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.
Articles
937 Documents
<![CDATA[Clustering Data Covid-19 Di Indonesia Menggunakan Intelligent K-Means ]]>
<![CDATA[Veri]]>;
<![CDATA[Dyah Erny Herwindiati]]>;
<![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.v10i2.22535
<![CDATA[Indonesia pada terkena dampak wabah baru yakni virus covid-19. Covid-19 telah menjadi pandemi dikarenakan jumlah kasus di Indonesia yang terkonfirmasi terus meningkat. Di Jurnal ini menggunakan metode Intelligent K-Means untuk clustering data covid-19 yang ada diindonesia. Setelah mendapatkan hasil kluster dari metode Intelligent K-Means hasil ini akan dibandingkan dengan hasil clustering yang dilakukan oleh pemerintah. Hasil evaluasi di jurnal ini menggunakan metode Silhouette yang di mana hasil ini evaluasi silhouette ini akan dibandingkan dengan metode K-Means.]]>
<![CDATA[PERANCANGAN SISTEM REKOMENDASI BUSANA H&M DENGAN CITRA DAN RIWAYAT TRANSAKSI ]]>
<![CDATA[Aditya Halimawan]]>;
<![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.v10i2.22537
<![CDATA[Sistem rekomendasi merupakan sebuah sistem yang digunakan untuk mengetahui produk apa yang mungkin dapat disukai oleh pelanggan. Sistem rekomendasi yang dibuat dapat menghasilkan output berupa citra gambar, sehingga pengguna dapat mengetahui produk apa saja yang ditawarkan oleh H&M. Pada perancangan ini digunakan 2 model, yaitu model Collaborative Filtering, dan model Convolutional Neural Network. Digunakan Collaborative Filtering dengan pendekatan matriks cosine similarity untuk mendapatkan prediksi gambar yang diambil dari riwayat transaksi pelanggan yang telah berbelanja. Untuk model Convolutional Neural Network, menggunakan arsitektur ResNet50 untuk dapat mengenali citra gambar yang diunggah oleh pengguna untuk dicari gambar produk busana H&M yang mempunyai ciri yang paling mirip. Pada akhir pengujian didapatkan tingkat akurasi untuk Collaborative Filtering dengan nilai MAPE sebesar 0,00652, dan model Convolutional Neural Network didapatkan tingkat akurasi sebesar 85,79%.]]>
<![CDATA[PENERAPAN METODE SUPPORT VECTOR MACHINE UNTUK ANALISIS SENTIMEN PADA ULASAN PELANGGAN HOTEL DI TRIPADVISOR ]]>
<![CDATA[Willyanto Wijaya]]>;
<![CDATA[Dyah Erny Herwindiati]]>;
<![CDATA[Novario Jaya Perdana]]>
<![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.v10i2.22538
<![CDATA[Indonesia is an archipelagic country that has very beautiful nature, in addition to the natural beauty of cultural diversity is also one of the factors Indonesia has a tourist attraction. One of the effects of Indonesia's natural beauty and cultural diversity can be seen from the increase in hotel occupancy rates. This hotel analysis system design uses training data and test data from the tripadvisor website. Tripadvisor is a website that focuses on tourism. on tripadvisor there are a lot of services offered ranging from transportation, lodging, travel experiences, and restaurants. One of the useful features of tripadvisor is the review column, this review column can be used to do research. visitor reviews from the tripadvisor comments column can be used as a value. to visualize and see people's emotions how the services provided by the hotel to visitors. The research phase starts from scrapping data from the triapadvisor review column, preprocessing data, word weighting, SVM, and evaluation with a confusion matrix. The data taken from the review column is done by web scraping technique. This study uses data from 3000 reviews from 15 hotels. The results of the classification will then be evaluated with a confusion matrix. The highest accuracy result will be used as a model for classification. the classification results will be displayed in the form of detailed tables and diagrams that describe the percentage of sentiment classification results.]]>
<![CDATA[PENDETEKSIAN JUMLAH PENUMPANG YANG MASUK BERDASARKAN CCTV PADA PINTU BUS DENGAN METODE YOLO ]]>
<![CDATA[Vincent Marcellino]]>;
<![CDATA[Viny Christanti Mawardi]]>;
<![CDATA[Novario Jaya Perdana]]>
<![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.v10i2.22539
