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All Journal Teknosains: Media Informasi Sains dan Teknologi Jurnal Sisfokom (Sistem Informasi dan Komputer) Journal of Embedded Systems, Security and Intelligent Systems
Indasari, Sri Suci
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Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Physics

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ANALISIS SISTEM PENGELOLAAN DATA ALUMNI JURUSAN SISTEM INFORMASI UIN ALAUDDIN MAKASSAR BERBASIS WEB MENGGUNAKAN FRAMEWORK CODEIGNITER Yusuf, Farida; Akib, Faisal; Indasari, Sri Suci
Teknosains Vol 13 No 2 (2019): JULI
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/teknosains.v13i2.9653

Abstract

Alumni merupakan aset dari suatu institusi pendidikan yang harus dirangkul dan dikembangkan sedini mungkin. Kualitas alumni menunjukkan kualitas dari institusi pendidikan tersebut. Peran alumni antara lain sebagai katalis untuk memberikan berbagai masukan membangun kepada almamater dan diharap mampu mengembangkan jaringan serta membangun pencitraan inistitusi diluar. Kondisi saat ini, relasi antara institusi pendidikan dan alumni belum terjalin dengan baik. Institusi pendidikan dalam hal ini pihak Jurusan Sistem Informasi UIN Alauddin Makassar belum mempunyai pendataan secara menyeluruh terkait informasi alumni. Sehingga, pihak Jurusan Sistem Informasi belum mengetahui tolok ukur pencapaian alumni di dunia kerja setelah lulus di kampus UIN Alauddin Makassar. Karena masalah tersebut, peneliti bertujuan untuk merancang sistem pengelolaan data alumni pada Jurusan Sistem Informasi UIN Alauddin Makassar sebagai pendukung pendataan alumni dan berbagi informasi terkait lowongan pekerjaan serta kegiatan alumni.Jenis penelitian yang digunakan pada penelitian ini adalah deskriptif kualitatif yaitu memahami kondisi yang terlah terjadi. Sedangkan, metode pengumpulan data yaitu observasi, wawancara dan Library Research. Metode perancangan aplikasi yang digunakan pada penelitian ini adalah metode waterfall dan Unified Modeling Language (UML). Sedangkan, tekhnik pengujian yang digunakan oleh penulis adalah pengujian Black Box.Hasil dari penelitian berupa aplikasi website sebagai salah satu media komunikasi dan informasi antara alumni Jurusan Sistem Informasi dengan pihak akademik Jurusan Sistem Informasi. Berdasarkan pengujian dapat disimpulkan bahwa sistem ini berjalan sesuai dengan tujuan yang diharapkan.
Automatic Categorization of Multi Marketplace FMCGs Products using TF-IDF and PCA Features Indasari, Sri Suci; Tjahyanto, Aris
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 12, No 2 (2023): JULI
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i2.1621

Abstract

The use of technology in line with the increasing number of internet users has caused a shift in the product sales ecosystem to the realm of electronic commerce (electronic commerce). A total of 73.23 customers made purchase transactions using e-commerce and the most purchased products were products classified as Fast Moving Consumer Goods (FMCGs). The increasingly varied FMCGs data coupled with the increasing number of marketplaces is felt to need to be broken down into specific groups. The process is carried out by analyzing e-commerce product information, especially product names, and descriptions. In this study, we propose an automatic categorization of multiple marketplaces using data from multiple marketplaces. Data text is converted into structured data with a series of preprocessing, and comprehensive experiments are carried out to see the extraction performance of variables including TF-IDF, BOW, and N-Gram.  All three methods are used to validate text data sets with K-Means grouping results used with the help of PCA to reduce data dimensions.  The results show that the performance of the TF-IDF algorithm with a dimension reduction value of 70 and the use of Python can provide optimal results for the percentage of grouping data.
Comparison of Efficiency 3D Rendering Methods for Augmented Reality: A Case Study of SRP, URP, and Light Estimation on a Mobile Device Indasari, Sri Suci; Achmad Zulfajri Syaharuddin; Nurhikmayana Janna; Irmawati
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 2 (2025): June 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v6i2.8400

Abstract

This study examines the efficiency of 3D rendering methods in the development of Augmented Reality (AR) applications, which significantly impact visual quality, response speed, and device resource consumption. The main objective of this research is to analyze and compare three commonly used rendering methods in AR development: Standard Render Pipeline (SRP), Universal Render Pipeline (URP), and Light Estimation. Data collection was conducted through the implementation of an AR prototype application featuring two 3D objects (Earth and Mars), followed by testing the render latency for each method. The results showed that all three methods produced the same latency time of 0.03 seconds on a high-specification device. These findings suggest that, under the given testing conditions, the choice of rendering method has no significant impact on rendering latency. However, overall efficiency may still be influenced by other factors such as lighting conditions, hardware specifications, and marker quality.
Automatic Categorization of Multi Marketplace FMCGs Products using TF-IDF and PCA Features Indasari, Sri Suci; Tjahyanto, Aris
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 12 No. 2 (2023): JULI
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i2.1621

Abstract

The use of technology in line with the increasing number of internet users has caused a shift in the product sales ecosystem to the realm of electronic commerce (electronic commerce). A total of 73.23 customers made purchase transactions using e-commerce and the most purchased products were products classified as Fast Moving Consumer Goods (FMCGs). The increasingly varied FMCGs data coupled with the increasing number of marketplaces is felt to need to be broken down into specific groups. The process is carried out by analyzing e-commerce product information, especially product names, and descriptions. In this study, we propose an automatic categorization of multiple marketplaces using data from multiple marketplaces. Data text is converted into structured data with a series of preprocessing, and comprehensive experiments are carried out to see the extraction performance of variables including TF-IDF, BOW, and N-Gram.  All three methods are used to validate text data sets with K-Means grouping results used with the help of PCA to reduce data dimensions.  The results show that the performance of the TF-IDF algorithm with a dimension reduction value of 70 and the use of Python can provide optimal results for the percentage of grouping data.
Co-Authors Achmad Zulfajri Syaharuddin Akib, Faisal Aris Tjahyanto Irmawati Nurhikmayana Janna Yusuf, Farida