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All Journal International Journal of Economics, Business and Accounting Research (IJEBAR) Safari : Jurnal Pengabdian Masyarakat Indonesia Journal of Research and Publication Innovation
Fahmi Firmansyah
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Arts Humanities Computer Science & IT Economics, Econometrics & Finance Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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Relational Marketing Model with Determinants of Service Quality and Pricing in Creating Customer Loyalty (Case Study of Seaweed Farmer Glacillaria sp in Brebes Regency-Central Java) Tabrani Tabrani; Dien Noviany Rahmatika; Fahmi Firmansyah
International Journal of Economics, Business and Accounting Research (IJEBAR) Vol 5, No 3 (2021): IJEBAR : Vol. 05, Issue 03, September 2021
Publisher : LPPM ITB AAS INDONESIA (d.h STIE AAS Surakarta)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijebar.v5i3.3148

Abstract

This study aims to determine and analyze how much the contribution of service quality, pricing and relational marketing to the satisfaction and loyalty of glacillaria sp seaweed farmers in brebes district, central Java, or the services of their partners, plasma nucleus companies. The research method used is explanatory survey. Data was collected using a questionnaire, the time of data collection was cross-sectional. Data analysis using SEM. The survey identified a sample of 180 samples. The results showed that service quality, pricing and relational marketing contributed significantly to the satisfaction and loyalty of seaweed farmers. Keyword: Relational Marketing Model, Service Quality, Pricing; Loyalty
Penanaman 1000 Pohon Cemara Laut Untuk Mitigasi Abrasi di Pantai Larangan Tegal Harira Irawan, Bei; Agus Prasetyono; Alip Toto Handoko; Fahmi Firmansyah; Mei Rani Amalia; Caesar Alwansyah Setiyanto; Fahzami Ahmad; Lulu Sabrina; Tika Widianti; Octania Meyrawati Alsaifira; Juli Riyanto Tri Wijaya
SAFARI :Jurnal Pengabdian Masyarakat Indonesia Vol. 4 No. 1 (2024): Januari : Jurnal Pengabdian Masyarakat Indonesia
Publisher : BADAN PENERBIT STIEPARI PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56910/safari.v4i1.1271

Abstract

Larangan Tegal Beach is located in the northern part of Central Java and is a tourist destination among other beaches such as Pulau Kodok beach, Komodo beach, and others. On the way to the beach, visitors will see ponds and mangrove trees lining the edge of the road. However, unfortunately, this beach is experiencing soil erosion which is quite worrying. Every time the sea water rises, the environment around the beach, especially the stalls that serve as resting places for tourists along the beach, will be submerged. The impact of coastal erosion is not only limited to inundation of sea water, but also has negative consequences for the environment and local communities. To overcome this abrasion problem, an activity was carried out to plant 1000 sea pine trees around the coast, especially in the areas of Kedungkelor Village, Munjungagung Village, and Bojongsana Village where the procurement of sea pine tree seeds came from the Tegal Regency National and Political Unity Agency (Kesbangpol) in collaboration with the Pancasakti Tegal University Campus and the Bhakti Negara Islamic Institute for the planting process. Through this activity, it is hoped that it can reduce the impact of land erosion on the coast and provide natural protection for coastal areas from strong winds and sea waves. It is hoped that this effort can protect the coast from damage that may arise due to storms and extreme weather
ANALISIS VISUAL DAN KLASTERISASI MULTIDOMAIN MENGGUNAKAN PYTON: KEUANGAN, GIZI, DAN POLITIK Abu Bakar Riziq; Ahmad Fadillah; Fahmi Firmansyah; Gumilang Ali Prayogi; Defri Sulaeman; Intan Kumalasari
Journal of Research and Publication Innovation Vol 3 No 3 (2025): JULY
Publisher : Journal of Research and Publication Innovation

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Abstract

This study applies data visualization and machine learning techniques to explore patterns across three distinct domains: corporate financial reports, food nutritional content (amino acids), and vote distribution in regional elections. Using Python and libraries such as pandas, scikit-learn, matplotlib, and seaborn, this study utilizes the KMeans algorithm, Principal Component Analysis (PCA), and linear regression. The results are evaluated using the Silhouette Score to assess cluster quality. This study demonstrates that an exploratory approach with Python is effective in uncovering insights from cross-domain data and supporting data-driven decision-making.
Co-Authors Abu Bakar Riziq Agus Prasetyono Ahmad Fadillah Alip Toto Handoko Caesar Alwansyah Setiyanto Defri Sulaeman Dien Noviany Rahmatika Fahzami Ahmad Gumilang Ali Prayogi Harira Irawan, Bei Intan Kumalasari Juli Riyanto Tri Wijaya Lulu Sabrina Mei Rani Amalia Mr. Tabrani Octania Meyrawati Alsaifira Tika Widianti