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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer E-Dimas: Jurnal Pengabdian kepada Masyarakat JAST : Jurnal Aplikasi Sains dan Teknologi Jurnal Penelitian dan Pengabdian Kepada Masyarakat UNSIQ JURIKOM (Jurnal Riset Komputer) Jurnal ICT : Information Communication & Technology Bantenese Jurnal Pengabdian Masyarakat Jurnal Mnemonic JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Computer Science and Information Technology (CoSciTech) Media Jurnal Informatika Jurnal Difusi Industrial Research Workshop and National Seminar Journal of Applied Islamic Economics and Finance Jurnal AbdiMU Jurnal Penjaminan Mutu
Wisnuadhi, Bambang
Politeknik Negeri Bandung
Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Social Sciences Other

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PENGEMBANGAN DAN PELATIHAN MODUL VERIFIKASI BMD PADA APLIKASI DIARVIS-BMD DI PEMERINTAH KABUPATEN BANDUNG Wisnuadhi, Bambang; Munawar, Ghifari; Alifi, Muhammad Riza; Arsyad, Zulkifli; Wirasta, Wendi
Jurnal Penelitian dan Pengabdian Kepada Masyarakat UNSIQ Vol 11 No 01 (2024): Januari
Publisher : Lembaga Penelitian, Penerbitan dan Pengabdian Masyarakat (LP3M) UNSIQ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32699/ppkm.v11i01.5844

Abstract

Aplikasi Diarvis-BMD telah dikembangkan sebagai media perekam data barang milik daerah (BMD) untuk membantu pelaksanaan sensus BMD di Pemerintah Kabupaten Bandung. Aplikasi ini telah digunakan oleh 66 SKPD mulai Dinas Pendidikan, Dinas Kesehatan, Dinas PUTR, Dinas Pariwisata dan Kebudayaan hingga ke Kecamatan. Secara umum alur pelaksanaan sensus BMD dibagi menjadi tiga tahapan, yakni tahap pelabelan dan sensus aset BMD, tahap verifikasi hasil sensus BMD, dan tahap pelaporan aset BMD. Versi awal aplikasi Diarvis-BMD baru dikembangkan sampai dengan tahapan pelabelan dan sensus aset BMD. Oleh karenanya di tahun 2023 ini, tim mengusulkan program PkM untuk mengembangkan modul verifikasi BMD dan modul pelaporan di aplikasi Diarvis-BMD serta memberikan pelatihan penggunaan aplikasinya. Pengguna aplikasi terbagi menjadi tiga peran, yaitu operator, verifikator 1, dan verifikator 2. Teknologi yang digunakan sebagai dasar pengembangan aplikasinya adalah web framework Laravel dengan bahasa pemrograman PHP dan database PostgreSQL. Modul yang telah dikembangkan kemudian dievaluasi oleh pengguna melalui kuesioner dan hasilnya menunjukkan penilaian yang positif.
Rekomendasi Fitur yang Mempengaruhi Harga Sewa Menggunakan Pendekatan Machine Learning Wisnuadhi, Bambang; Setiawan, Irwan
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 4: Agustus 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021843305

