Article Per Year (5 Year)
p-Index From 2020 - 2025
2.064
P-Index
This Author published in this journals
All Journal Communications in Science and Technology JMBI UNSRAT (Jurnal Ilmiah Manajemen Bisnis dan Inovasi Universitas Sam Ratulangi) YUME : Journal of Management Jurnal Pengabdian kepada Masyarakat Nusantara Global Abdimas: Jurnal Pengabdian Masyarakat Teknik: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Inspiration: Jurnal Teknologi Informasi dan Komunikasi Jurnal MediaTIK
Aras, Rezty Amalia
Institut Teknologi Dan Bisnis Kalla
Agriculture, Biological Sciences & Forestry Automotive Engineering Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Public Health Social Sciences Transportation Other

Published : 13 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 13 Documents
Search

 1   2 
FAKTOR KEBERHASILAN START-UP DI MAKASSAR Aras, Rezty Amalia; Sucipto, Kiki Resky Ramdhani; Sari, Emmy Puspita
JMBI UNSRAT (Jurnal Ilmiah Manajemen Bisnis dan Inovasi Universitas Sam Ratulangi). Vol 8, No 3 (2021): JMBI UNSRAT Volume 8 Nomor 3
Publisher : FEB Universitas Sam Ratulangi Manado

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35794/jmbi.v8i3.36757

Abstract

Perkembangan teknologi yang sangat cepat berdampak pada pertumbuhan ekonomi, berbagai macam bisnis rintisan atau seringkali disebut dengan start-up khususnya di bidang teknologi. Start-up adalah model bisnis baru yang menciptakan ekonomi nilai-nilai dan jalur karir bagi generasi muda, khususnya yang tertarik pada inovasi dan teknologi dan melihat peluang bisnis di peneliti start-up teknologi di bidang start-up. Menurut catatan situs forbes.com 90% start-up yang diciptakan di dunia gagal. Banyak alasan mengapa start-up gagal, diantaranya salah memprediksi kebutuhan pasar, konflik internal, kehabisan dana dan ketidakharmonisan tim serta pola perusahaan yang buruk. Oleh karena itu, diperlukan analisis strategi bisnis e-commerce Perusahaan Start-up Digital di Makassar. Tujuan penelitian ini adalah untuk menganalisis strategi bisnis e-commerce perusahaan start-up digital di Makassar. Penelitian ini merupakan penelitian kualitatif yang dilaksanakan di Makassar Provinsi Sulawesi Selatan dengan tujuan untuk mengetahui faktor keberhasilan start-up yang berada di Makassar. Subjek dari penelitian ini adalah para CEO atau orang yang memiliki peran inti dalam start-up. Pengumpulan data dilakukan untuk memperoleh informasi yang dibutuhkan dalam rangka mencapai tujuan penelitian. Pengumpulan data dilakukan dengan wawancara mendalam (indephth interview), dengan mewawancarai CEO atau orang yang memiliki peran inti dalam start-up. Faktor keberhasilan start-up di Makassar seperti Digides, Clean up, Octopus, Mall Sampah dan Helper yang paling mempengaruhi adalah penentuan tim, ide yang cemerlang, timing yang tepat, model bisnis dan kemudian funding juga menjadi faktor pendukung sebuah start-up.
Analisis Pola Lelang di Ebay Menggunakan Metode K-Means Clustering Rezty Amalia Aras; Ilna Nardiyah
Jurnal MediaTIK Volume 7 Issue 2, Mei (2024)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Platform lelang daring telah menjadi aspek penting dalam perdagangan elektronik, yang menghadirkan peluang besar bagi analisis pola perilaku pengguna. Dalam penelitian ini, kami melakukan analisis pola lelang di platform eBay menggunakan metode klastering K-Means. Data transaksi lelang dikumpulkan dan dianalisis untuk mengidentifikasi pola yang mungkin tersembunyi di dalamnya. Langkah-langkah pembersihan data dilakukan untuk memastikan kualitas data yang optimal. Setelah itu, metode K-Means diterapkan untuk mengelompokkan transaksi lelang berdasarkan karakteristik tertentu. Hasil klastering divisualisasikan untuk memberikan wawasan tentang kelompok-kelompok transaksi yang berbeda. Evaluasi hasil klastering dilakukan dengan mempertimbangkan metrik evaluasi seperti inertia dan Silhouette Score. Temuan dari analisis ini dapat memberikan pemahaman lebih dalam tentang perilaku pengguna dalam melakukan lelang di platform eBay.
MENJADI SMART DIGITALPRENEUR UNTUK GENERASI MILLENIAL PADA SISWA SMA DI MAKASSAR Aras, Rezty Amalia; Rahmawati, Aulia; Afrizal, Yogi Hady; Salam, Muhammad Fachrul; Sucipto, Kiki Resky Ramdhani; Rijal, Syamsul; Juhri, Juhri
GLOBAL ABDIMAS: Jurnal Pengabdian Masyarakat Vol. 4 No. 1 (2024): Mei 2024, GLOBAL ABDIMAS
Publisher : Unit Publikasi Ilmiah Perkumpulan Intelektual Madani Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51577/globalabdimas.v4i1.513

