Article Per Year (5 Year)
p-Index From 2020 - 2025
0.61
P-Index
This Author published in this journals
All Journal Indonesian Journal of Artificial Intelligence and Data Mining JUDICIOUS: Journal of Management Jurnal Multidisiplin West Science
Ramadhan, M Fitrah
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Compratative Analysis of Online and Offline Sales of Blacksmith Product Income in the Cibatu Area Pratiwi, Intan Deanida; Ramadhan, M Fitrah; Algipari, M Fauzan; Rafly, Muhammad Naufal; Ilmi, Salya Aina Zahratani
JUDICIOUS Vol 5 No 2 (2024): Judicious
Publisher : Neolectura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37010/jdc.v5i2.1781

Abstract

This research aims to analyze the comparison of online and offline sales of blacksmith product income in the Cibatu area. The analytical method used in this journal is a qualitative method by conducting direct interviews with blacksmith sellers in the Cibatu area. The findings from interviews with iron sellers show that on average online sales are more profitable compared to offline income because of advances in technology and the spread of the internet, of course e-commerce is more easily accessible to people throughout the world, which makes online sales increasingly popular. used by local residents to increase income. But offline sales also still have an important role for the local market. However, online sales also affect profit margins due to the resellers involved. ROI on online sales is considered more profitable than offline sales. The results of the analysis highlight the strengths and weaknesses of each sales channel as well as the implications for blacksmith product income in the Cibatu area.
Lithology Prediction Using Deep Learning Artificial Neural Network and Schlumberger Resistivity Inversion Data at Eastern Lampung Ramadhan, M Fitrah; Irianto, Suhendro Yusuf; Farduwin, Alhada
Indonesian Journal of Artificial Intelligence and Data Mining Vol 8, No 2 (2025): July 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v8i2.37652

Abstract

The Schlumberger geoelectric method has been extensively employed in earth resource exploration due to its capability to identify variations in subsurface resistivity. However, the manual interpretation of geoelectric data inversion results is often subjective and time-consuming. This study aims to automate the lithology identification process by utilizing deep learning techniques, particularly Artificial Neural Networks (ANN), based on the inverted resistivity parameters obtained through the IPI2Win software. The Schlumberger configuration geoelectric data were obtained from survey reports provided by the Ministry of Public Works and Housing (Kementerian Pekerjaan Umum dan Perumahan Rakyat/ PUPR), which conducted geoelectric measurements in East Lampung Regency, Lampung Province, Indonesia. The ANN algorithm demonstrated an average accuracy of 90% in predicting lithology based on resistivity patterns resulting from Schlumberger inversion. Outperforming Support Vectorr Machine (SVM) (87%) and XGBoost (88%). These results confirm the initial hypothesis that ANN can effectively capture the complex relationships between resistivity values and rock types. The present study proposes an integrated approach between geophysics and machine learning with ANN algorithms for lithology prediction based on Schlumberger configuration geophysical inversion data. The present study proposes an integrated approach between geophysics and machine learning with ANN algorithms for lithology prediction based on Schlumberger configuration geophysical inversion data.
Pengaruh Promosi dan Kualitas Produk Tentang Keputusan Konsumen di Tiktok Marketplace Ramadhan, M Fitrah
Jurnal Multidisiplin West Science Vol 3 No 09 (2024): Jurnal Multidisiplin West Science
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/jmws.v3i09.1353

Abstract

Penelitian ini bertujuan untuk mengevaluasi dampak promosi dan kualitas produk terhadap keputusan konsumen di TikTok Marketplace. Sebagai platform media sosial yang populer, TikTok telah memperkenalkan fitur marketplace yang memungkinkan penjual untuk memasarkan dan menjual produk mereka langsung kepada pengguna. Dipercaya bahwa promosi yang efektif dan produk berkualitas tinggi dapat mempengaruhi keputusan pembelian konsumen. Penelitian ini menggunakan metode survei dengan menyebarkan kuesioner kepada 21 responden yang aktif berbelanja di TikTok Marketplace. Data yang terkumpul dianalisis menggunakan aplikasi ibm spss untuk menentukan sejauh mana promosi dan kualitas produk mempengaruhi keputusan konsumen. Hasil penelitian menunjukkan bahwa kedua variabel tersebut, baik promosi maupun kualitas produk, memiliki dampak signifikan terhadap keputusan konsumen. Promosi yang menarik dan informatif meningkatkan minat dan kepercayaan konsumen untuk membeli, sementara produk dengan kualitas tinggi memastikan kepuasan dan loyalitas konsumen. Studi ini menyarankan agar penjual di TikTok Marketplace berfokus pada strategi promosi yang kreatif serta menjaga kualitas produk untuk mengoptimalkan keputusan pembelian konsumen.
Co-Authors Algipari, M Fauzan Farduwin, Alhada Ilmi, Salya Aina Zahratani Intan Deanida Pratiwi Rafly, Muhammad Naufal Y. Suhendro