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All Journal Jurnal Abdimas BSI: Jurnal Pengabdian Kepada Masyarakat Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Indonesian Journal on Software Engineering (IJSE) Jurnal Khatulistiwa Informatika Paradigma EVOLUSI : Jurnal Sains dan Manajemen Jurnal Teknologi Informasi dan Terapan (J-TIT) Indonesian Journal of Business Intelligence (IJUBI) JUSTIAN - Jurnal Sistem Informasi Akuntansi Indonesian Journal of Networking and Security - IJNS SPEED - Sentra Penelitian Engineering dan Edukasi Informatics and Computer Engineering Journal Jurnal Pengabdian Masyarakat Bangsa WASANA NYATA Kesejahteraan Bersama : Jurnal Pengabdian dan Keberlanjutan Masyarakat
Candra Agustina
Universitas Bina Sarana Informatika
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Optimalisasi Algoritma Random Forest Menggunakan SMOTE untuk Prediksi Pembatalan Tamu Hotel Agustina, Candra; Rahmawati, Eka
Evolusi : Jurnal Sains dan Manajemen Vol 12, No 2 (2024): Jurnal Evolusi 2024
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/evolusi.v12i2.23149

Abstract

The role of technology has simplified user access to various services, including hotel reservations. Technology has also made it easier for service providers to offer their products by showcasing hotel photos and specifications. However, the ease of making reservations aligns with the ease for users to cancel their hotel room bookings, which undoubtedly has a negative impact on hotel owners. To minimize losses, cancellation penalties and predictions regarding the likelihood of reservation cancellations can be implemented. Therefore, predicting hotel reservation cancellations has become crucial for hotel managers to reduce occupancy declines. One of the tools for prediction can be done through machine learning technology. The researcher utilized a hotel reservation dataset consisting of 18 attributes, which underwent data processing using the Random Forest algorithm, where the label attribute was the decision to cancel or not. In this study, the Random Forest algorithm was used without optimization, yielding an accuracy of 87.85%. Subsequently, the dataset, before being processed using Random Forest, underwent handling for imbalanced data using SMOTE. Through this method, the accuracy was enhanced by 2.46%, resulting in a final accuracy of 90.31%. Since the classification was only divided into 2 groups, SMOTE was performed only once to obtain a balanced data sample. This research contributes significantly to understanding the use of machine learning algorithms, particularly Random Forest, in addressing the challenges of imbalanced data in the case of predicting hotel reservation cancellations. The research highlights the potential of SMOTE as an effective tool in handling data imbalance, which can assist hotel managers and hospitality service providers in optimizing reservation management and improving room occupancy rates.
Penerapan Sistem Informasi Pembayaran Air Minum pada Penyediaan Air Minum dan Sanitasi Berbasis Masyarakat (Pamsimas) “Bersatu” Desa Candirejo Rahmawati, Eka; Agustina, Candra; Sardiarinto, Sardiarinto; Syukron, Akhmad
Jurnal Abdimas BSI: Jurnal Pengabdian Kepada Masyarakat Vol 7, No 1 (2024): Februari 2024
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jabdimas.v7i1.19975