Abstract

Di era digital yang terus berkembang, menjadi seorang digitalpreneur adalah tantangan menarik dan menjanjikan, terutama bagi generasi milenial. Siswa SMA yang memiliki keterampilan teknologi, kreativitas, dan semangat kewirausahaan, memiliki potensi besar untuk meraih kesuksesan dalam dunia bisnis digital. Kegiatan seminar "Smart Digitalpreneur untuk Generasi Z" bertujuan memberikan wawasan dan simulasi kepada siswa di Makassar. Melalui kegiatan ini, kami mencoba untuk menunjukkan pentingnya kreativitas dan pemahaman pasar dalam bisnis digital. Kegiatan ini juga mencoba untuk membuka pikiran peserta seminar melalui materi-materi yang disampaikan tentang bagaimana menyiapkan diri menjadi digitalpreneur yang cerdas dan inovatif, dengan hasil yang menunjukkan peningkatan pemahaman dan keterampilan peserta. Pelaksanaan PKM ini telah diikuti oleh 24 siswa dan mahasiswa dari sekolah dan perguruan tinggi di Makassar. Seminar dilakukan secara luring di Auditorium Institut Teknologi dan Bisnis Kalla. Hasil survei pasca-kegiatan menunjukan ketertarikan peserta pada kegiatan seminar ini.
COMPARISON OF DATA MINING CLASSIFICATION TECHNIQUES FOR HEART DISEASE PREDICTION SYSTEM Rezty Amalia Aras; Noor Akhmad Setiawan
Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol. 2 No. 2 (2022): Juli : Jurnal Teknik Mesin, Elektro dan Ilmu Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (789.232 KB) | DOI: 10.55606/teknik.v2i2.672

Abstract

DM is the process of analyzing data from different perspectives and gathering knowledge that can be used for different applications. Classification as one of the data mining techniques used to predict group membership. For example, the healthcare industry. DM provides a set of techniques for discovering hidden patterns from data. In this paper, we examine the heart disease dataset in order to obtain information or patterns that can be useful for making a decision. The test in this paper is a prediction of heart disease using three classification methods, namely OneR, decision tree and naive bayes. The results of this experiment show predictions from each experiment with different levels of prediction accuracy in each method used with 91.48% accuracy for the decision tree, 85.18% for naive Bayes and 76.3% for OneR.
Decision Support System (DSS) dengan Berorientasi -Solver Rezty Amalia Aras
Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol. 2 No. 1 (2022): Maret : Jurnal Teknik Mesin, Elektro dan Ilmu Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/teknik.v2i1.917

Abstract

A Decision Support System (DSS) or decision support system is part of a computer-based information system (including knowledge-based/knowledge management systems) that is used to support decision-making within an organization or company. can also be said as a computer system that processes data into information to make decisions on specific semi-structured problems. In this paper, we try to solve a simple DSS with Microsoft Excel by using Solver.
Implementation of Haar Cascade and Adaboost Algorithms in Photo Classification on Social Networks Rezty Amalia Aras; Hutami Endang
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol. 13 No. 1 (2023): Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Pusat Penelitian dan Pengabdian Pada Masyarakat Sekolah Tinggi Manajemen Informatika dan Komputer AKBA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35585/inspir.v13i1.45

