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All Journal Techno.Com: Jurnal Teknologi Informasi Open Access Indonesia Journal of Social Sciences Open Access Indonesia Journal of Social Sciences
Wahyudi, Aditio
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Humanities Computer Science & IT Economics, Econometrics & Finance Education Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences

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Analysis of Gojek's Brand Perception Utilizing Twitter Hashtag: Sentiment Analysis Using Ekman's Classification Wahyudi, Aditio; Arief Tirtana; Lady Diana Langoy
Open Access Indonesia Journal of Social Sciences Vol. 6 No. 2 (2023): Open Access Indonesia Journal of Social Sciences
Publisher : HM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (522.609 KB) | DOI: 10.37275/oaijss.v6i2.153

Abstract

Advertisers constantly try to use different communication channels to approach consumers more effectively and promptly and increase their products' visibility and attractiveness. Gojek, an Indonesian ride-hailing and delivery company, uses hashtags as part of its marketing strategy on social media platforms such as Twitter and Instagram. This research aimed to analyze Gojek's brand perception using the Twitter hashtag. This research uses descriptive analysis and sentiment analysis using Ekman's classification of emotional expression algorithm. This research analyzed 813 tweets containing hashtags related to Gojek, an Indonesian ride-hailing and delivery company, including #AmanBersamaGojek, #Cerdikiawan, #JalanTerus, #PastiAdaJalan, and #SebelumGojek, to understand the sentiment and emotional tone of the tweets. Using Ekman's classification method for identifying and categorizing emotional expressions, the analysis found that the tweets were predominantly positive in sentiment, with surprise and joy being the most frequently expressed emotions. However, the research also identified a range of other emotions expressed in the tweets, including fear, sadness, disgust, and anger, indicating that Twitter users may have more complex and nuanced attitudes toward Gojek and its hashtags. In conclusion, Gojek may consider conducting additional research and implementing strategies to address negative emotions and better engage with its audience on social media to improve its brand perception on Twitter.
Analysis of Gojek's Brand Perception Utilizing Twitter Hashtag: Sentiment Analysis Using Ekman's Classification Wahyudi, Aditio; Arief Tirtana; Lady Diana Langoy
Open Access Indonesia Journal of Social Sciences Vol. 6 No. 2 (2023): Open Access Indonesia Journal of Social Sciences
Publisher : HM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37275/oaijss.v6i2.153

Abstract

Advertisers constantly try to use different communication channels to approach consumers more effectively and promptly and increase their products' visibility and attractiveness. Gojek, an Indonesian ride-hailing and delivery company, uses hashtags as part of its marketing strategy on social media platforms such as Twitter and Instagram. This research aimed to analyze Gojek's brand perception using the Twitter hashtag. This research uses descriptive analysis and sentiment analysis using Ekman's classification of emotional expression algorithm. This research analyzed 813 tweets containing hashtags related to Gojek, an Indonesian ride-hailing and delivery company, including #AmanBersamaGojek, #Cerdikiawan, #JalanTerus, #PastiAdaJalan, and #SebelumGojek, to understand the sentiment and emotional tone of the tweets. Using Ekman's classification method for identifying and categorizing emotional expressions, the analysis found that the tweets were predominantly positive in sentiment, with surprise and joy being the most frequently expressed emotions. However, the research also identified a range of other emotions expressed in the tweets, including fear, sadness, disgust, and anger, indicating that Twitter users may have more complex and nuanced attitudes toward Gojek and its hashtags. In conclusion, Gojek may consider conducting additional research and implementing strategies to address negative emotions and better engage with its audience on social media to improve its brand perception on Twitter.
Integrasi Perangkat Energy Meter iEM3255 Pada Sistem Pemantau Konsumsi Energi Listrik Berbasis Internet of Things (IoT) Menggunakan Komunikasi ModBus Atmajaya, Gde KM; Abdullah, Muhammad Husein; Wahyudi, Aditio; Yuliansyah, Harry
Techno.Com Vol. 24 No. 1 (2025): Februari 2025
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v24i1.12110

Abstract

Energi listrik merupakan salah satu energi yang banyak dimanfaatkan dalam menjalankan segala aktivitas manusia. Konsumsi energi listrik yang tidak terkendali dapat menjadi potensi pemborosan yang dapat merugikan dari segi ekonomi dan lingkungan. Berdasarkan permasalahan tersebut, dirancang suatu sistem pemantau konsumsi energi listrik berbasis Internet of Things (IoT) untuk memantau konsumsi energi listrik. Sistem ini tersusun dari sensor arus, energy meter iEM3255, Mikrokontroller ESP32, perangkat LoRa, dan suplai daya. Komponen – komponen tersebut diintegrasikan menggunakan komunikasi ModBus dan hasil pengukuran dapat dilihat melalui aplikasi smartphone yang dibuat menggunakan platform Kodular. Berdasarkan hasil implementasi dan pengukuran arus, tegangan, dan daya diperoleh nilai error sebesar 3,84%. Berdasarkan hasil tersebut dapat disimpulkan perangkat Energy Meter iEM3255 dapat diintegrasikan dengan sistem pemantau konsumsi energi listrik berbasis IoT dengan menyesuaikan kapasitas beban yang terpasang.   Kata kunci: Sistem Pemantau Energi Listrik, Energy Meter, Komunikasi ModBus, IoT.
Co-Authors Abdullah, Muhammad Husein Arief Tirtana Atmajaya, Gde KM Lady Diana Langoy Yuliansyah, Harry