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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937 Documents
<![CDATA[PENERAPAN ALGORITMA C4.5 UNTUK KLASIFIKASI MAHASISWA PENERIMA BANTUAN SOSIAL COVID-19 ]]>
<![CDATA[Eugenius Edsel Barito]]>;
<![CDATA[Jap Tji Beng]]>;
<![CDATA[Desi Arisandi]]>
<![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.v10i1.17819
<![CDATA[Dengan adanya pandemi Covid-19 yang mempengaruhi kondisi sosial-ekonomi masyarakat, banyak mahasiswa yang berkuliah di Universitas Tarumanagara membutuhkan bantuan sosial agar dapat memenuhi kebutuhan hidup. Pembuatan aplikasi ini bertujuan untuk membantu melakukan proses klasifikasi mahasiswa Universitas Tarumanagara yang termasuk calon penerima bantuan sosial Covid-19. Karena terbatasnya jumlah bantuan yang dapat diberikan kepada mahasiswa maka dari itu akurasi data penerima bantuan sosial diperlukan agar penyaluran bantuan sosial dalam upaya mengatasi dampak pandemi Covid-19 bisa tepat sasaran sehingga para mahasiswa bisa mendapatkan bantuan secara adil. Parameter atau kriteria yang digunakan untuk klasifikasi mahasiswa penerima bantuan sosial Covid-19 adalah status kondisi finansial, Jumlah anggota keluarga, status kepemilikan tempat tinggal, Status pekerjaan kepala keluarga atau penanggung biaya hidup calon penerima bantuan, dan Status kesehatan calon penerima dan keluarganya terkait dengan Covid-19. Metode yang digunakan untuk mengolah data mahasiswa adalah pohon keputusan dengan Algoritma C4.5. Dengan mengumpulkan 500 data mahasiswa Universitas Tarumanagara digunakan 400 mahasiswa sebagai data pelatihaan dan 100 mahasiswa sebagai data pengujian dan hasil dari lima kali percobaan pengujian data tersebut menunjukkan bahwa aplikasi ini sudah berfungsi dengan baik dalam mengklasifikasi mahasiswa calon penerima bantuan sosial dengan rata-rata accuracy sebesar 89%, precision sebesar 90.16%, dan recall sebesar 83.27%.]]>
<![CDATA[PENGGUNAAN METODE SUPPORT VECTOR MACHINE UNTUK KLASIFIKASI SENTIMEN E-WALLET ]]>
<![CDATA[Bryan Filemon]]>;
<![CDATA[Viny Christanti Mawardi]]>;
<![CDATA[Novario Jaya Perdana]]>
<![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.v10i1.17824
<![CDATA[In Google Play Store there are lots of application ready to be explored and downloaded. Google Play Store is a place where many developers can sell applications that they have made. Apart from being a place for searching and downloading applications, Google Play Store can also be used to conduct a research. E-Wallet is one of a technological development that can be used to do many transactions. Doing transaction with e-wallet can be done anywhere you want. E-wallet in Indonesia is growing very rapidly especially in the present time where covid-19 is growing rapidly. This is one of the reasons why many people now using e-wallet for doing transcations. Many interesting promotions that were given is also one of the reason why people start using e-wallet. This research had the objective to visualize people’s emotion on e-wallet based on user opinion in Google Play Store. The research stage starts from scrapping data from Google Play Store, preprocessing data, classification with Support Vector Machine, evaluation with confusion matrix. Data were scrapped from google play store using google_play_scrapper API. This research uses OVO review of 500 data, DANA review of 500 data, LinkAja review of 500 data. The classification results will then be evaluated using a confusion matrix. The highest accuracy results will be used as a model for the classification stage. The classification results will be displayed in the form of tables and pie charts that describe the percentage results of sentiment classification.]]>
<![CDATA[KLASIFIKASI PENYAKIT MATA MENGGUNAKAN CNN ]]>
<![CDATA[William William]]>;
<![CDATA[Chairisni Lubis]]>
<![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.v10i1.17834
<![CDATA[The eye is one of the organs of the human senses, namely the sense of sight. Eyes has an important function in capturing visual information that is used for daily activities. Eye health is important because vision can't be replaced by anything.Previously, a doctor made a diagnosis of an eye disease using retinal fundus images. But it takes expertise and a long time. Therefore, a classification system was made using the Convolutional Neural Network (CNN). The CNN network is used to recognize the visual pattern of image pixels with minimal preprocessing.The variables used during testing are data and batch size for the CNN training process. The data variables consist of 50 images from each class which are reproduced using mirroring with a total of 1,000 images; 50 images from each class reproduced using rotation totaling 2,000 images; and 275 normal images, 55 diabetic images, 250 glaucoma images, 250 cataract images, and 170 hypertension images totaling 1,000 images. Batch size variables used were 25 and 32. After all models were tested, it was concluded that the model trained using 1,600 images and 32 batch size gave the best results, namely loss: 0.1228 and accuracy: 0.9100.]]>