Abstract

Instagram is one of the fastest social networks in recent years. Instagram is a popular social media for sharing images. For example, image searches on Instagram may use certain keywords, sometimes called hashtags. There are no rules for specifying hashtags when users upload images. As such, the specified hashtag may not be relevant to the uploaded image. There are photos whose content is dominated by selfies. The study was conducted using data from Instagram, using hashtags to refine searches. Next, classify from the search results. The survey has three categories: selfies, food, and travel. Results: Two of her classification algorithms, Haar Cascade and Adaboost, were used in this study. From the study results, we can conclude that the Haar cascade has a precision rate of 0.7081/s and a detection error of 0.8816/s, while Adaboost has a precision rate of 0.7072/s and a detection error of 0.8424/s. According to the recognition results, the two algorithms can recognize and classify photos with almost the same accuracy (only 0.0392 seconds).
User Segmentation Based on Purchasing Habits and Preferences on the Amazon Platform Using K-Means Clustering Al Isra Denk Rimakka; Aras, Rezty Amalia
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol. 13 No. 2 (2023): Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Pusat Penelitian dan Pengabdian Pada Masyarakat Sekolah Tinggi Manajemen Informatika dan Komputer AKBA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35585/inspir.v13i2.63

Abstract

As a large company, Amazon operates an online marketplace with a diverse user base exhibiting varied purchasing habits. This diversity challenges Amazon to provide tailored services and marketing strategies for each user with distinct characteristics. Therefore, this research aims to assist Amazon in segmenting its users based on their characteristics, enabling the implementation of targeted marketing strategies and service provision for each user. The study employs the K-Means Clustering method to segment Amazon platform users based on their purchasing behavior, site feature interactions, and preferences. The research process involves Knowledge Data Discovery (KDD) stages, including data processing, attribute selection, and applying the K-Means Clustering algorithm. The analysis results reveal five distinct user clusters, each with unique characteristics reflecting user behavior and preferences. These clusters depict variations in purchasing frequency, interactions with site features, and responses to product recommendations. This user segmentation provides valuable insights for Amazon to develop more focused marketing strategies, enhance personalized services, and improve overall customer satisfaction.
Segmentation of retinal blood vessels for detection of diabetic retinopathy: A review Aras, Rezty Amalia; Lestari, Tri; Nugroho, Hanung Adi; Ardiyanto, Igi
Communications in Science and Technology Vol 1 No 1 (2016)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.1.1.2016.13

Abstract

Diabetic detinopathy (DR) is effect of diabetes mellitus to the human vision that is the major cause of blindness. Early diagnosis of DR is an important requirement in diabetes treatment. Retinal fundus image is commonly used to observe the diabetic retinopathy symptoms. It can present retinal features such as blood vessel and also capture the pathologies which may lead to DR. Blood vessel is one of retinal features which can show the retina pathologies. It can be extracted from retinal image by image processing with following stages: pre-processing, segmentation, and post-processing. This paper contains a review of public retinal image dataset and several methods from various conducted researches. All discussed methods are applicable to each researcher cases. There is no further analysis to conclude the best method which can be used for general cases. However, we suggest morphological and multiscale method that gives the best accuracy in segmentation.
Towards The Future of Crab Farming: The Application Of AI with Yolox And Yolov9 To Detect Crab Larvae Zakiyabarsi, Furqan; Amalia Aras, Rezty; Dwi Nugroho H, Yabes; Muhaimin Nur, Muhammad; Aditya Alfarizi, Dimas; Ulil Amri, Muhammad
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol. 14 No. 2 (2024): Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Pusat Penelitian dan Pengabdian Pada Masyarakat Sekolah Tinggi Manajemen Informatika dan Komputer AKBA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35585/inspir.v14i2.93

