JIKSI (Jurnal Ilmu Komputer dan Sistem Informasi)
Jurnal Ilmu Komputer dan Sistem Informasi (JIKSI) diterbitkan oleh Fakultas Teknologi Informasi Universitas Tarumanagara (FTI Untar) Jakarta sebagai media publikasi karya ilmiah mahasiswa program studi Teknik Informatika dan Sistem Informasi FTI Untar. Karya-karya ilmiah yang dihasilkan berupa hasil penelitian kualitatif dan kuantitatif, perancangan sistem informasi, analisis dan perancangan progam aplikasi. Jurnal ini terbit dua kali dalam setahun yaitu pada bulan Januari dan Agustus.
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<![CDATA[PERANCANGAN SISTEM PENJUALAN BERBASIS WEB PADA TOKO SMART JAYA PHONE ]]>
<![CDATA[Reinaldi Reinaldi]]>
<![CDATA[ Jurnal Ilmu Komputer dan Sistem Informasi Vol 10, No 1 (2022): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI ]]>
Publisher : <![CDATA[Fakultas Teknologi Informasi Universitas Tarumanagara ]]>
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DOI: 10.24912/jiksi.v10i1.17860
<![CDATA[Pada zaman yang modern ini smart phone sangat dibutuhkan untuk memenuhi kebutuhan sehari-hari seperti bertukar informasi dan lain-lain. Maka dari itu bisnis penjualan smartphone sangat menguntungkan. Namun dalam penjualan ini dibutuhkan system informasi untuk menyimpan, mendata dan juga menjaga data customer, transaksi dan juga produk. Maka dari itu dibuat lah aplikasi web yang dapat memenuhi fungsi dari toko tersebut. Untuk metode perancangannya digunakan metode waterfall karena sesuai dengan kebutuhan Analisa. Dan untuk pembuatan aplikasi digunakan, Php dengan framework flutter dan CodeIgniter. Dan databasenya menggunakan mysql. Juga di dalam aplikasi terdapat fungsi forecast untuk membantu pengadaan barang dengan menggunakan metode Single Exponential Smoothing agar mendapatkan nilai peramalan.Di dalam aplikasi yang sudah dibuat dibagi menjadi tiga User yaitu Admin yang dapat melakukan pengadaan barang dan retur barang Kembali kepada supplier, juga ada kasir yang dapat melakukan penjualan kepada Customer, dan terakhir ada Owner yang dapat mengakses laporan dari Admin dan Kasir.]]>
<![CDATA[ANALISIS SENTIMEN KOMENTAR NETIZEN TWITTER TERHADAP KESEHATAN MENTAL MASYARAKAT INDONESIA ]]>
<![CDATA[Kenny Yan]]>;
<![CDATA[Desi Arisandi]]>;
<![CDATA[Tony Tony]]>
<![CDATA[ Jurnal Ilmu Komputer dan Sistem Informasi Vol 10, No 1 (2022): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI ]]>
Publisher : <![CDATA[Fakultas Teknologi Informasi Universitas Tarumanagara ]]>
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DOI: 10.24912/jiksi.v10i1.17865
<![CDATA[In today's modern era, everyone can easily exchange messages, share activities carried out in the form of images or videos using social media. Frequent use of social media can be bad for physical and mental health. Health is very important, by being healthy everyone can do activities such as studying, working, exercising, etc. Twitter as one of the social media that is widely used by the Indonesian people is used as a place to get comments that will be analyzed to find out the opinion of the Indonesian people about their mental health, this is the purpose of the analysis that has been carried out. The results obtained after analyzing the sentiments of Twitter social media users' comments on the mental health of the Indonesian people are from 2369 comment data that have been analyzed, as many as 50.8% negative, 45.1% positive and 4.1% neutral. So, it can be concluded that the sentiment analysis of social media users' comments on the mental health of Indonesian people tends to be negative. The Naïve Bayes method is used when carrying out sentiment analysis and the accuracy results are 0.7961165048543689 or rounded up to 79%.]]>
<![CDATA[PERANCANGAN SISTEM INFORMASI SEKOLAH MENENGAH ATAS KRISTEN KASIH KEMULIAAN BERBASIS WEB ]]>
<![CDATA[Daniel Hadiyanto]]>;
<![CDATA[Desi Arisandi]]>;
<![CDATA[Wasino Wasino]]>
<![CDATA[ Jurnal Ilmu Komputer dan Sistem Informasi Vol 10, No 1 (2022): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI ]]>
