTM + attention models, namely by using the parameters of 60 timestep, 32 neurons, 150 epoch, 32 batch size, and a learning rate of 0.001. The results obtained from the LSTM model are the total training time of 108.76 seconds, the loss value is 0.000162, and the RMSE result is 1.3328. The results obtained from the LSTM + attention model are the total training time of 116.05 seconds, the loss value is 0.000157, and the RMSE result is 0.6335. So it can be concluded that LSTM with attention can improve training accuracy.
DETEKSI PENYAKIT DIABETES DENGAN METODE FUZZY C-MEANS CLUSTERING DAN K-MEANS CLUSTERING Abdi Praja; Chairisni Lubis; Dyah Erny Herwindiati
Computatio : Journal of Computer Science and Information Systems Vol 1, No 1 (2017): Computatio : Journal of Computer Science and Information Systems
Publisher : Faculty of Information Technology, Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/computatio.v1i1.233

Abstract

Diabetes adalah penyakit yang terjadi ketika kandungan glukosa di dalam darah tinggi. Tes glukosa yang menghasilkan keakuratan tinggi harus dilakukan beberapa kali untuk mendeteksi diabetes di dalam tubuh. Beberapa indikator di dalam tubuh dapat menjadi titik awal untuk mendeteksi diabetes. Bagaimanapun juga, keterbatasan seorang tenaga medis dalam mendeteksi dalam jumlah data yang sangat besar dengan cara manual menjadi kendala. Salah satu solusi untuk gap tersebut adalah menggunakan komputer sebagai perhitungan matematika dalam metode pengelompokan K-Means dan Fuzzy C-Means. Pengelompokan terdiri dari kelompok diabetes dan non-diabetes. Pengujian untuk masing-masing metode dilakukan terhadap 9 data. Hasil pengujian terbaik metode K-Means adalah 73,438% dan untuk metode Fuzzy C-Means adalah 82,812%.
Sistem Informasi Pemetaan Warisan Budaya Kawasan Banten Lama Berbasis Android Ery Dewayani; Chairisni Lubis; Bagus Mulyawan
Computatio : Journal of Computer Science and Information Systems Vol 3, No 2 (2019): COMPUTATIO : JOURNAL OF COMPUTER SCIENCE AND INFORMATION SYSTEMS
Publisher : Faculty of Information Technology, Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (638.717 KB) | DOI: 10.24912/computatio.v3i2.5554

Abstract

In this global era, when seeking information or communicate with each other, people are using information technology to support those activities. Smartphones for example, is one of affordable technology that can be owned by common people. These days, people are using smartphones anywhere and any time. On every smartphones that being used, it has a operating systems to manages smartphones hardware and provide services that given. Android is the most popular of a mobile operating systems that being used to operate smartphones in the world. Through the popularity of android and growing smartphones users, transmitting information are more effective if the information can be accessed using smartphones. On the first year of research” Mapping Banten Lama’s Cultural Heritage Website “has already developed, and to make accessibility of the information more convenient, on the second year of research has developed application program “Android Based Information System for Mapping Banten Lama’s Cultural Heritage”. This application program is accessible through any kind of android smartphones. Prototyping method is used to develop this application program. For storing data, this application program use MySql database that operate inside server (hosting) so it can can be accessed through internet. Android studio and Java programming language are used to build this application program. Black Box Testing and User Acceptance Test (UAT) are used to test this application program. The result of this research is develop a product of software that can be accessed through android smartphones.  Pada era global saat  ini  masyarakat menggunakan teknologi informasi  dalam  mencari informasi maupun untuk berkomunikasi.  Salah satu teknologi yang  terjangkau dan dapat dimiliki oleh masyarakat umum adalah handphone. Mereka membawa dan menggunakan  handphone setiap saat dimanapun mereka berada. Perusahaan gadget  mulai mengembangkan  perangkatnya  menggunakan sistem operasi Android yang akhir-akhir ini sangat popular dan menjadi perhatian masyarakat Indonesia maupun dunia. Dengan memanfaatkan perkembangan teknologi tersebut,  dalam mengenalkan berbagai informasi kepada masyarakat umum  akan lebih efektif bila informasi dapat diakses  melalui handphone. Website Warisan Budaya Kawasan Banten Lama  sudah dibuat pada penelitian tahun pertama  dan    agar lebih  memudahkan masyarakat luas untuk akses , pada penelitian tahun kedua dikembangkan suatu  program aplikasi “Sistem Informasi Pemetaan Warisan Budaya Kawasan Banten Lama  Berbasis Android”. Program aplikasi yang dikembangkan ini dapat diakses  diberbagai tipe handphone yang berbasis Android. Metodologi pengembangan sistem menggunankan metode  Prototyping.  Basisdata  menggunakan  My Sql, yang disimpan dalam server (hosting) agar dapat diakses melalui internet. Selain  itu program aplikasi  menggunakan Android Studio dengan bahasa pemrograman Java. Metode pengujian menggunakan User Acceptance Test (UAT). Penelitian ini menghasilkan produk software yang dapat diakses melalui handphone berbasis android.
Alat Virtual Assistant Untuk Membantu Treatment Pasien Patah Tulang Kaki Tony Tony; Budianto Lomewa Lo; Chairisni Lubis
Seminar Nasional Teknologi Informasi Komunikasi dan Industri 2012: SNTIKI 4
Publisher : UIN Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (769.744 KB)

