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All Journal Jutech: Jurnal Teknologi Informasi Jurnal Sistem Informasi
Diana Yusuf
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Computer Science & IT Decision Sciences, Operations Research & Management

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Journal : Jurnal Sistem Informasi

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Penerapan Data Mining Untuk Memprediksi Pembelian Mobil Bekas Menggunakan Algoritma Naïve Bayes Diana Yusuf
Jurnal Sistem Informasi (JUSIN) Vol 4 No 1 (2023): Jurnal Sistem Informasi
Publisher : ITB Ahmad Dahlan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32546/jusin.v4i1.2070

Abstract

Database can also be interpreted as a data warehouse. The amount of data collected in the database can be processed to generate valuable knowledge for science. One popular and widely used technique for processing databases is data mining. Data mining is the process of extracting knowledge from large and complex data warehouse. Data mining encompasses various algorithm to generate knowledge, one of which is naïve bayes. The dataset used in this research, employing the naïve bayes algorithm, consists of attributes relevant to the purchase of used cars, such year, transmission, mileage, car condition, and brand. This research aims to produce patterns and additional knowledge for participants in the used car business to identify the supporting factors in purchasing used cars.
RANCANGAN APLIKASI SPK PENENTUAN WALI KELAS BERDASARKAN PRESTASI GURU DENGAN METODE AHP PADA SMK JAKARTA BARAT 1 Sundari, Yola; shevti Arbekti Arman; Diana Yusuf
Jurnal Sistem Informasi (JUSIN) Vol 5 No 1 (2024): Jurnal Sistem Informasi
Publisher : ITB Ahmad Dahlan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32546/jusin.v5i1.2136

Abstract

A decision support system (DSS) is the definition of a procedural model of data processing and assisting management in making decisions. Computer-based decision support systems can improve decision-making ability to solve problems that appear structured or unstructured. The Analytical Hierarchy Process (AHP) method can be used to solve the DSS problem. This method is one of the most sought-after optimal solutions among several other decision support system method options. The research was conducted at SMKN 1 West Jakarta which aimed to assist the school in selecting homeroom teachers based on the effectiveness of teachers in the learning process to students. The creation of this application is done through data collection, system design, system analysis and database design. The creation of this application program is developed using PHP, the database is MySQL. In running this application, input or alternative information is needed, namely the names of teachers, and the assessment criteria are professional values, pedagogic values, personality values, and social values. The process requirements needed are alternative data entry process, teacher data entry process and also criteria data. The result is a teacher report that is expected to help the principal to determine homeroom based on teacher achievement scores.
RANCANG BANGUN APLIKASI DATA MINING DENGAN ALGORITMA FP-GROWTH PADA DATA PENJUALAN SPAREPART MOBIL SUZUKI RADIO DALAM Qonita Adinda Putri; Diana Yusuf; R.Tommy Gumelar
Jurnal Sistem Informasi (JUSIN) Vol 4 No 2 (2023): Jurnal Sistem Informasi
Publisher : ITB Ahmad Dahlan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32546/jusin.v4i2.2143

Abstract

Suzuki Radio Dalam is an automotive company operating in the automotive sector. They have been facing a challenge where sales data of spare parts has been accumulating without being effectively utilized or managed. The company has never employed data mining techniques to extract meaningful patterns or insights from this spare parts sales data. To address these issues, the researchers adopted the data mining technique known as the FP-Growth algorithm. The FP-Growth algorithm is a form of association algorithm within data mining. Association algorithms are utilized to uncover relationships and connections between variables present in a dataset. Through the application of the FP-Growth algorithm, data can be extracted through the construction of FP-Trees, which reveals insights into patterns of items purchased by customers. This method allows for the identification of frequently co-purchased items, enabling the company to devise marketing strategies aimed at boosting spare parts sales. The proposed solution involves creating a web-based platform to facilitate the FP-Growth algorithm calculations, particularly when dealing with large volumes of data. This web-based system was developed using PHP and utilizes a MySQL database. This data is then subjected to FP-Growth algorithm calculations and subsequently analyzed to generate association rules. These association rules hold valuable information about customer purchasing patterns. The implementation of this web mining solution streamlines the FP-Growth algorithm calculations, making it more manageable and efficient when dealing with substantial datasets. The resulting association rules derived from these calculations provide actionable insights for Suzuki's marketing strategies. By offering enticing promotions to customers based on the information gleaned from these association rules, the company aims to enhance spare parts sales.
Co-Authors Aldin Tegar Wahyudi Elliya Sestri Fahrul Razi Fahrul Razi Giawa, Amonio Qonita Adinda Putri R. Tommy Gumelar R.Tommy Gumelar Reynaldi, Reza Riska Sulistiani Saputri, Sheren Tasyana Shevti Arbekti Arman Sundari, Yola Syamsu, Muhajir Toha, Muhamad Toha Vany Terisia