<![CDATA[Salah satu cara untuk mengurangi kemacetan pada kota besar adalah dengan mengubah pola pikir masyarakat untuk lebih menggunakan kendaraan umum, kendaraan umum bus merupakan salah bentuk dari kendaraan umum. Namun kelebihan penumpang pada kendaraan umum merupakan permasalahan yang dapat ditemukan. Perancangan pendeteksian jumlah penumpang ini bertujuan untuk membantu melakukan perhitungan jumlah penumpang dari kendaraan umum menggunakan kamera, guna mendeteksi jumlah penumpang dalam kendaraan umum. Perancangan ini menggunakan algoritma YOLO (You Only Look Once), algoritma ini digunakan karena memiliki performa pendeteksian yang cepat pada skenario pendeteksian secara real-time. Perancangan ini menggunakan data berupa gambar yang telah dipecah dari video untuk kemudian digunakan sebagai data latih, data uji, dan data validasi. Setelah melakukan proses pengujian dengan 50 data video untuk pintu masuk dan pintu keluar, hasil yang didapatkan berupa 82% untuk tingkat akurasi perhitungan penumpang pada data video pintu masuk dan 72% untuk tingkat akurasi perhitungan penumpang pada data video pintu keluar.]]>
<![CDATA[PENERAPAAN GATED RECURRENT UNIT UNTUK PREDIKSI ZAT PENCEMAR UDARA ]]>
<![CDATA[Jasmine Kezia Halim]]>;
<![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.v10i2.22540
<![CDATA[Air pollution caused by air pollutant substances is one of the problems of great concern in big cities, including the city of Jakarta. On June 16, 2022, Jakarta has been named the city with the worst source of air pollution in the world. This of course makes the residents of Jakarta and its surroundings feel worried. The purpose of designing this system is to predict air pollutants in DKI Jakarta using the website-based Gated Recurrent Unit (GRU) method. Where the test results from the GRU method produce different predictive values. The MAPE evaluation resulted in good predictions using the GRU method for air pollutants of PM10, SO2, CO, and O3 types with an average MAPE value of less than 50%. However, there are quite bad results for the type of NO2 substance, because it produces a MAPE value of more than 50%. Meanwhile, in the RMSE evaluation, all air pollutants produced an average value of no more than 20% so that it can be said that the GRU method produces predictions that are quite accurate for predicting air pollutants in the DKI Jakarta area.]]>
<![CDATA[APLIKASI PENCARIAN PROPERTI DI JAKARTA DENGAN METODE ANALYTIC NETWORK PROCESS DAN TOPSIS ]]>
<![CDATA[Yagyu Munenori M.E.]]>;
<![CDATA[Viny Christanti Mawardi]]>;
<![CDATA[Novario Jaya Perdana]]>
<![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.v10i2.22542
<![CDATA[There have been several buying and selling applications that are intended to help bring together buyers, sellers, or agents in finding the house criteria needed. But there are still conditions where buyers find it difficult to find the house or property of their dreams. At the same time sellers are also difficult to find the right buyer. For that we need an application that can realize a search application with property recommendation features that can be used to find the best unit that suits their wishes. The methods used are the Analytic Network Process and TOPSIS methods. The ANP method is used because of the consideration of the interrelationships between elements at different levels. TOPSIS method is also used to be able to display more accurate results in terms of ranking. From the recommendation test, 90% of the 10 tests were obtained and the percentage result was 94.1% from 17 respondent tests. Based on these tests, it is known that the error occurred because the data was not found. The absence of property data in accordance with the Criteria can be caused by filling out invalid criteria and can also be caused by a lack of variation in property data.]]>
<![CDATA[Klasifikasi Kekuatan Struktur Beton Menggunakan Convolutional Neural Networks ]]>
<![CDATA[Johan Hartanto]]>;
<![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.v10i2.22543