Abstract

Program pengabdian kepada masyarakat telah dilaksanakan pada Penyediaan Air Minum dan Sanitasi Berbasis Masyarakat (Pamsimas) Bersatu Desa Candirejo yang terletak di Kecamatan Borobudur. Melalui program Pamsimas pemerintah Desa Candirejo membangun jaringan pipa air bersih untuk menjamin ketersediaan pasokan air warga. Dikenal dengan nama Pamsimas Bersatu, program ini disambut baik warga Desa. Namun pengelolaannya masih sangat terbatas, termasuk dalam sistem pembayaran. Semua proses dilakukan secara manual, dan masih dikerjakan oleh staf pemerintah Desa Candirejo. Dalam menjalankan sistem manual saat ini sering terjadi kesalahan seperti, terjadi selisih perhitungan uang yang diperoleh dengan catatan admin. Dari sisi pelanggan juga menunggu petugas memberikan lembar tagihan untuk dapat melakukan pembayaran, padahal saat ini petugas hanya ada 1 orang untuk menangani seluruh pelanggan. Oleh karena itu dibutuhkan sistem pembayaran yang lebih efektif dan efisien. Salah satu solusinya adalah dengan memanfaatkan Teknologi Informasi. Sistem dirancang menggunakan metode Scrum, kemudian di aplikasikan pada pengelolaan Pamsimas Bersatu. Aplikasi ini menampung data pelanggan, data tagihan dan data pembayaran. Outputnya berupa tagihan, nota pembayaran, dan laporan. Penggunaan sistem informasi pembayaran air minum ini pengelola lebih mudah dan cepat dalam melakukan pekerjaannya. Terlebih jumlah pelanggan yang terus bertambah, membutuhkan sistem yang dapat meminialisir kesalahan meskipun dengan sumber daya manusia yang terbatas. Hasil pelaksanaan program pengabdian menunjukan bahwa sistem dapat meningkatkan efisiensi dalam pengelolaan Pamsimas seperti input pelanggan, input meter, cetak tagihan, input pembayaran dan cetak laporan.
Strategi Digitalisasi Layanan Wisata Melalui Pengelolaan Website di Kampung VW Borobudur Rahmawati, Eka; Syukron, Akhmad; Agustina, Candra; Sulistyo, Gunawan Budi
Jurnal Pengabdian Masyarakat Bangsa Vol. 2 No. 9 (2024): November
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v2i9.1528

Abstract

Warisan budaya Candi Borobudur di Kecamatan Borobudur, Kabupaten Magelang, Jawa Tengah, telah menjadi daya tarik wisatawan domestik maupun mancanegara. Kunjungan yang terus meningkat setiap tahun mendorong wisatawan untuk mengeksplorasi wisata lain di sekitar Borobudur, termasuk keindahan alam pedesaan yang asri. Potensi wisata di sekitar kawasan Candi Borobudur pun terus dikembangkan, salah satunya adalah paket wisata trip dengan VW Safari. Kampung VW Borobudur merupakan paguyuban yang mengelola tur dengan VW Safari, menyediakan perjalanan wisata melintasi desa-desa dan objek wisata di sekitar Candi Borobudur. Namun, mitra mengalami kendala dalam pembuatan dan pengelolaan website VW Tour untuk memperluas jangkauan pemasaran. Untuk menanggapi permasalahan ini, tim pengabdian masyarakat memberikan solusi berupa pembuatan website. Selain itu, pelatihan pengelolaan website diberikan kepada anggota paguyuban agar mereka mampu menyajikan informasi terkait produk wisata secara mandiri. Diharapkan, dengan adanya website, mitra dapat lebih mudah menyajikan informasi dan wisatawan dapat lebih mudah mengakses informasi serta melakukan reservasi. Keluaran dari program ini berupa press release, website informasi, hak kekayaan intelektual, dan publikasi pada jurnal pengabdian masyarakat.
IMPLEMENTASI SMOTE DAN ALGORITMA MACHINE LEARNING UNTUK MENINGKATKAN AKURASI REKOMENDASI HOTEL Agustina, Candra; Rahmawati, Eka; Irawan, Denny; Tristanti, Vriska wahyu
Indonesian Journal of Business Intelligence (IJUBI) Vol 7, No 2 (2024): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v7i2.5141