<![CDATA[SCREENING REKSADANA DENGAN PERHITUNGAN ESTIMASI RETURN MENGGUNAKAN METODE ROI ]]>
<![CDATA[Bagus Mulyawan]]>;
<![CDATA[Manatap Dolok Lauro]]>;
<![CDATA[Hendrawan Cahyady]]>
<![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.v10i1.17838
<![CDATA[Aplikasi yang dibuat merupakan aplikasi untuk otomatisasi proses screening reksadana pada sebuah perusahaan. Perusahaan tersebut merupakan perusahaan yang bergerak didalam bidang pengelolaan dana pensiun. Aplikasi yang dibuat berfungsi untuk memudahkan pengguna dalam melakukan screening data instrument reksdana yang sangat banyak sehingga data menjadi tersentralisasi di dalam satu aplikasi. Aplikasi dibuat berbasis website menggunakan bahasa pemorgraman C#, untuk sistem basis data menggunakan SQL server, serta untuk tampilan menggunakan html,css dan boostrap. Aplikasi ini memudahkan pengguna melakukan screening reksdana hingga pembuatan laporan berdasarkan hasil screening.]]>
<![CDATA[Sistem Pengenalan Plat Nomor Kendaraan Menggunakan Mask RCNN dan CNN ]]>
<![CDATA[Anthony Mesakh]]>
<![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.v10i1.17852
<![CDATA[Plat nomor kendaraan adalah sebuah objek yang berfungsi sebagai tanda pengenal dari sebuah kendaraan. Plat nomor kendaraan dapat digunakan untuk mengidentifikasi sebuah kendaraan secara unik. Sistem yang dapat mengenali plat nomor kendaraan secara otomatis dapat digunakan dalam berbagai macam skenario. Misalnya untuk sistem parkir kendaraan dimana lama kendaraan berada di dalam lapangan parkir dapat ditentukan secara otomatis melalui waktu masuk dan keluar kendaraan. Ataupun pada sistem keamanan dimana plat nomor kendaraan seorang kriminal dapat dideteksi secara otomatis melalui sistem yang dapat memberitahu pihak berwenang secara otomatis. Untuk dapat mengembangkan sistem yang bisa mengenali plat nomor kendaraan secara otomatis, digunakan metode Mask R-CNN dan juga CNN.Dari 2 model program yang diuji, yaitu model cepat dan akurat, sistem mendapatkan tingkat akurasi 73,8% dan 74,2% untuk keseluruhan karakter dalam plat nomor. Hal ini juga merupakan peningkatan dari hasil penelitian sebelumnya dimana segmentasi karakter membutuhkan keadaan yang sangat spesifik agar bisa mendapatkan hasil yang baik[1].]]>
<![CDATA[ANALISIS KEPUASAN PENGGUNAAN APLIKASI SHOPEE MENGGUNAKAN ALGORITMA NAÏVE BAYES ]]>
<![CDATA[Gabriel Carvenita Triasis]]>;
<![CDATA[Desi Arisandi]]>;
<![CDATA[Tri Sutrisno]]>
<![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.v10i1.17857
<![CDATA[The Covid-19 pandemic that attacks the world's health conditions, including Indonesia, greatly affects daily life. The impacts include the need to maintain distance and avoid crowds, which forces people to reduce interactions between people. Therefore, people need other ways to be able to meet their daily needs. One alternative that can be done is to use e-commerce applications to conduct online transactions or also known as online shopping. It was reported on September 30, 2021 that shopee occupies the most superior e-commerce in Indonesia with the number of monthly visitors which currently reaches 93 million subscribers, followed by Tokopedia with 86 million subscribers and in third place with 35 million customers occupied by Bukalapak. Therefore, an analysis of satisfaction with the use of e-commerce applications with the Shopee case study will be carried out to determine the response from users to the applications that are declared the most desirable. The application will be made based on a website to make it easier to use and use the Naïve Bayes algorithm as the analysis method. The Naïve Bayes algorithm is one method that can classify data which in this case are comments from application users into three types of comments, namely positive, negative and neutral. The process that is run also includes a preprocessing task as raw data processing into ready-to-use data and a confusion matrix as a calculation of the accuracy of the resulting application. Testing of the application is carried out in two ways, namely using a confusion matrix using a system with 80% results and a user acceptance test with 94.8% results, namely very good predicate. From the analysis, it can be concluded that Shopee users are satisfied with the application used and the classification of user reviews using the Naïve Bayes Algorithm produces a fairly good accuracy.]]>
