Jurnal Sistem Informasi dan Ilmu Komputer
Jurnal Sistem Informasi dan Ilmu Komputer berfokus pada publikasi hasil penelitian, kajian konseptual, dan pengembangan keilmuan di bidang Sistem Informasi dan Ilmu Komputer. Jurnal ini bertujuan menjadi media diseminasi ilmiah bagi akademisi, peneliti, dan praktisi dalam pengembangan serta penerapan teknologi informasi yang inovatif dan berkelanjutan. Ruang Lingkup Ruang lingkup jurnal mencakup, namun tidak terbatas pada, topik-topik berikut: Bidang Sistem Informasi Analisis dan Perancangan Sistem Informasi Manajemen Sistem Informasi Sistem Informasi Manajemen Sistem Enterprise (ERP, SCM, CRM) Sistem Pendukung Keputusan Business Intelligence dan Data Warehouse Tata Kelola Teknologi Informasi Audit dan Keamanan Sistem Informasi E-Government dan E-Business Bidang Ilmu Komputer Rekayasa Perangkat Lunak Kecerdasan Buatan (Artificial Intelligence) Machine Learning dan Deep Learning Data Mining dan Big Data Jaringan Komputer dan Keamanan Jaringan Internet of Things (IoT) Pengolahan Citra dan Visi Komputer Sistem Terdistribusi dan Cloud Computing Human-Computer Interaction (HCI)
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169 Documents
<![CDATA[Optimasi Keuntungan Maksimum Dari Penjualan Seblak Dengan Menggunakan Metode Simpleks, Software POM-QM Dan Implementasi Rstudio ]]>
<![CDATA[ Jurnal Sistem Informasi dan Ilmu Komputer Vol. 1 No. 4 (2023): November : Jurnal Sistem Informasi dan Ilmu Komputer ]]>
Publisher : <![CDATA[International Forum of Researchers and Lecturers ]]>
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DOI: 10.59581/jusiik-widyakarya.v1i4.1657
<![CDATA[This article aims to optimize the profit of seblak business through the application of Simplex method in linear program. Seblak is a popular business today with a wide variety of toppings such as meatballs, sausages, noodles, feet and many more, but efficient production planning and resource allocation can be challenging. In calculating this profit optimization, we use the Simplex method to identify production combinations that can generate maximum profit by considering various constraints related to raw materials, processing time, production costs to product selling prices. The result is expected to help seblak business owners in making smarter decisions regarding production, inventory, and pricing strategies, thus improving their business profitability.]]>
<![CDATA[Menentukan Titik Rawan Malaria Di Provinsi Nusa Tenggara Timur Menggunakan Metode K-Means Clustering ]]>
<![CDATA[ Jurnal Sistem Informasi dan Ilmu Komputer Vol. 1 No. 4 (2023): November : Jurnal Sistem Informasi dan Ilmu Komputer ]]>
Publisher : <![CDATA[International Forum of Researchers and Lecturers ]]>
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DOI: 10.59581/jusiik-widyakarya.v1i4.1750
<![CDATA[Malaria is one of the diseases that is currently affected, but is still a threat and often causes unusual events in NTT province. Malaria in NTT province is the second highest malaria disease in Indonesia after Papua. The method used to analyze the vulnerability to malaria in NTT province is K-Means Clustering. The purpose of analyzing the level of malaria vulnerability is to find out which districts have the highest to lowest vulnerability in NTT province, which is carried out in a geographic information system. The results of the analysis showed tha 7 districts were classified as low malaria vulnerability, 1 district as medium, 12 districts as high and 2 districts as very high. The level of vulnerability can be understood as the level of malaria endemicity.]]>
<![CDATA[Visualisasi Data Kependudukan Daerah Kabupaten Tangerang Menggunakan Aplikasi Microsoft Power Bi. ]]>
<![CDATA[ Jurnal Sistem Informasi dan Ilmu Komputer Vol. 1 No. 4 (2023): November : Jurnal Sistem Informasi dan Ilmu Komputer ]]>
Publisher : <![CDATA[International Forum of Researchers and Lecturers ]]>
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DOI: 10.59581/jusiik-widyakarya.v1i4.1766
<![CDATA[Tangerang Regency is a district located in Banten Province, Indonesia. Tangerang Regency is divided into 29 sub-districts, 28 sub-districts and 246 villages. The Tangerang Regency Opendata Portal is a DKAN-based platform, which is a community-based, free and open-source open data platform that provides freedom for organizations and individuals to publish and consume structured information. The Tangerang Regency opendata portal provides datasets that are useful for local communities to find out various types of information such as economic, social, educational, health, population and so on. So that this data can be processed into valuable information, tools are needed to visualize these data so that they can display information about population datasets, these tools include Business Intelligence (BI) software. This research aims to provide a clear picture or visualization of population data for the Tangerang Regency area from 2019 to 2021. This research was conducted using the Microsoft Power BI application with stages of data collection, data entry, data modeling and data visualization. The results of this research are in the form of a dashboard/summary report and detailed reports regarding population data for Tangerang Regency. ]]>