Publisher : <![CDATA[Fakultas Teknologi Informasi Universitas Tarumanagara ]]>
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DOI: 10.24912/jiksi.v10i1.17818
<![CDATA[The world has entered the era of digitalization where information technology is growing very rapidly, especially technology related to the internet. Almost every aspect of life uses the internet as a practical and worldwide information medium. With the development of information technology, many things can be produced in certain fields including education; such as creating a website to advertise schools and/or campuses so that more people are known to be interested in registering their children so they can continue their education, creating a database containing a list of school/academic grades to monitor the progress of students who determine their graduation correctly. and accurate, or save teaching materials online so that they are easy to learn when learning must be online, etc. In this case, SMAK Kasih Kemuliaan utilizes the internet network to introduce information about the school as completely and interestingly as possible. Thus the school can be known by the wider community and even abroad. The information technology used by SMAK Kasih Kemuliaan is the school's web profile as complete as possible, besides that the public is expected to be able to access school information easily and efficiently. By using the school's web profile, it is hoped that prospective high school students will get the school they expect. Thus, SMAK Kasih Kemuliaan can be their main goal. With the increasing number of new students at SMAK Kasih Kemuliaan, the school will progress and develop, not closing the hope of becoming one of the leading schools.]]>
<![CDATA[HUMAN ACTIVITY RECOGNATION DARI REKAMAN VIDEO PENGAWAS DENGAN METODE YOLO ]]>
<![CDATA[Harry Ronaldo Yudistira]]>;
<![CDATA[Lina Lina]]>
<![CDATA[ Jurnal Ilmu Komputer dan Sistem Informasi Vol 10, No 1 (2022): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI ]]>
Publisher : <![CDATA[Fakultas Teknologi Informasi Universitas Tarumanagara ]]>
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DOI: 10.24912/jiksi.v10i1.17823
<![CDATA[Advances in technology today, so that human work can be helped easily by using machines. One of the jobs that can be time-consuming is supervising. The supervision carried out requires human labor to oversee the events and activities recorded on CCTV cameras. With the development of technology, conducting surveillance is now easier. By utilizing video recordings containing activities, the design made can produce a program that can detect Sitting, Standing, Studying, Raising Hands, and Clapping activities. These detections can then be summarized into an activity logbook along with the time the activity occurred. The system is made using Python and the You Only Look Once (YOLO) method. The program is expected to be able to accurately detect activities with the specified classes. The results show that the YOLO method can find objects and their activities using the internet dataset and IP Camera dataset which produces the highest mean Average Precision (mAP) of 86.85% for the internet dataset and 99.96% for the IP Camera dataset. And the test results on the best model show an accuracy rate of 80.6% for the internet dataset and 98% for the IP Camera dataset.]]>
<![CDATA[CUSTOMER RELATIONSHIP MANAGEMENT MENGGUNAKAN METODE LEAST SQUARE DAN RFM K-MEANS BERBASIS WEBSITE ]]>
<![CDATA[Gabriel Ivan Setyaputra]]>;
<![CDATA[Bagus Mulyawan]]>;
<![CDATA[Manatap Dolok Lauro]]>
<![CDATA[ Jurnal Ilmu Komputer dan Sistem Informasi Vol 10, No 1 (2022): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI ]]>
Publisher : <![CDATA[Fakultas Teknologi Informasi Universitas Tarumanagara ]]>
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DOI: 10.24912/jiksi.v10i1.17835