<![CDATA[SISTEM INFORMASI PENGOLAHAN DATAAKADEMIK SISWA BERBASIS WEB PADA SMA BUDI AGUNG ]]>
<![CDATA[Albert Albert]]>;
<![CDATA[Wasino Wasino]]>;
<![CDATA[Zyad Rusdi]]>
<![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.v10i1.17862
<![CDATA[The information system application program used by Budi Agung High School to process student academic data to store all school academic data so the data will be stored neatly in the database so it will be easy to access easily, quickly, precisely, and accurately. This website also has a decision support system that can helping schools in prospective scholarship program with the Simple Additive Weighting selection method. This website is well designed using PHP programming language and uses MySQL and phpMyAdmin as database. The testing using whitebox method. The method used in developing software is the Rapid Application Development method. The results obtained are SMA Budi Agung uses a website-based application program to obtain information about student data, teacher data, class data, announcement data, grade data, attendance data, and schedule data in the form of reports. Admin also has full access rights to add, update, and delete existing data in the database.]]>
<![CDATA[ANALISIS SENTIMEN TANGGAPAN MASYARAKAT TERHADAPBANTUAN SOSIALPEMERINTAH DI MASA PANDEMI COVID-19 PADA PLATFORM TWITTER ]]>
<![CDATA[Melani Asta Rosari]]>;
<![CDATA[Wasino Wasino]]>;
<![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.v10i1.17867
<![CDATA[The study was conducted to analyze public opinion about the government's efforts in overcoming the Covid- 19 pandemic by providing social assistance (bansos) in the form of goods, money and or services. Through social media Twitter with the topic of social assistance, the classification of positive, neutral or negative sentiments will be carried out. The results of this classification will reveal what social assistance topics are often discussed on Twitter. This classification process uses the Naive Bayes method and uses the RapidMiner application. The data used in this analysis process is 747 Twitter comment text data with a data collection time span from October to November. The classification process is supported by the Term Frequency-Inverse Document Frequency feature as the word weighting stage. This classification produces 2,382 word attributes or word vectors from 747 data, with 370 sample data for model testing which produces an accuration value of 24.32%, a true neutral recall value of 100%, and a true neutral precision value of 24.32%. The word that most often appears from the results of this sentiment analysis is the word "bantuan".]]>
<![CDATA[REKOMENDASI CALON KARYAWAN TETAP DI PERUSAHAAN J&T EXPRESS DENGAN METODE SIMPLE ADDTIVE WEIGHTING ]]>
<![CDATA[Prabu Alif Anggadiputra]]>;
<![CDATA[Viny Christanti Mawardi]]>;
<![CDATA[Tri Sutrisno]]>
<![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.v10i1.17794
<![CDATA[The definition of an expedition is the delivery of goods or a company that transports goods. Expeditions for shipping goods are now often found in Indonesia because of the large number of people who make transactions via online. There is a J&T Express expedition service which is one of the shipping services that is able to serve deliveries within cities, between cities and between provinces. J&T Express has problems in determining permanent warehouse employees. The determination of warehouse employees for permanent employees at J&T Express is still done individually by the Supervisor of each J&T Express branch. The Simple Additive Weighting method is one method to make it easier for Supervisors to choose permanent warehouse employees with rankings. The way it works is that the user selects the 7 criteria provided, namely performance, attendance, manners, appearance, ability, knowledge, and responsibility.]]>
<![CDATA[APLIKASI PERINGKASAN DOKUMEN MENGGUNAKAN METODE MAXIMUM MARGINAL RELEVANCE (MMR) ]]>
<![CDATA[Delvin Delvin]]>;
<![CDATA[Desi Arisandi]]>;
<![CDATA[Tri Sutrisno]]>
<![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.v10i1.17820
<![CDATA[making a summary application to help readers who do not like to read long and thick news articles which take a relatively long time and can cause readers to be lazy to read the news articles. This summary application is used to summarize news articles, in making the application using ASP.Net. In this summary, the Maximum Marginal Relevance (MMR) method is used. In this study, you can use articles on the website, and do it. Articles are processed in the form of a file (single document) with a txt extension. The summary process goes through the preprocessing stage, which consists of sentence segmentation, case folding, tokenizing, filtering, stemming.]]>