<![CDATA[Sistem Informasi Pendukung Keputusan Pengadaan Armada Baru Pada PT. Jaya Sampurna Makmur Bekasi Berbasis Web Mengunakan Metode Weighted Product ]]>
<![CDATA[ Jurnal Sistem Informasi dan Ilmu Komputer Vol. 1 No. 4 (2023): November : Jurnal Sistem Informasi dan Ilmu Komputer ]]>
Publisher : <![CDATA[International Forum of Researchers and Lecturers ]]>
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DOI: 10.59581/jusiik-widyakarya.v1i4.1767
<![CDATA[Companies in making a decision require good consideration, therefore we need a system that helps provide information from good data processing so that it becomes the basis for decision making. This analysis aims to create a decision support system that can help the company to provide an overview of the decision to procure a new fleet that the company wants to buy.This decision support information system is implemented using the Hypertext Preprocessor (PHP) programming language and MySsql as the database application so that the desired features are created and neatly stored in operating the information system.This decision support information system also uses the Weighted Product method which is used to assist in decision making in determining the procurement of new fleets.The end result of this decision support information system is to combine a programming language with the Weighted Product method which can be used for decision making in determining which new fleet to buy, where the calculations are based on several predetermined criteria so that their use is on target.]]>
<![CDATA[Analisis Editing Video Broadcast Pada Acara Berita TVRI Sumatera Utara ]]>
<![CDATA[ Jurnal Sistem Informasi dan Ilmu Komputer Vol. 1 No. 4 (2023): November : Jurnal Sistem Informasi dan Ilmu Komputer ]]>
Publisher : <![CDATA[International Forum of Researchers and Lecturers ]]>
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DOI: 10.59581/jusiik-widyakarya.v1i4.1775
<![CDATA[. In the ever-growing information era, video editing has become an important part of television news production. This study investigates the use of video editing on TVRI North Sumatra news programs. This research focuses on the editing software used, the editing methods used, and how the use of this editing impacts the quality of news production. To gain a better understanding of video editing techniques at regional news stations, we conducted direct observations, interviews, and document analysis through qualitative research methods. The research results show that video editing at TVRI North Sumatra is carried out by professional programs. To improve the visual and audio quality of news broadcasts, adjustment techniques such as visual transitions, color adjustments, and sound effects are often used. In the use of broadcast video editing, issues such as limited time and resources are identified as important elements. Improved time management, more training for production teams, and more technical resources are recommended. In other words, this research provides a comprehensive analysis of video editing methods in TVRI North Sumatra news production. The results could improve the industry's understanding of video editing methods in regional news contexts and help develop more creative and high-quality news production methods.]]>
<![CDATA[Tingkat Kepuasan Mahasiswa Terhadap Pelayanan Akademik Diukur Dengan Data Mining C4.5 Menggunakan Metode Decision Tree Dan Naïve Bayes ]]>
<![CDATA[ Jurnal Sistem Informasi dan Ilmu Komputer Vol. 1 No. 4 (2023): November : Jurnal Sistem Informasi dan Ilmu Komputer ]]>
Publisher : <![CDATA[International Forum of Researchers and Lecturers ]]>
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DOI: 10.59581/jusiik-widyakarya.v1i4.1777
<![CDATA[The goal of this data mining C4.5 implementation is to improve student performance in academic coursework in the computer science department at Teknik Fakultas and Pancasakti University in Tegal. Use a limited number of dimensions to assess the following: nyata, jaminan, keandalan, empatia, dan bukti nyata. It is difficult to determine which quality standard has to be raised because the aforementioned kelima aspek cannot be changed in an objective manner. Utilizing the algorithm C4.5 method, the authors consider reducing the sample size to the point where the keputusan is reduced. After manual perhitungan, pembuktian is also carried out using an application called RapidMiner.The analysis's conclusions show that the most important factor in determining the mahasiswa's tingkat kepuasan is the style of teaching.]]>
<![CDATA[Analisis Perbandingan Keamanan Data Dan Privasi Pengguna Aplikasi Telemedisin Berdasarkan Hukum Indonesia: Halodoc Dan Alodokter ]]>
<![CDATA[ Jurnal Sistem Informasi dan Ilmu Komputer Vol. 1 No. 4 (2023): November : Jurnal Sistem Informasi dan Ilmu Komputer ]]>
Publisher : <![CDATA[International Forum of Researchers and Lecturers ]]>
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DOI: 10.59581/jusiik-widyakarya.v1i4.1789