<![CDATA[Concrete is one of the most important elements in building a building construction. Concrete is widely used because it has advantages compared to other construction materials. In addition, the development of concrete construction has increased rapidly compared to other constructions, especially in the way of making concrete to the technology and use of materials used. In its development, materials will increase so that experiments in the laboratory make the costs swell. Therefore, a research is proposed which is intended to help researchers as well as to provide a comparison of the use of the model used. The method used to classify will use the CNN model by producing output that will display the class categories on the variables that have been inputted. The test results on training data resulted in an accuracy of 86.04% and testing on test or validation data was 82.14% on the Adam optimizer and 83.25% on training data and 80.35% on test or validation data on RMSprop. After determining the model to be used, it is continued with the use of K-fold validation.]]>
<![CDATA[Perancangan Dashboard Penilaian Tim Merchandising PT. Astro Technologies Indonesia ]]>
<![CDATA[Deistata Majiore]]>;
<![CDATA[Wasino]]>;
<![CDATA[Tri Sutrisno]]>
<![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.v10i2.22545
<![CDATA[Companies in achieving a company's goals must understand the performance of each team in the company. In overcoming and supervising that each team has achieved a goal and has performed well, a dashboard is needed to provide information and also help a company achieve its goals in understanding and monitoring the performance of each team and its members. The dashboard is made using a UCD (User Centered Design) method, a method that focuses on user behavior as the basis for creating a system. With this method, the dashboard will become a monitoring, evaluation tool, and become a report for a merchandising team in meeting the needs of a company. By making this dashboard, it will be very easy for users to understand and assess the performance of existing members and teams and with the design of existing KPIs it can facilitate the assessment of members and the merchandising team.]]>
<![CDATA[SISTEM INFORMASI AKADEMIK SISWA BERBASIS WEBSITE PADA SMAN 1 NGABANG ]]>
<![CDATA[Ari Setiawan Susanto]]>;
<![CDATA[Ery Dewayani]]>;
<![CDATA[Tri Sutrisno]]>
<![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.v10i2.22546
<![CDATA[Information system for Sman 1 Ngabang to process academic of students this web-based and mobile web system can help schools in learning features. The web- based is well designed using the PHP programming language and for the database using MySQL and phpMyAdmin. For testing using the white box method. The method used in software development is Rapid Application Development. The results obtained are Sman 1 Ngabang uses a web-based to obtain information system data in the form of reports. Admin also has full data access to add, update, and delete existing data in the database.]]>
<![CDATA[PENENTUAN REKOMENDASI MATAKULIAH YANG BERPENGARUH DALAM DUNIA KERJA DENGAN C4.5 ]]>
<![CDATA[Rayvaldi Harvian]]>;
<![CDATA[Bagus Mulyawan]]>;
<![CDATA[Tri Sutrisno]]>
<![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.v10i2.22547
<![CDATA[Education is closely related to the world of work, so we need a system that helps provide an overview of the courses needed by the company. It is hoped that the application of course recommendations that have an effect on the world of work will attract many students who can work in accordance with the desired company and are ready to face competition in the world of work. This application is designed to aim to provide recommendations for courses that are influential in the world of work so that students who are running lectures can use this application to make it easier to get information about the courses needed by the desired company so that students have no difficulty in choosing courses that are influential in the world work. In providing course recommendations, a method is needed, namely using the C4.5 Algorithm to make decisions and this application is made using the Javascript programming language and uses the MongoDB database system. In testing the method, accuracy is needed using a confusion matrix with several test schemes and the highest level of accuracy is using 50% data training and 50% data testing with 80% accuracy. Based on the tests carried out, this application can assist students in making decisions to choose the required courses and see the minimum achievements that must be passed to be able to work on the desired job.]]>
