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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika JurTI (JURNAL TEKNOLOGI INFORMASI) Indonesian Journal of Business Intelligence (IJUBI) Jurnal Abdimas Bina Bangsa NUSANTARA: Jurnal Pengabdian Kepada Masyarakat Jurnal Informatika: Jurnal Pengembangan IT
Rifka Dwi Amalia
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Computer Science & IT Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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ANALISIS PENGGUNAAN LOCAL SERVER PADA PENGELOLAAN DATA SEKOLAH MENEGAH MENGGUNAKAN DELONE MCLEAN Rifka Dwi Amalia; Eko Riyanto
Indonesian Journal of Business Intelligence (IJUBI) Vol 6, No 1 (2023): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v6i1.3201

Abstract

Peningkatan pengguna internet di Indonesia selaras dengan pertumbuhan angka penggunaan domain. Hal ini berimplikasi terhadap banyaknya local server yang digunakan, tak terkecuali dalam bidang pendidikan. Pemanfaatan local server ini sudah menjadi hal yang mulai dilakukan oleh beberapa institusi pendidikan di Indonesia. Namun, penerapan saja local server pada masing-masing institusi tidaklah cukup, perlu dilakukan pengukuran untuk mendapatkan gambaran apakah penerapan teknologi sudah tergolong sukses atau belum. Metode pendekatan yang dapat digunakan adalah Delone Mclean yang memiliki indikator untuk melakukan pengukuran kesuksesan. Pada penelitian ini, data diambil dari sekolah menengah yang sudah menerapkan local server. Data yang digunakan ada pada 10 sekolah menengah yang masing-masing sekolah akan mengirimkan 3 responden untuk mengisi dari penerapan local server pada institusinya dengan total responden pada penelitian ini sebanyak 30 responden. Hasil akhir dari penelitian dari 26 butir skema hipotesa, 20 butir dinyatakan valid dan 6 tidak valid. Sedangkan untuk pengujian hipotesa 5 hipotesa dinyatakan terbukti, yakni Information System berpengaruh terhadap Use; Information System berpengaruh terhadap User Satisfaction; User Satisfaction berpengaruh terhadap Net Benefit; dan Net Benefit berpengaruh terhadap Use dan User Satisfaction. 
PENGAPLIKASIAN PENGGUNAAN MICROSOFT OFFICE SEBAGAI MEDIA PENGAJARAN DAN PEMBELAJARAN BAGI GURU DI SMKS MANDIRI BOJONGGEDE BOGOR Neny Rosmawarni; Rifka Dwi Amalia; Zatin Niqotaini
Jurnal Abdimas Bina Bangsa Vol. 4 No. 2 (2023): Jurnal Abdimas Bina Bangsa
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/jabb.v4i2.636

Abstract

This community service (PKM) aims to examine the introduction of Microsoft Office as a teaching and learning medium at SMKS Mandiri Bojonggede, Bogor. The methods used are surveys and interviews to evaluate the use and benefits of Microsoft Office in an educational context. PKM results show that the use of Microsoft Office has great potential in improving the quality of teaching and learning at SMKS Mandiri Bojonggede. Teachers use it to create interactive presentations, manage learning materials, and create assignments and exams. While students use applications such as Word, Excel, and PowerPoint to do assignments, create reports, and present PKM results. The use of Microsoft Office as a medium of teaching and learning provides benefits in the form of improving technology skills, collaboration between teachers and students, increasing creativity in material delivery, and preparing students for the technological world of work. Despite challenges such as limited technology accessibility, lack of training for teachers, and limited understanding of students' potential applications, it is recommended to provide regular training for teachers, improve technology infrastructure, and develop teaching strategies that meet student needs. In conclusion, the introduction of Microsoft Office as a teaching and learning medium at SMKS Mandiri Bojonggede, Bogor, has a positive impact in improving student learning experience and teacher teaching effectiveness. By addressing existing challenges, the use of Microsoft Office can continue to be improved and integrated in school curricula to enhance innovative and relevant learning in the era of information technology
Optimalisasi Segmentasi Pelanggan Menggunakan Hierarchical Clustering Musthofa Galih Pradana; Rifka Dwi Amalia; Kharisma Wiati Gusti
JurTI (Jurnal Teknologi Informasi) Vol 7, No 2 (2023): DESEMBER 2023
Publisher : Universitas Asahan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36294/jurti.v7i2.3782