Abstract

Broken leg bone is one of the conditions which must be dealt with immediately emergency quickly, appropriately and in accordance with applicable procedures. In the design of a virtual assistant to help tool treatment patient fractures foot, accelerometer sensor is used to detect boundary slope foot raised by patients. When the tool is run, the microcontroller will run a program that has been input and accelerometer sensor will detect the tilt foot limit would be appointed by the patient. In addition to the sensor, which also serves to display the LCD schedule medication as well as exercise treatment foot fracture patients and buzzer that serves as a warning sound when the schedule is on medication and exercise treatment foot fracture patients the time has come. If the process of treatment of fractures leg exercises are over, then press button ok to terminate the program. Test results show overall tool can run with either starting from warning alarm in reminding patients to take medication until the accelerometer sensor in detecting limit the slope foot raised by patients in their healing process.Keywords: virtual assistant, microcontroller, accelerometer sensor
Pendeteksian Masker dan Klasifikasi Masker Menggunakan Metode Region-Based Neural Network Syawal Ludin; Chairisni Lubis; Teny Handhayani
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 10 No. 2 (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.v10i2.22532

Abstract

At this time the world is experiencing a pandemic, the virus is COVID-19 and to prevent a very fast spread, there are many ways to spread the virus, starting from touching, one of which is through saliva when sneezing or talking, therefore all people around the world The world is given rules for washing hands, social distancing and wearing mas. However, it is very unfortunate that there are still many who do not comply with the rules made. Due to this, the mask detection system exists to facilitate community monitoring to be more obedient to the regulations that have been made. In the proposed system the Region-based Convolutional Neural Network (RCNN) is used to classify images which consist of three classes including medical masks, non-medical masks and not using masks. Later the system will detect people in one image. With the Region-based Convolutional Neural Network (RCNN) method, 2 experiments were carried out on 30 epochs with 2 different layers and the first layer got 86% accuracy and 74% accuracy validation and the second layer got 80% accuracy and validation by 79%. With the level of accuracy obtained, it is hoped that it can help the government in slowing down the rate of increase in the number of COVID-19 and also that the community can be more obedient to the rules that have been applied.
Sistem Pengenalan Covid-19 Berdasarkan Foto X-ray Paru dengan Metode EfficientNet-B0 Jourdan Stanley; Chairisni Lubis; Teny Handhayani
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 10 No. 2 (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.v10i2.22549

Abstract

Covid-19 is a viral infection disease severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Covid-19 is a group of viruses that attack the respiratory system in humans which can cause symptoms ranging from mild symptoms to severe symptoms. Currently, to detect whether a person is infected with the Covid-19 virus or not, several tests can be carried out, one of which is the polymerse chain reaction (PCR) examination. This type of examination has a high level of accuracy but this examination requires quite expensive costs, adequate laboratories and requires a long time. So from these problems there is another alternative, namely radiological examination. From these problems, a system was built that can perform classification based on x-ray images of the lungs using the convolutional neural network (CNN) method of Efficientnet-B0 architecture. This system is expected to assist medical personnel in pre-diagnosing a patient's lung condition based on their lung x-ray without changing the role of the medical personnel. After successfully building a Covid-19 recognition system, the system will be tested using the confusion matrix method where in this test there are 2 scenarios. In the first scenario, the data trained using the CLAHE preprocessing method obtained an accuracy rate of 98%, while in the second scenario the data was trained without using the CLAHE preprocessing method, the results obtained an accuracy rate of 97%. Previous research was conducted using the resnet-18 method and obtained an accuracy rate of 92%. From the results obtained prove that Efficientnet is able to increase the level of accuracy from previous studies.
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