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Journal : JOIV : International Journal on Informatics Visualization

Big Mart Sales Data Visualization and Correlation Arista, Artika; Theresiawati, Theresiawati; Seta, Henki Bayu
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.1780

Abstract

The amount of unprocessed data available every day is growing. This massive amount of data needs to be effectively assessed to give results that are extremely useful. In the present day, it is crucial for inventory management and demand forecasting to collect sales data for commodities or things, together with all their numerous dependent or independent parts. In a Big Mart Company, the use of sales forecasting is to estimate numerous goods that are readily available and supplied at multiple retailers in different towns. As the number of products and outlets increased drastically, it became increasingly difficult to forecast them manually. As a result, it is necessary to see to what extent the relationship between several variables, including price, popularity, time of day, outlet type, outlet location, etc., affects the appeal of a product. In this research, a data cleaning process was carried out, and data visualization using scatter plots, as well as finding Pearson correlations. The raw processing the data with study of a case big mart sales data is taken from the Kaggle website [https://www.kaggle.com/datasets/sandeepgauti/bigmart-sales]. The Pearson correlation test determines a lack of connection between the two Item_Weight and Item_Outlet_Sales variables. There is a strong but negative correlation where if Item_Visibility decreases, Item_Outlet_Sales also decreases. Positive relationships exist between the two Item_MRP and Item_Outlet_Sales variables. In addition to the correlation test, descriptive statistical analysis is also performed here. With this simple data processing, the raw data will be better organized and easier to analyze, read, and use.
Push-Pull-Mooring Theory and The Moderating Effect of Inertia on Switching Intention to Mobile Learning Seta, Henki Bayu; Theresiawati, Theresiawati; Niqotaini, Zatin; Trahira, Juwita Istiqomah; Assegaf, Najwaa Nahda
JOIV : International Journal on Informatics Visualization Vol 9, No 5 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.5.2867

Abstract

Inertia is a hindering factor in transition, which is essential to investigate as a push-pull-mooring factor influencing the switching intention to use mobile learning. Mobile learning research in Indonesia is still new, and only a few studies analyze the moderating effect of inertia on switching intention to mobile learning.  The research aims to examine students' intentions to adjust to mobile learning at universities in Indonesia and analyze the moderating effect of inertia in weakening the correlation between pull and push factors and shifting intention. This study employed a quantitative method involving a sample of 163 students. To explain inertia, this study adopted habits, switching costs, student innovation, network externalities, and technological self-efficacy as independent variables leading to inertia. This research reveals that inertia moderates learning convenience, learning autonomy, and task technology fit. Meanwhile, inertia is influenced by habit, switching costs, student innovativeness, and technological self-efficacy. This research also confirms that service quality, perceived enjoyment, and task technology fit significantly impact switching intention to employ the use of mobile learning. This research reveals that inertia moderates learning convenience, learning autonomy, and task technology fit. Meanwhile, inertia is influenced by habit, switching costs, student innovativeness, and technological self-efficacy. This research also confirms that service quality, perceived enjoyment, and task technology fit have a significant effect on switching intention to use mobile learning. University management and practitioners must increase students’ awareness of the benefits of mobile learning in higher education institutions.  Further research should test additional variables such as gender and student satisfaction with mobile learning.
Co-Authors Achmad Nizar Hidayanto Adella Rifiandika Putri Alif Garindra Alya Nur Ramadhani Ananda Alvi Al Fadhli Josephine Andhika Octa Indarso Anita Muliawati Annisa Rizky Damanik Artika Arista Assegaf, Najwaa Nahda Bambang Triwahyono Bayu Seta, Henki devitasari, Devitasari Diana Dyah Damayanti Erly Krisnanik Ernawati, Iin Ernawati Fadiyawan, Vidiani Aulia Fikastiana Cahya Gilang Priambodo Gilang Priambodo Gunasti, Nabilah Hadi, Novi Trisman Hafizhah, Annizhamul Hanif Razka, Muhamad Harvey Guharelvino Prabowo Henki Bayu Seta Hesti, Intan I Wayan Widi P I Wayan Widi P I Wayan Widi Pradnyana I Wayan Widi Pradyana Ichsan Mardani Ika Nurlaili Isnainiyah Ika Nurlaili Isnainiyah Intan Hesti Isnainiyah, Ika Nurlaili Jayanta Jayanta Jayanta Jayanta Jayanta Jayanta Jayanta Kamila, Vina Zahrotun Kinantan Prabu, Hamonangan Kraugusteeliana Kraugusteeliana Maghribi, Muhammad Rezka Al Matondang, Nurhafifah Muhammad Ridwan Muslikhah, Riki Muslim, Muhammad Panji Nabila, Suci Niqotaini, Zatin Nugrahaeni Puspita Dewi, Catur Nurul Chamidah Pangaribuan, Artambo Benjamin Prabu, Hamonangan Kinantan Rahmah, Fauzia Hayati Rahmawan, Rizki Rafly Razaqa, Dhi'fan Refa Yudhatama Ramadhan Regina Josephine Ria Astriratma Rio Wirawan Risma Yulistiani Rudhy Ho Purabaya Ruth Mariana Bunga Wadu Sarika Afrizal, Sarika Sarika Sarika Sarika, Sarika Siti Khofifah Situmorang, Arnold Parulian Sumilir Tjahjanto Tjahjanto Tjahjanto, Tjahjanto Trahira, Juwita Istiqomah Tri Rahayu Tri Rahayu Triwahyono, Bambang Wahanandra, Muhammad Daffa Wahyuda, Murdika Warsuta, Bambang Zaidiah, Ati