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All Journal Elkom: Jurnal Elektronika dan Komputer Kalbiscientia Jurnal Sains dan Teknologi ABDIMAS Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Bersama Masyarakat Indonesia
Ari Hidayatullah
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Public Health Social Sciences

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Analisis Pengaruh Fitur User Interface Ramah Pengguna Terhadap Tingkat Loyalitas Pelanggan di Tokopedia Septanto, Henri; Ari Hidayatullah; Harya Bima Dirgantara
KALBISCIENTIA Jurnal Sains dan Teknologi Vol. 11 No. 02 (2024): Jurnal Sains dan Teknologi
Publisher : Research and Community Service UNIVERSITAS KALBIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53008/kalbiscientia.v11i02.4324

Abstract

This research aims to analyze the influence of user-friendly user interface features on the level of customer loyalty in the Tokopedia application. In an increasingly advanced digital era, user experience is a crucial factor in maintaining and increasing customer loyalty. Tokopedia, as one of the largest market place platforms in Indonesia, continues to develop UI features that make navigation easier, increase interaction and enrich the shopping experience. This research uses a survey method involving 50 active Tokopedia users to collect data regarding their perceptions of the application's UI features. Data analysis was carried out using simple quantitative descriptive processing techniques to identify the relationship between user-friendly UI and customer loyalty. The research results show that there is a significant positive correlation between intuitive and easy-to-use UI features and the level of customer loyalty. Users who feel comfortable and satisfied with the application interface tend to make repeat transactions more often and recommend Tokopedia to others. These findings emphasize the importance of investing in user-friendly UI development as a strategy to increase customer satisfaction and loyalty in the competitive e-commerce market.Keywords: user interface, loyalty, application, market place
Pelatihan Pembuatan Game Edukasi Pengenalan Profesi sebagai Media Alternatif Berbasis Multimedia untuk Guru SD Vianney Septanto, Henri; Ari Hidayatullah
ABDIMAS Jurnal Pengabdian Kepada Masyarakat Vol. 6 No. 1 (2025): ABDIMAS JURNAL PENGABDIAN KEPADA MASYARAKAT
Publisher : Research and Community Service INSTITUT TEKNOLOGI DAN BISNIS KALBIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53008/abdimas.v6i1.4542

Abstract

Game Edukasi memiliki pengaruh dalam membentuk pengetahuan, sikap, dan keterampilan anak. Game Edukasi pengenalan terhadap beragam profesi pada PKM yang ada di masyarakat. Pengenalan profesi ini tidak hanya memberikan wawasan kepada anak-anak mengenai berbagai pilihan karir di masa depan, tetapi juga membantu mereka memahami peran penting orang tua dalam kehidupan sehari-hari dan masyarakat secara keseluruhan. PKM ini bertujuan untuk membantu guru-guru dalam memberikan materi tentang beberapa profesi melalui game edukasi. Aplikasi ini dirancang untuk memberikan pengalaman belajar yang menyenangkan, di mana siswa dapat mengenal berbagai profesi, memahami tanggung jawab dan keterampilan yang diperlukan, serta menyadari pentingnya profesi dalam kehidupan masyarakat. PKM ini bertujuan untuk membantu para guru meningkatkan kesadaran anak-anak TK terhadap pentingnya mengetahui berbagai profesi di dalam masyarakat karena di masa depan anak-anak juga harus memiliki profesi untuk kehidupannya. Metode pelatihan mencakup analisis kebutuhan dan peserta, pengembangan aplikasi, pendekatan interaktif dengan anak-anak SD, pelatihan untuk guru SD dan evaluasi melalui tanya jawab dengan murid SD tentang profesi orang tua mereka dan profesi yang mereka inginkan di masa depan. Hasil evaluasi menunjukkan bahwa game multimedia edukasi efektif dalam meningkatkan kesadaran anak-anak SD terhadap pentingnya pengetahuan tentang profesi sebagai penambah wawasan mereka tentang masa depan.
The Prediksi Curah Hujan Pada Stasiun BMKG (CITEKO) Menggunakan Metode Backpropogation Neural Network Reni, Reni Utami; Ari Hidayatullah
Elkom: Jurnal Elektronika dan Komputer Vol. 17 No. 1 (2024): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v17i1.1921

Abstract

Accurate rainfall prediction is needed to improve the performance of land that always uses rainfall data. Data mining or often called knowledge discovery in databases (KDD) is an activity that includes collecting, using historical data to find regularities, patterns or relationships in large data. In predicting rainfall, there are several conditions that can be observed as reference data to predict rainfall, namely wind speed, temperature, and air humidity. In this research, a backpropagation artificial neural network prediction method is developed that can be used in predicting future rainfall. The backpropogation artificial neural network method that was built produced an accuracy value of 95.36%, a precision value of 90.50%, a recall value of 97.50% and an f-measure value of 92.00%
The CLASSIFICATION OF PROSPECTIVE POLICY HOLDERS FOR SELECTING INSURANCE PRODUCTS USING A COMPARISON OF THE K-NEAREST NEIGHBOR METHOD AND THE NAIVE BAYES METHO irfan, Irfan Nurdiansyah; Ari Hidayatullah
Elkom: Jurnal Elektronika dan Komputer Vol. 17 No. 1 (2024): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v17i1.1922

Abstract

The insurance business within an insurance company offers insurance products owned by the insurance company. In every insurance product there is a premium payment and the premium is the income of an insurance company at the rate of the amount insured. The problem that PT BNI Life Insurance has is that there are many stops in premium payments such as policy redemptions due to errors in the benefits received or incorrect selection of the insurance product, this can reduce the achievement of targets for an insurance company. The aim of this research is to find out the best classification algorithm compared between K-Nearest Neighbor and Naive Bayes to predict the type of insurance product that customers will choose. In this research, data mining methods are applied to compare two different methods, namely the K-Nearest Neighbor method and the Naïve Bayes method. The level of accuracy results for the K-Nearest Neighbor method is 80% and the Naïve Bayes method is 70.53%, which means that the K-Nearest Neighbor method is the best method to apply to an insurance product classification system based on the demographics of prospective customers.
Co-Authors Harya Bima Dirgantara Henri Septanto Henri Septanto, Henri Irfan Nurdiansyah irfan, Irfan Nurdiansyah Reni, Reni Utami