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All Journal Informatics and Digital Expert (INDEX) eProceedings of Engineering KALBISIANA Jurnal Sains, Bisnis dan Teknologi
Naufal, Farhan
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Social Sciences

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Sistem Rekomendasi Penawaran Produk Pada Online Shop Menggunakan K-Means Clustering Naufal, Farhan; Herry Chrisnanto, Yulison; Kania Ningsih, Ade
Informatics and Digital Expert (INDEX) Vol. 4 No. 1 (2022): INDEX, Mei 2022
Publisher : LPPM Universitas Perjuangan Tasikmalaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36423/index.v4i1.879

Abstract

Online Shop adalah salah satu fasilitas yang disajikan oleh internet, yang mampu mempermudah masyarakat dalam belanja tanpa harus bertatap muka dengan pelanggan, tanpa harus antri dan tawar menawar. Pertumbuhan ekonomi digital semakin besar persaingan bisnis juga akan semakin berat, akibatnya semakin banyak online shop tidak hanya menampilkan produk-produk tetapi juga perlu didukung oleh pemilihan produk yang tepat untuk menarik perhatian pelanggan. Terlalu banyaknya variasi produk yang ditawarkan secara random (acak) pada online shop membuat beberapa pelanggan kesulitan dalam menentukan produk yang akan dibeli. Berdasarkan permasalahan yang muncul maka penelitian mengenai Sistem Rekomendasi Penawaran Produk Pada Online Shop Menggunakan K-Means Clustering ini dilakukan. Sistem ini menggunakan algoritma K-Means Clustering serta dataset yang digunakan adalah data transaksi penjualan dari kurun waktu 1 tahun terakhir agar cakupanya tidak meluas dengan menggunakan data terbaru. Hasil dari penelitian ini ditemumakan bahwa ada 3 cluster yang memiliki karakteristik berbeda yaitu, cluster 1 dengan karakteristik penjualan sedang dengan rentang umur pembeli 36-50 tahun , cluster 2 dengan karakteristik penjualan terbanyak dengan rentang umur pembeli 18-26 tahun dan cluster 3 dengan karakteristik penjualan rendah dengan rentang umur 27-35 tahun. Dari hasil cluster dapat disimpulkan bahwa produk yang direkomendasikan merupakan produk terpopuluer dari setiap clusternya. Hasil perhitungan nilai sillhouette coeficient didapatkan cluster dengan jumlah 3 karena memiki nilai paling mendekati Si = 1 yaitu dengan nilai 0.7354092263523232.
Pengaruh Capital Adequacy Ratio (CAR), Dana Pihak Ketiga(DPK), Non Performng Finance terhadap Profitabilitas Perbankan Pada Tahun 2016 - 2020 Naufal, Farhan; Djunaedi, Mira Kartika Dwi
KALBISIANA Jurnal Sains, Bisnis dan Teknologi Vol. 9 No. 4 (2023): Kalbisiana
Publisher : UNIVERSITAS KALBIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53008/kalbisiana.v9i4.783

Abstract

This study aims to determine whether the capital adequacy ratio, non-performing finance, third party funds affect the profitability of Islamic banking. The grand theory in this study uses Agency Theory. The population in this study is Islamic banking registered on the OJK website. Using purposive sampling technique by using secondary data. The results of this study indicate that the capital adequacy ratio has a positive and insignificant effect, third party funds have a negative and insignificant effect on the profitability of Islamic banking and non-performing finance has a negative and significant effect on the profitability of Islamic banking.
Sistem Kendali Kecepatan Motor Penggerak Sikat Berbasis Fuzzy Logic Pada Robot Pembersih Kaca Gedung Bertingkat Naufal, Farhan; Sumaryo, Sony; Rahma, Basuki
eProceedings of Engineering Vol. 12 No. 5 (2025): Oktober 2025
Publisher : eProceedings of Engineering

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

Abstract

Abstract Window cleaning on high-rise buildings is a high-risk task for workers, especially regarding accidents at heights. As the number of high-rise buildings increases, the demand for safer and more efficient cleaning systems becomes more urgent. This study develops a robotic window cleaning system that integrates the YOLOv5 object detection algorithm with a fuzzy logic-based motor speed controller. The system is designed to detect stains on the glass using a camera and adjust the brush motor speed based on the level of dirt detected. The main goal of this research is to improve energy efficiency and reduce the risk of work-related accidents during manual cleaning at height. The methods used include hardware design based on Jetson Nano, implementation of YOLOv5 for stain detection, and the application of fuzzy logic to control motor speed. Testing on 30 image samples shows a stain detection accuracy of 90.82%, while the use of fuzzy logic can save power consumption by up to 38% compared to conventional control methods. The conclusion of this study is that the integration of YOLOv5 and fuzzy logic in the robotic window cleaner provides significant energy savings and enhances work safety in high-rise buildings. Keywords: window cleaning robot, YOLOv5, fuzzy logic, motor control, stain detection
Co-Authors Djunaedi, Mira Kartika Dwi Kania Ningsih, Ade Rahma, Basuki Sony Sumaryo Yulison Herry Chrisnanto