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All Journal Venus: Jurnal Publikasi Rumpun Ilmu Teknik Journal on Pustaka Cendekia Informatika
Robertus Tamo Ama
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Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Pengaruh Sumber Daya Manusia Dalam Pengembangan Digital Marketing Terhadap Minat Beli : (Studi Kasus : Toko Sumber Usaha Sumba Barat Daya) Robertus Tamo Ama; Delsiana Kette; Ancelina Bili; Meriana Milla
Venus: Jurnal Publikasi Rumpun Ilmu Teknik  Vol. 2 No. 3 (2024): Juni : Jurnal Publikasi Rumpun Ilmu Teknik
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/venus.v2i3.352

Abstract

This research aims to investigate the influence of human resources in digital marketing development on consumer purchasing interest, at business source stores. The research method used is quantitative using a questionnaire as a data collection tool. The sample for this research is consumers of business source stores who have made online transactions. Data analysis was carried out using multiple linear regression to test the relationship between digital marketing human resource variables and consumer buying interest. The research results show that human resources who are skilled and experienced in digital marketing have a positive and significant influence on consumer buying interest. The managerial implication of this research is the importance of investing in developing quality human resources in the digital marketing field to increase consumer buying interest and strengthen the competitive advantage of business resource stores in the market.
Klasifikasi Kain Tenun Sumba menggunakan Jaringan Saraf Tiruan Trisno, Trisno; Karolus Wulla Rato; Adelbertus Umbu Janga; Robertus Tamo Ama; Robinson Datu Reja
Journal on Pustaka Cendekia Informatika Vol. 1 No. 3 (2024): Journal on Pustaka Cendekia Informatika: Volume 1 Nomor 3 Oktober 2023 - Januar
Publisher : PT Pustaka Cendekia Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70292/pctif.v1i3.24

Abstract

The evaluation results with epoch 100 have quite good classification accuracy. The correct accuracy value of the classification is 60% of the test data. In other words, the results of this classification can be said to be good. Compared with the classification accuracy at epoch 100, which is 20-30% of the test data. The model obtained is good. At epoch 400 this model has a better level of accuracy than epoch 100. At epoch 1000 the increase in recognition accuracy for test data increases by 20% so that the recognition accuracy becomes 55-60%. Based on the results of research using the backpropagation neural network algorithm, there are several different levels of accuracy, the training and validation accuracy values ​​are quite good. The researcher's suggestion is to continue this research so that it can produce a more accurate process. The training process is carried out using several epoch values, namely epoch 200, epoch 400, epoch 600, epoch 800, epoch 1000, epoch. The best accuracy obtained during training was 89.3% and validation was 82%.
Co-Authors Adelbertus Umbu Janga Ancelina Bili Delsiana Kette Karolus Wulla Rato Meriana Milla Robinson Datu Reja Trisno Trisno