<![CDATA[This research was conducted to obtain information regarding data security and privacy of users of digital health applications, Halodoc and Alodokter, based on legal regulations in Indonesia. The method used is a qualitative method through sources such as literature reviews, journals, scientific works and other media, as well as a quantitative method through calculating the level of conformity of regulations on applications with applicable laws and regulations. The results obtained in both applications are that data security and user privacy are met by seven out of ten indicators, and both make their best efforts to protect and secure their users' personal data, however there is no guarantee that the platform will be safe and reliable.]]>
<![CDATA[Pembuatan User Interface Aplikasi Berbasis Website K-Foodies ]]>
<![CDATA[ Jurnal Sistem Informasi dan Ilmu Komputer Vol. 1 No. 4 (2023): November : Jurnal Sistem Informasi dan Ilmu Komputer ]]>
Publisher : <![CDATA[International Forum of Researchers and Lecturers ]]>
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DOI: 10.59581/jusiik-widyakarya.v1i4.1793
<![CDATA[The User Interface (UI) of the website-based application 'K-Foodies' was created to provide information on Korean street food recipes with an attractive appearance and is easy to use. In the context of the popularity of Korean street food in Jakarta and people's interest in cooking themselves, the difficulty in finding scattered recipe information is an obstacle. Creating the UI involved using Figma software, with a focus on UI design and user experience. The UI design includes descriptions of Korean street food, recipes, and cooking steps. Usability tests using the completion rate method will measure the effectiveness of the UI based on user interactions with the system in the form of various task scenarios. The aim of this research is to create an attractive and easy-to-use UI for the 'K-Foodies' application, allowing users to easily find Korean street food recipes in one place.]]>
<![CDATA[Implementasi Algoritma Decision Tree untuk Klasifikasi Data Evaluation Car Menggunakan Python ]]>
<![CDATA[ Jurnal Sistem Informasi dan Ilmu Komputer Vol. 1 No. 4 (2023): November : Jurnal Sistem Informasi dan Ilmu Komputer ]]>
Publisher : <![CDATA[International Forum of Researchers and Lecturers ]]>
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DOI: 10.59581/jusiik-widyakarya.v1i4.1830
<![CDATA[Di era digital saat ini, kemajuan teknologi informasi mengalami pertumbuhan yang pesat. Salah satu perkembangan yang signifikan terjadi dalam bidang kecerdasan buatan (Artificial Intelligence), yang telah diterapkan luas di berbagai sektor, termasuk analisis data dan pengambilan keputusan. Para peneliti di bidang data mining telah menciptakan beragam algoritma klasifikasi yang meningkatkan proses klasifikasi dengan memanfaatkan atribut numerik dan nominal. Klasifikasi adalah suatu proses analisis data yang menghasilkan model untuk mewakili kelas-kelas dalam data tersebut, seperti yang terjadi pada Decision Tree yang digunakan untuk menganalisis klasifikasi dan pola prediksi data serta menggambarkan hubungan antara variabel atribut dan variabel target dalam bentuk struktur pohon. Python, sebagai bahasa pemrograman populer dalam pengembangan kecerdasan buatan, menyediakan pustaka dan framework yang mendukung implementasi algoritma Decision Tree. Dengan menerapkan algoritma Decision Tree untuk klasifikasi data evaluasi mobil menggunakan Python, kita dapat memanfaatkan kekuatan AI untuk memberikan solusi efektif dan efisien dalam pengambilan keputusan terkait evaluasi mobil. Menggunakan dataset Evaluation Car dari UC Irvine Machine Learning Repository, hasil penelitian menunjukkan akurasi sebesar 81%. Confusion Matrix dan laporan klasifikasi menunjukkan performa model yang baik dalam melakukan prediksi.]]>
<![CDATA[Penerapan Algoritma Decision Tree Dalam Melakukan Analisis Klasifikasi Harga Handphone ]]>
<![CDATA[ Jurnal Sistem Informasi dan Ilmu Komputer Vol. 1 No. 4 (2023): November : Jurnal Sistem Informasi dan Ilmu Komputer ]]>
Publisher : <![CDATA[International Forum of Researchers and Lecturers ]]>
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DOI: 10.59581/jusiik-widyakarya.v1i4.1861
<![CDATA[The use of the Decision Tree method in smartphone price classification is the focus of this study. By using the 10 most relevant features and data normalization to achieve scale consistency, the Decision Tree algorithm delivers an average accuracy of 81%. Although some false positives and false negatives occur, the model is able to classify smartphone prices well, especially in identifying low and high prices. These results provide important insights into the features that affect smartphone prices. While there is still room for improvement, this model provides a solid foundation for the smartphone industry to determine prices based on certain specifications. The importance of relevant feature selection and data normalization was revealed in this study. Despite the accuracy reaching 81%, improvements in the classification of medium and high price classes are still possible to reduce prediction errors. This method provides an important basis for the smartphone industry to set prices based on specifications, and data mining techniques such as Decision Tree can be improved to improve the accuracy of future price predictions.]]>