Abstract

Crabs are a highly valued food source and a key export commodity for Indonesia, but farming them remains a challenge, particularly during the larval stage, where survival rates are critically low. This issue has contributed to the declining population of wild crabs. A crucial factor in improving survival rates is the accurate detection and counting of crab larvae. By determining the precise number of larvae, farmers can optimize feeding ratios, manage stocking densities to reduce cannibalism, maintain water quality, and improve cost efficiency through better resource management. Despite its importance, no affordable and precise tools currently exist for this purpose. This study aims to develop a cost-effective and accurate crab larvae detection and counting application using image processing powered by deep learning artificial intelligence (AI). Two models, You Only Look Once eXtreme (YOLOX) and YOLOv9, were evaluated for their performance. The YOLOX-S model struggled with accuracy in detecting larvae, whereas the YOLOv9 model demonstrated superior performance, achieving a mean Average Precision (mAP) of 0.85 at IoU=0.5 and successfully detecting 93% of crab larvae objects accurately. The findings of this research have significant implications for supporting Indonesia's blue economy and aligning with Sustainable Development Goals (SDGs), particularly in sustainable fisheries and aquaculture. By enabling a tech-driven approach to crab farming, this solution addresses the challenges of declining wild crab populations, improves food security, and promotes economic growth for fishers and farmers. These advancements contribute to the development of a sustainable crab farming ecosystem, ensuring long-term ecological and economic benefits.
Analisis Pengaruh Konten Digital Marketing Terhadap Minat Beli Produk Mobil Hyundai Sari, Emmy Puspita; Aras, Rezty Amalia; Sucipto, Kiki Resky Ramdhani
YUME : Journal of Management Vol 7, No 1 (2024)
Publisher : Pascasarjana STIE Amkop Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37531/yum.v7i1.6279

Abstract

Digital marketing termasuk strategi pemasaran yang dijalankan oleh PT. Gowa Modern Motor atau Hyundai Gowa melalui Instagram sejak tahun 2020 hingga sekarang. Selama diterapkannya belum pernah dilakukan evaluasi untuk melihat efektivitas konten digital marketing terhadap minat beli calon customer Hyundai Gowa. Penelitian ini bertujuan untuk mengetahui pengaruh konten digital marketing terhadap minat beli konsumen pada produk Hyundai di Hyundai Gowa melalui Instagram dengan metode kuantitatif menggunakan software SPSS 27 yang dilakukan dari bulan Maret hingga Agustus 2023. Selain melakukan wawancara, observasi, dan kuesioner, data populasi dikumpulkan dari 665 sampel, dengan 90 responden diambil dari pengikut Instagram dan calon pelanggan Hyundai Gowa. Regresi sederhana dengan uji T dan uji R Square kemudian digunakan untuk menganalisis data, dengan digital marketing sebagai variabel X (independen) dan minat beli sebagai variabel Y (dependen). Temuan penelitian menunjukkan bahwa pada tingkat signifikansi 0,05, pemasaran digital mempengaruhi minat beli sebesar 72,4%. Konten digital marketing yang dapat meningkatkan minat beli calon customer adalah jenis konten feeds gambar produk, edukasi dan informatif.Kata Kunci: Digital Marketing, Minat Beli, PT.Gowa Modern Motor
Co-Authors Aditya Alfarizi, Dimas Afrizal, Yogi Hadi Akbar, Andi Makkulai Al Faqih, Shofwan Al Isra Denk Rimakka Aulia Rahmawati Aulia Rahmawati, Aulia Darwis, Analta Dwi Nugroho H, Yabes Furqan Zakiyabarsi Hanung Adi Nugroho Hutami Endang Igi Ardiyanto Ilna Nardiyah Juhri, Juhri Muhaimin Nur, Muhammad Noor Akhmad Setiawan Ramdhani Sucipto, Kiki Reski Resky Ramdhani Sucipto, Kiki Resky Ramdhani, Kiki Rimakka, Al Isra Denk Sari, Emmy Puspita Sucipto, Kiki Resky Ramdhani Sukri Ahmad, Muhammad Syamsul Rijal Tri Lestari Ulil Amri, Muhammad Yogi Hady Afrizal