Abstract

Pariwisata memiliki peran penting dalam perekonomian global, dengan destinasi seperti Candi Borobudur menarik berbagai jenis pengunjung. Untuk meningkatkan pengalaman wisatawan, rekomendasi hotel yang akurat menjadi sangat penting. Namun, data yang tidak seimbang, seperti ulasan positif yang terlalu dominan, sering kali mengurangi kinerja model machine learning yang digunakan untuk rekomendasi. Penelitian ini bertujuan untuk mengatasi masalah tersebut dengan menerapkan Synthetic Minority Over-sampling Technique (SMOTE) guna menyeimbangkan dataset dan meningkatkan akurasi rekomendasi hotel. Beragam algoritma machine learning, termasuk Random Forest, Support Vector Machines, dan Neural Networks, diterapkan dan dievaluasi. Hasil penelitian menunjukkan bahwa penerapan SMOTE secara signifikan meningkatkan kinerja semua model, dengan Random Forest memberikan hasil terbaik. Studi ini menunjukkan bahwa SMOTE, dalam kombinasi dengan teknik machine learning, memberikan solusi yang kuat terhadap ketidakseimbangan kelas pada sistem rekomendasi hotel, sehingga menghasilkan rekomendasi yang lebih andal dan relevan bagi wisatawan. Temuan ini memiliki implikasi penting bagi manajemen hotel dan sektor pariwisata secara keseluruhan.
Pengenalan Artificial Intelligence Pada Pondok Pesantren Yatim Al Ikhsan Surakarta Budi Al Amin; Candra Agustina; Wawan Haryanto; Galih Setiawan Nurohim
Kesejahteraan Bersama : Jurnal Pengabdian dan Keberlanjutan Masyarakat Vol. 1 No. 2 (2024): April: Kesejahteraan Bersama : Jurnal Pengabdian dan Keberlanjutan Masyarakat
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/bersama.v1i2.158

Abstract

Introduction and use of artificial intelligence (AI) technology is increasingly widespread in various aspects of human life. In the context of community service, AI has great potential to improve the quality of life of people through a variety of innovative applications. This article discusses how AI can be used in community service, including practical applications in the field of education. Student Data Management: Al Ihsan Foundation can use AI to manage orphan student data such as personal data, academic data, and health data. AI-supported data management systems can integrate this information better, thus enabling more personalized and customized services. Learning and Development: AI can be used to develop online learning platforms that are tailored to individual student learning needs. AI systems analyze student learning preferences and progress and recommend the most effective learning materials and methods. By leveraging AI, younger generations can create exciting, high-quality content without having to have specialized expertise in graphic design or video editing. For example, technologies such as Canva Magic Studio leverage artificial intelligence to make it easier to make exciting designs.The training aims to provide a better understanding to the younger generation of the basic concepts of AI and its applications in everyday life, including in the creation of creative digital content. Hopefully, with a better understanding of AI, the younger generation will be able to develop their creative potential and use it for a variety of positive purposes in their lives.
Analisis Sentimen pada Komentar YouTube terkait Pembahasan eSIM Menggunakan Metode Naive Bayes dan Random Forest Ardiansyah, Angga; Agustina, Candra; Maryani, Ina; Pribadi, Denny
Indonesian Journal on Software Engineering Vol 11, No 1 (2025): IJSE 2025
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/ijse.v11i1.26180