<![CDATA[Persaingan di dunia bisnis semakin ketat dalam persaingannya, yang membuat tiap perusahaan berniat keras untuk menciptakan strategi bisnis yang bisa bersaing dengan tekanan kompetitor. Melihat kenyataan yang ada, dengan adanya kemajuan teknologi yang semakin pesat maka aplikasi Customer Relationship Management dapat menjadi solusi dalam memelihara hubungan yang baik dengan pelanggan.Aplikasi CRM ini dibuat sebuah fitur peramalan pendapatan sales tahunan yang dapat membantu perusahaan dalam menentukan strategi bisnis kedepannya. Perlu digaris bawahi bahwa proyeksi atau prediksi pendapatan harus berdasarkan kebenaran fakta yang diambil dari data penjualan dari masa lalu sehingga data yang di prediksi adalah data yang baik dan akurat. Dalam aplikasi yang dibuat saat ini, metode yang akan digunakan adalah metode Forecasting Least Square. Dari hasil Mean Absolute Percentage Error (MAPE) rata-rata error sebesar 19.27% berdasarkan data 2015 – 2018 untuk memprediksi tahun 2019-2020.juga dibuat sebuah fitur klustering yang bertujuan untuk mengelompokkan data setiap pelanggan dalam waktu per tahun ke dalam model Recency, Frequency dan Monetary Value dengan metode K-Means. Dari hasil perhitungan diperoleh nilai Davies Bouldin-Index (DBI) sebesar 0.410372 yang dapat disimpulkan bahwa klustering terhadap pelanggan terbentuk dengan baik.]]>
<![CDATA[KAJIAN TENTANG APLIKASI MOBILE INTERFACE PENCARIAN CITRA PADA BASIS DATA ONLINE BERBASIS iOS ]]>
<![CDATA[Daniel Antineus]]>;
<![CDATA[Lina Lina]]>;
<![CDATA[Agus Budi Dharmawan]]>
<![CDATA[ Jurnal Ilmu Komputer dan Sistem Informasi Vol 2, No 2 (2014): Jurnal Ilmu Komputer dan Sistem Informasi ]]>
Publisher : <![CDATA[Fakultas Teknologi Informasi Universitas Tarumanagara ]]>
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DOI: 10.24912/jiksi.v2i2.3198
<![CDATA[The use of the mobile phone as an information retrieval system nowadays has become a frequently performed task. Mobile phone that is easy and practical to carry anywhere, lightweight and with advanced technology makes the device more efficient to use than a desktop or a laptop. On these basis, we designed a simple application to recognize objects using the image histogram method for helping people especially to those affected by Alzheimer ,Aphasia, and those who are computer illiterate. This application is made using XCode with Objective-C programming language. The application is built in the iOS platform used on the mobile device technology company Apple, the iPhone. Key words Image Histogram, iOS, Xcode, Objective-C, Object, iPhone.]]>
<![CDATA[PENGENALAN WAJAH PEGAWAI KANTOR DENGAN MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK BERBASIS ANDROID ]]>
<![CDATA[Harry Chandra]]>;
<![CDATA[Lina]]>
<![CDATA[ Jurnal Ilmu Komputer dan Sistem Informasi Vol. 10 No. 2 (2022): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI ]]>
Publisher : <![CDATA[Fakultas Teknologi Informasi Universitas Tarumanagara ]]>
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DOI: 10.24912/jiksi.v10i2.22530
<![CDATA[Face is one of the elements used to identify identity between humans. The purpose of making this thesis is as a basic basis for developing an attendance system and making artificial intelligence that can identify humans through their faces. How to do data processing, the data taken comes from a video of office employees which lasts approximately 10 seconds. To make a program that can recognize the faces of office employees, the Convolutional Neural Network (CNN) method is used which will be trained to be able to distinguish each unique feature on the face to distinguish and recognize humans specifically. In performing facial recognition, office employees can provide input in the form of facial photos of office employees who have been trained and use the camera on a smartphone to perform face recognition directly. The faces of office employees used as targets for this CNN training came from Pt Eternal Indonesia, Faculty of Information Technology, Tarumanagara University, and Kekar Clinic. The output of the application is the accuracy of each photo of the office employee's face given. The results of the confusion matrix test show that the trained model has an accuracy of 80.39%, a precision of 80%, a recall of 80%, and an f1-score of 80%.]]>