Abstract

Posisi dan peranan pelanggan dalam keberlangsungan usaha bagi sebuah perusahaan sangatlah vital, hal ini menjadikan perusahaan harus bisa melakukan proses kebijakan dan keputusan yang tepat dalam mengoptimalkan segala sumber yang dimiliki untuk dapat merumuskan strategi dan kebijakan yang baik, tak terkecuali bagi perusahaan penyedia layanan pusat perbelannjaan seperti mall. Landasan kebijakan atau keputusan yang baik, pada dasarnya dapat didasarkan pada sebuah fakta ataupun data nyata yang merepresentasikan keadaan sesungguhnya. Proses perumusan dan penentuan keputusan juga dapat berimplikasi secara langsung terhadap keberlangsungan dan jalannya sebuah perusahaan. Salah satu identifikasi yang bisa dilakukan oleh perusahaan diantaranya adalah dengan melakukan segmentasi pelanggan. Proses segmentasi dapat digunakan dengan berbagai macam acuan dan juga ranah keilmuan, salah satunya dalam hal data mining atau proses ekstrasi data menjadi sesuatu yang lebih bernilai. Teknik pendekatan yang dapat diterapkan untuk strategi segmentasi salah satunya dengan proses klustering, hal ini cocok dikarenakan proses pengelompokan data yang secara tidak terbimbing dapat menjadikan dan mengekstrak informasi baru dari sekumpulan data. Salah satu algoritma yang dapat diterapkan adalah hierarchical clustering, algoritma ini menghubungkan baris atau sampel dengan konfigurasi yang sama untuk membentuk struktur pohon. Adapun hasil dari penelitian ini adalah proses penerapan algoritma hierarchical clustering dapat memberikan sudut pandang baru dari data yang ada dan berpeluang dijadikan strategi segmentasi perusahaan. Cluster yang terbentuk dari segmentasi ini sebanyak 5 cluster dengan hasil validasi terhadap penggunaan metode elbow memiliki hasil yang sama.
A CNN Model for ODOL Truck Detection Arifuddin, Nurul Afifah; Gusti, Kharisma Wiati; Amalia, Rifka Dwi
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.13780

Abstract

This study developed a Convolutional Neural Network (CNN) model as one of artificial intelligence method to detect trucks experiencing over-dimension and over-loading (ODOL). The primary goal of this research is to enhance the efficiency of truck monitoring, reduce road infrastructure damage, and support the sustainability of transportation using artificial intelligence approaches. The model was trained using a dataset consisting of ODOL and non-ODOL truck images, and successfully achieved a testing accuracy of 94.23%. The confusion matrix analysis demonstrated the model's ability to classify trucks with high precision.  Additional testing on truck images not included in the training or testing dataset showed the model's potential for good generalization.
Optimizing Road Safety with MobileNet-Based Classification of Over-dimensioned Trucks Arifuddin, Nurul Afifah; Capri, Hary; Setiawan, Deni; Amalia, Rifka Dwi; Gusti, Kharisma Wiati
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 2 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i2.8239

Abstract

This study aims to automatically detect overdimension trucks using a lightweight and efficient deep learning model based on MobileNet. Overdimension trucks pose serious threats to road infrastructure, traffic safety, and contribute to increased economic costs due to road damage and congestion. The developed model utilizes MobileNet as a feature extractor without the standard fully connected layers, and is equipped with additional layers including Flatten, Batch Normalization, Dense with Leaky ReLU activation, and Dropout to enhance training stability and prevent overfitting. The dataset consists of two classes—normal trucks and overdimension trucks—with images sized 128×128 pixels, collected from internet sources and field photos. The training process employs binary crossentropy loss, the Adam optimizer with an initial learning rate of 0.0001, and an Early Stopping mechanism. Fine-tuning is performed by unfreezing layers from the 100th layer upward and lowering the learning rate to 0.00001. Evaluation results show an accuracy of 97.92%, with consistent loss and accuracy visualization, demonstrating the model's capability in classifying overdimension trucks to support automatic traffic monitoring systems. This model has the potential to be implemented in toll gate systems to automatically deny access to overdimension vehicles. Furthermore, integration with roadside CCTV allows real-time monitoring of vehicle dimension violations across various traffic checkpoints.
Pelatihan Google Workspace sebagai Sistem Manajemen Pengetahuan di TK Islam At-Tin Rifka Dwi Amalia; Nurul Afifah Arifuddin; Radinal Setyadinsa
Nusantara: Jurnal Pengabdian kepada Masyarakat Vol. 5 No. 3 (2025): Agustus : NUSANTARA Jurnal Pengabdian Kepada Masyarakat
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/nusantara.v5i3.6451

Abstract

This community service program is designed to address the need for digitalization in administrative management and improve digital literacy in schools. The main focus of the activity is training on the use of Google Workspace as an integrated knowledge management system to improve work efficiency and collaboration among staff. Problems faced by schools include the continued use of manual administrative systems and a low understanding of how to use digital platforms. The training was conducted as a workshop with a learning-by-doing approach, allowing participants to learn directly and contextually. The training material covered the operation of various Google Workspace features, such as Google Forms, Sheets, Calendar, Docs, Drive, and Meet. This activity was designed so that participants not only understand the function of each application but also are able to integrate them into daily administrative activities. The training evaluation was conducted through pre- and post-tests, which showed a significant increase in participants' technical understanding. In addition to improving digital competency, this training also encouraged a shift in work culture towards a more collaborative, efficient, and data-driven one. The program's success demonstrates that digital transformation in educational environments can be achieved through an educational, participatory approach tailored to local needs. With positive results, this activity has the potential to be replicated in other educational institutions as a sustainable strategy for cloud-based administrative management. This training is proof that adopting digital technology in schools can strengthen administrative governance comprehensively and sustainably.
Co-Authors Capri, Hary DENI SETIAWAN Eko Riyanto Kharisma Wiati Gusti Musthofa Galih Pradana Neny Rosmawarni Niqotaini, Zatin Nurul Afifah Arifuddin Radinal Setyadinsa