Abstract

Perkembangan teknologi komunikasi digital telah melahirkan inovasi baru seperti embedded SIM (eSIM), yang menawarkan kemudahan dalam pengelolaan identitas pelanggan seluler tanpa kartu fisik. Seiring meningkatnya adopsi teknologi ini, YouTube menjadi salah satu media diskusi publik yang ramai membahas eSIM melalui kolom komentar. Penelitian ini bertujuan untuk menganalisis sentimen masyarakat terhadap layanan eSIM berdasarkan komentar-komentar di video YouTube. Dengan menggunakan algoritma klasifikasi Naive Bayes dan Random Forest, sebanyak 324 komentar dikategorikan menjadi opini positif dan negatif. Proses penelitian mencakup tahapan pengumpulan data melalui teknik scraping, preprocessing teks, serta evaluasi model menggunakan metrik akurasi, presisi, recall, dan AUC. Hasil menunjukkan bahwa algoritma Naive Bayes mampu mencapai akurasi sebesar 98,52% dengan presisi tinggi terutama pada kelas negatif. Sementara itu, Random Forest menghasilkan akurasi lebih tinggi sebesar 99,69% dengan nilai AUC sempurna sebesar 1.000, mencerminkan performa optimal dalam membedakan sentimen komentar. Temuan ini menegaskan bahwa kedua algoritma efektif dalam klasifikasi sentimen teks, dengan Random Forest menunjukkan keunggulan performa. Penelitian ini dapat menjadi referensi bagi pengembangan analisis opini publik secara digital serta pemanfaatan machine learning dalam pemrosesan bahasa alami.               Kata kunci: Analisis Sentimen, Youtube, eSIM Abstract (10pt, italic, tebal, dan ditengah) The advancement of digital communication technologies has introduced new innovations such as the embedded SIM (eSIM), which provides users with flexibility in managing their mobile identity without the need for a physical SIM card. As the adoption of this technology increases, YouTube has become a prominent platform where public discussions regarding eSIM occur through comment sections. This study aims to analyze public sentiment towards eSIM services based on comments posted on YouTube videos. Utilizing the Naive Bayes and Random Forest classification algorithms, a total of 324 comments were categorized into positive and negative sentiments. The research process involved data collection through web scraping, text preprocessing, and model evaluation using metrics such as accuracy, precision, recall, and AUC. The results show that the Naive Bayes algorithm achieved an accuracy of 98.52%, with particularly high precision for the negative class. Meanwhile, the Random Forest algorithm yielded even higher accuracy at 99.69%, with a perfect AUC score of 1.000, indicating outstanding performance in distinguishing between sentiment classes. These findings affirm the effectiveness of both algorithms in sentiment text classification, with Random Forest demonstrating superior performance. This research contributes as a reference for further applications of public opinion analysis in digital media and the implementation of machine learning in natural language processing.Keywords: Sentiment Analysis, Youtube, eSIM
Enhance Artificial Intelligence Literacy for Islamic Boarding School Students Using the Asset Based Community Development Method Setyadi, Heribertus Ary; Agustina, Candra; Haryanto, Wawan; Rousyati, Rousyati
WASANA NYATA Vol 9, No 1 (2025)
Publisher : STIE AUB Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36587/wasananyata.v9i1.1970

Abstract

Use of artificial intelligence (AI) in teaching and learning has become an increasingly important topic in modern education context. AI offers a wide range of potential to enhance students' learning experiences through better personalization and adaptation to individual needs. From initial observations in several Islamic boarding schools in Banjarsari Surakarta, it was found that understanding of students and teachers about AI and AI supporting applications was still lacking. As part of efforts to improve education quality and community readiness to face a digital era, Bina Sarana Informatika University, Surakarta City Campus, took an initiative to implement a community service program in form of training on using AI in education for students. Community service method used in this activity is the Asset Based Community Development (ABCD) approach which aims to empower communities by utilizing existing potential and resources. Implementation stages include needs analysis (Discovery), expectations formulation (Dream), design of training modules (Design), finalization of plans with FGD (Define), and training implementation (Destiny). AI workshop for Islamic boarding schools has been successfully implemented with good results. From questionnaires that have been filled out by all participants, it shows that workshop materials presented are very useful, materials and tutors delivery method are satisfactory. Workshop participants who are satisfied or rate it good are 63% and those who rate it as very satisfied or very good are 32%.
Co-Authors - Amik BSI Yogyakarta, Gunawan Budi S Akhmad Syukron Akrom, Akrom Angga Ardiansyah Budi Al Amin Budi Al Amin eka rahmawati F Febiyanti Galih Setiawan Nurohim Gunawan Budi Sulistyo Haryanto, Wawan Hendri Hermawan Adinugraha Heribertus Ary Setyadi Irawan, Denny Maryani, Ina Nani Purwati Pribadi, Denny Rahmawati-Universitas Bina Sarana Informatika, Eka Rousyati, Rousyati Sardiarinto Sardiarinto Sri Mulyani Tri Wahyudi - AMIK BSI Yogyakarta Tri Wahyudi - AMIK BSI Yogyakarta Tristanti, Vriska wahyu Wahyu Setyo Prabowo Wawan Haryanto