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All Journal JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Creative Information Technology Journal Techno Nusa Mandiri : Journal of Computing and Information Technology JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL ILMIAH INFORMATIKA JurTI (JURNAL TEKNOLOGI INFORMASI) Martabe : Jurnal Pengabdian Kepada Masyarakat Krea-TIF: Jurnal Teknik Informatika CSRID (Computer Science Research and Its Development Journal) Informasi Interaktif CCIT (Creative Communication and Innovative Technology) Journal Indonesian Journal of Business Intelligence (IJUBI) IJIIS: International Journal of Informatics and Information Systems Jurnal Pembelajaran Pemberdayaan Masyarakat (JP2M) Management and Sustainable Development Journal Journal of Applied Data Sciences International Journal of Computer and Information System (IJCIS) Jurnal Pengabdian Kepada Masyarakat Patikala Journal Computer Science and Informatic Systems : J-Cosys Jurnal Ilmiah Edutic : Pendidikan dan Informatika Jurnal Informatika: Jurnal Pengembangan IT ABDIKOM
Musthofa Galih Pradana
Universitas Pembangunan Nasional Veteran Jakarta
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

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Journal : Journal of Applied Data Sciences

 1 
Maximizing Strategy Improvement in Mall Customer Segmentation using K-means Clustering Pradana, Musthofa Galih; Ha, Hoang Thi
Journal of Applied Data Sciences Vol 2, No 1: JANUARY 2021
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v2i1.18

Abstract

The application of customer segmentation is very vital in the world of marketing, a manager in determining a marketing strategy, knowing the target customer is a must, otherwise it will potentially waste resources to pursue the wrong target. Customer segmentation aims to create a relationship with the most profitable customers by designing the most appropriate marketing strategy. Many statistical techniques have been applied to segment the market but very large data are very influential in reducing their effectiveness. The aim of clustering is to optimize the experimental similarity within the cluster and to maximize the dissimilarity in between clusters. In this study, we use K-means clustering as the basis for the segmentation that will be carried out, and of course, there are additional models that will be used to support the research results. As a result, we have succeeded in dividing the customer into 5 clusters based on the relationship between annual income and their spending score, and it has been concluded that customers who have high-income levels & have a high spending score are also very appropriate targets for implementing market strategies.
YOLOv8-Based Microplastic Detection and Quantification in River Water Microscopic Images Pradana, Musthofa Galih; Nyamiati, Retno Dwi; Shabrina, Husna Muizzati; Adrezo, Muhammad; Maulana, Nurhuda
Journal of Applied Data Sciences Vol 7, No 2: May 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i2.1262

Abstract

Plastic particles with various size variations such as microplastics are environmental contaminants that are widely found in waters and have the potential to cause negative impacts. The process of identifying plastic particles using microscopic imagery manually takes a lot of time and considerable cost. In order to provide an alternative solution as part of early detection, microscopic image-based plastic particle detection was carried out with the YOLOv8 architecture, accompanied by an estimate of microplastic abundance in microplastic units per cubic meter. This study aims to develop and evaluate the detection of plastic particles in microscopic images of river water. This research dataset consists of 300 microscopic images taken from three river locations in Indonesia and annotated for model training and testing. The results of the evaluation showed that the proposed model had an aggregate performance value with a precision value of 0.786, recall of 0.66, and mAP@0.5 of 0.731. Additional test results show that with the addition of image resolution, the precision value can increase to 0.804 and the value mAP@0.5 increases to 0.762, even at the expense of computing time, which is also increasing. Extended scenario-based analysis showed that more than 87% of the detected objects fell into the category of small objects, affecting the localization sensitivity and variability of the estimated MPS value. This study also validated the results of object detection with FTIR-based laboratory tests using a full quantitative agreement between the model detection results and the identification of plastic particle materials at the sampling location level. The main contribution and findings of this study is an integrated evaluation framework for object detection, particle size characterization which is expected to be an alternative to the initial screening tool for plastic particle content.
Co-Authors Adhien Kenya Anima Estetikha Andri Pramuntadi Anni Alvionita Simanjuntak Budi, Ryan Setya Dema Mathias Lumban Tobing Dhina Puspasari Wijaya, Dhina Puspasari Dwi Nyamiati, Retno Dyah Listianing Tyas, Dyah Listianing Emha Taufiq Luthfi Fadhli Suko Wiryanto Fandli Supandi Gutama, Deden Hardan Ha, Hoang Thi Henki Bayu Seta I Wayan Rangga Pinastawa Izzety, Aurel Jayanta Kaharuddin Karenina, Syaila Ananta Kharisma Wiati Gusti Khoironi, Khoironi Khoirunnisa, Hilda Kusrini Kusrini Kusrini Kusrini Kusrini Kusrini MARTINI, NI PUTU DEVIRA AYU Mu, Jesselyn Muhamad Ridwan Muhamad Ridwan Muhammad Adrezo Muthia Zahrah, Nada Neny Rosmawarni Nindy Irzavika Niqotaini, Zatin Nurcahyo, Azriel Christian Nurhajar Anugraha Nurhuda Maulana Nurul Afifah Arifuddin Nyamiati, Retno Dwi Pamekas, Bondan Wahyu Prananto, Muhammad Teguh Pujo Hari Saputro Rabbani , Salma Ashiila Radinal Setyadinsa Rangga Pinastawa, I Wayan Rangga Saputra Ridlo Muttaqien Ridwan Raafi'udin Rifka Dwi Amalia Rifqi Hammad Rusiyono, Ruwet Setiawan, Deandra Satriyo Shabrina, Husna Muizzati Wahit Desta Prastowo Wari, Valtrizt Khalifah Yulianto Mustaqim Yusuf Hendra Pratama