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All Journal SMATIKA SISFOTENIKA JURNAL MEDIA INFORMATIKA BUDIDARMA IKRA-ITH Informatika : Jurnal Komputer dan Informatika Dinamisia: Jurnal Pengabdian Kepada Masyarakat JUTEKIN (Jurnal Manajemen Informatika) JURTEKSI PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Jurnal Tekno Kompak Building of Informatics, Technology and Science Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Journal of Computer System and Informatics (JoSYC) Journal of Innovation Information Technology and Application (JINITA) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal AbdiMas Nusa Mandiri Jurnal Computer Science and Information Technology (CoSciTech) Rengganis Jurnal Pengabdian Masyarakat Jurnal Komtekinfo Smatika Jurnal : STIKI Informatika Jurnal
Prasetyaningrum, Eka
Universitas Darwan Ali
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Journal : Jurnal Computer Science and Information Technology (CoSciTech)

 1 
Analisis Perilaku Adopsi Digital Marketing Pada UMKM Menggunakan Model UTAUT3 di Era New Normal Eka Prasetyaningrum; Sari Atul Hilaliyah
Computer Science and Information Technology Vol 3 No 2 (2022): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v3i2.3955

Abstract

Penelitian ini bertujuan untuk mengetahui perilaku adopsi digital marketing pada pelaku UMKM di Kabupaten Kotawaringin Timur menggunakan model UTAUT3 di Era New Normal. Penelitian ini terdiri dari 146 responden yang didapatkan menggunakan teknik Probability Sampling. Hipotesis diuji dengan SEM PLS (Partial Least Square) dan menggunakan perangkat lunak WarpPls 7.0. Hasil pengujian ini terdapat Variabel yang menunjukkan hasil berpengaruh tidak signifikan yaitu Facilitating Condition terhadap Behavioral Intention, Facilitating Condition terhadap Use Behavior, Habit terhadap Behavioral Intention dan Perceived Risk terhadap Behavioral Intention. Sedangkan variable Performance Expentancy, Effort Expentancy, Social Influence, Hedonic Motivation, Personal Innovativeness of IT, Perceived Trust sangat berpengaruh signifikan terhadap variable Behavioral Intention. Dan variable Personal Innovativeness of IT dan Behavioral Intention juga berpengaruh signifikan terhadap Use Behavior.
Implementasi algoritma apriori dan metode topsis dalam penentuan pola penjualan pada meubel mentaya hafiz Eka Prasetyaningrum; Ummy Sholihah
Computer Science and Information Technology Vol 4 No 2 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i2.5013

Abstract

Indonesia's economic growth during the Covid-19 pandemic was not good due to low levels of public consumption. The government and MSME actors are trying to build the economy so that it can survive in all the conditions it faces. This study aims to find out how the implementation of the a priori algorithm and the TOPSIS method determine the sales pattern of a business. The analysis was carried out using two methods, namely the association rule using the a priori algorithm and the TOPSIS method as a decision support system. The analysis of the a priori algorithm produces an itemset of house frames, doors and windows as a combination that meets the 20% support value. Meanwhile, there are three association rules, namely if you buy house frames and doors, then buy windows with a confidence value of 100% and a lift ratio of 1.89. It's the same as the other 2 rules which produce a lift ratio value of more than 1, which means the rule is valid. In the analysis of the TOPSIS method, of the 22 alternatives it is known that alternative A14, namely windows, is ranked 1st as the product that sells the most, followed by alternative A13, namely doors. In addition, there are several products that have the same preference value so that they are also in the same rank, such as cafe chairs, stakes/stones and flower shelves then cafe tables and shoe racks.
Analisis Sentimen Kenaikan Harga Beras di Facebook Menggunakan Algoritma Naïve Bayes Rijal; Eka Prasetyaningrum; Agung Purwanto; Abdul Aziz
Computer Science and Information Technology Vol 5 No 2 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i2.7473

Abstract

This study explores public sentiment towards the rice price increase in Indonesia using data from social media posts on Facebook. As a crucial staple commodity, rice prices significantly impact the economy and social life of the community. In this study, data was collected from Facebook using Instant Data Scraper during the period from January to May. The collected data underwent a cleaning process, and 200 data points were manually labeled as training data. The text preprocessing steps included tokenization, case folding, and stopword removal. Subsequently, TF-IDF weighting was applied to determine the importance of each word in the documents. The processed data was then analyzed using the Naive Bayes algorithm to classify positive and negative sentiments. The analysis results showed that out of 428 test data points, the Naive Bayes algorithm successfully identified 237 reviews as positive sentiment and 191 reviews as negative sentiment. Based on the obtained data, this study is expected to provide insights for the government and policymakers in managing rice price policies and improving public communication strategies, as well as anticipating the social impact of rice price increases.
Co-Authors Abdul Aziz Agung Purwanto Andy Ismail arie wahyu pribadi Arindya Khauli Awanda Octavianti Putri Benny Setyawan Budiyanto, Herwin Dwi Wahyu Prabowo Elma Tiana Geofanny Widianto Sihite Haspianto, Mauli Istanta Lukman Bachtiar Mauli Haspianto Melano, Reynaldi Minarni Minarni Muhamad Rizky Mustaqiem, Mustaqiem Nurahman Nurahman, Nurahman Nurul Wahidah Patmawati Hasan Puji Susanti Puji Susanti Rafli Pratama Ramadhani, Nur Rachmat Fajar Rijal Sapitri, Amelia Wulan Sari Sari Atul Hilaliyah SATRIYAS ILYAS Thaher, Muhammad Tarmizi Thea Kirana, Elika Tobias Alexander Ummy Sholihah Wenti Utari Yunita, Selviana