<![CDATA[Pendeteksian Masker dan Klasifikasi Masker Menggunakan Metode Region-Based Neural Network ]]>
<![CDATA[Syawal Ludin]]>;
<![CDATA[Chairisni Lubis]]>;
<![CDATA[Teny Handhayani]]>
<![CDATA[ Jurnal Ilmu Komputer dan Sistem Informasi Vol. 10 No. 2 (2022): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI ]]>
Publisher : <![CDATA[Fakultas Teknologi Informasi Universitas Tarumanagara ]]>
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DOI: 10.24912/jiksi.v10i2.22532
<![CDATA[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.]]>
<![CDATA[Aplikasi Bimbingan Belajar Bahasa Inggris Tingkat Sekolah Dasar (SD) Dengan Fitur Live Chat Dan Automatic Essay Scoring ]]>
<![CDATA[Destu Adiyanto]]>;
<![CDATA[Viny Christanti Mawardi]]>;
<![CDATA[Manatap Dolok Lauro]]>
<![CDATA[ Jurnal Ilmu Komputer dan Sistem Informasi Vol. 10 No. 2 (2022): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI ]]>
Publisher : <![CDATA[Fakultas Teknologi Informasi Universitas Tarumanagara ]]>
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DOI: 10.24912/jiksi.v10i2.22533
<![CDATA[In the current pandemic, parents want to do additional learning for their children. Therefore, a research was conducted with the title of Application of English Tutoring for Elementary School Level (SD) with Live Chat and Automatic Essay Scoring features and is expected to help the learning carried out by teachers and students. The hope of this application can be useful and can make it easier for teachers to find places to do learning. The system created today is a scoring system in the form of an essay where when students solve problems in the current system it will produce points per question worked on and the total points will produce the correct number of points. Experiments were carried out with several students with several similar questions to find out whether the designed system worked as expected or not. By conducting three trials on students with the same 10 questions and with K-Gram 3, 4 and 5. 4 which was carried out, the results were 70% and for the accuracy results from the K-Gram 5 experiments carried out, the results were 65%.]]>
<![CDATA[PERBANDINGAN K-MEANS DAN K-MEDOIDS UNTUK KLASTERING TINGKAT STRES PADA MANUSIA ]]>
<![CDATA[Arya Triansyah]]>;
<![CDATA[Dyah Erny Herwindiati]]>;
<![CDATA[Janson Hendryli]]>
<![CDATA[ Jurnal Ilmu Komputer dan Sistem Informasi Vol. 10 No. 2 (2022): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI ]]>
Publisher : <![CDATA[Fakultas Teknologi Informasi Universitas Tarumanagara ]]>
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DOI: 10.24912/jiksi.v10i2.22534
<![CDATA[Society is faced with various problems as a result of progress and development of the times. Things in social relationships and demands from an expectation in achievement but not being met, from these inability and demands can cause stress in a person. Stress is the body's response caused by demands from outside the individual that exceed the ability to meet the demands to overcome and resolve the problem. The need to respond and manage stress well so that the quality of life becomes better, with clustering it can make it easier to group data. The clustering technique used is the K-Means and K-Medoids methods which partition the data into clusters. Comparison of cluster results used the use of a covariance matrix. So that in the comparison of the K-Means method k=2 and k=3, the best one is k=3 because the determinant of the covariance matrix is smaller, namely -1.4709e-11. In the comparison of the K-Medoids method k=2 and k=3, the best one is k=3 because the determinant of the covariance matrix is smaller, namely -1.4285e-11. Continued comparison of the two methods, namely K-Means and K-Medoids, the best is K-Medoids with a smaller covariance determinant than K-Means.]]>