Abstract

Perkembangan Teknologi Infromasi, internet, dan perangkat bergerak telah mengubah perilaku konsumen dalam menjalankan aktivitasnya. Hal ini direspon oleh industri dengan menyediakan berbagai aplikasi berbasis web dan perangkat bergerak dalam interaksinya dengan pelanggan. Salah satu industri yang beradaptasi dengan perubahan teknologi dan perilaku konsumen ini adalah industri pariwisata dan perhotelan. Kebutuhan konsumen yang sebelumnya menggunakan akomodasi wisata tradisional seperti hotel, berubah menjadi lebih memilih rumah-rumah penduduk disekitar tempat wisata sebagai tempat penginapan sementara wisatawan. Perubahan ini berdampak kepada semakin banyaknya properti pribadi yang disewakan sehingga menyebabkan persaingan harga sewa. Harga sewa merupakan salah satu faktor penting yang dipertimbangkan calon penyewa dalam menentukan properti yang akan disewanya. Hal ini tentunya membuat para pemiliki properti harus memikirkan strategi penentuan harga sewa agar propertinya laku dipasaran. Penelitian ini bertujuan untuk mendapatkan fitur apa saja yang dapat mempengaruhi penentuan harga sewa properti berdasarkan data pengguna Airbnb di Berlin. Data penelitian diambil dari dataset yang disediakan oleh InsideAirbnb berupa file dengan format CSV. Penelitian dilakukan menggunakan teknik machine learning dengan pendekatan algoritma XGBoost. Terdapat lima tahapan pengerjaan dalam penelitian ini, yaitu data understanding, data pre-processing, exploratory data analysis, pemodelan, dan insights. Hasil yang didapatkan dari penelitian ini adalah room type private room, room type entire home/apt, dan cancellation policy super strict 60 days merupakan tiga fitur tertinggi yang mempengaruhi penentuan harga sewa. Luas properti menempati urutan keempat berdasarkan rekomendasi algoritma yang diterapkan. AbstractThe development of information technology, the internet, and mobile devices has changed the behavior of consumers in carrying out their activities. The industry responded by providing various web-based and mobile applications in their interactions with customers. The tourism and hospitality industry is adapting to changes in technology and consumer behavior. The needs of consumers who previously used traditional tourist accommodations such as hotels have changed to prefer residents' houses around tourist attractions as their temporary lodging. This change has an impact on the increasing number of private properties being leased, causing competition in rental prices. It is undeniable that the rental price is one of the essential factors that prospective tenants consider in making choices. This certainly makes property owners, who will rent out their properties, have to think about rental pricing strategies. This study aims to obtain any features that affect pricing based on Airbnb user data in Berlin. The study was conducted using machine learning techniques with the XGBoost algorithm approach. There are five stages of work in this study, namely understanding data, pre-processing data, exploratory data analysis, modeling, and insights. The results obtained from this study are room type private room, room type entire home / apt, and cancellation policy type super strict 60 are the three highest features that affect price determination. Property size ranks fourth based on algorithmic recommendations.
Optimizing Function Point Analysis in Moodle: A Plugin-Based Solution for Automated Grading and Student Assessment Firdaus, Lukmannul Hakim; Wisnuadhi, Bambang; Rahmani, Ani
Media Jurnal Informatika Vol 17 No 1a (2025): Special Issue Information System Media Jurnal Informatika
Publisher : Teknik Informatika Universitas Suryakancana Cianjur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/mji.v0i0.5758

Abstract

Learning Management Systems (LMS), especially Moodle, have become integral tools in modern education, enabling efficient management of teaching materials, assignments, and assessments. This study aimed to develop and integrate a Moodle plugin for automating Function Point (FP) calculations, a method used in software engineering education to estimate development complexity. The research focused on creating an Activity Module plugin that automates the FP calculation process, reduces manual grading efforts, and provides immediate feedback to students. The plugin underwent functional testing, including Requirement Verification, UI Testing, Integration Testing, and Output Validation, to assess its performance. The results demonstrated that the plugin successfully automated the calculation of Unadjusted Function Points (UFP) and Value Adjustment Factor (VAF), with accurate results and seamless integration into Moodle’s core modules such as assignment creation, grading, and user management. Testing confirmed that the plugin met all functional requirements, and the UI and integration worked as intended. The study concluded that the FP plugin is a viable alternative to traditional FP instruction, delivering time saved, error reduction, and reduced manual grading effort. Limitations of the study include the small-scale testing, and future research should focus on evaluating scalability for larger classes and assessing its impact on student learning outcomes. Further development could explore integrating advanced features like analytics and AI-assisted feedback to enhance the learning experience.
Co-Authors Ade Chandra Nugraha Ahmad Wibawa, Aldira Aldy Akbarrizky Alfian, Hadi Ani Rahmani Ardhian Ekawijana Arsyad, Zulkifli Asri Maspupah Cholid Fauzi Dimas Sumitra Danisworo Dimas Sumitra Danisworo Dimas Sumitra Danisworo Firdaus, Lukmannul Hakim Gelar, Trisna Ghifari Munawar Hasbi Assidiki Mauluddi Haya Utami Lutfi IRWAN SETIAWAN Joe Lian Min Jonner Hutahaean Karnawati, Hennidah Kristianingsih, Kristianingsih Lian Min, Joe Lukmannul Hakim Firdaus Lukmanul Hakim Firdaus Mauludi , Hasbi Assidiki Mayasari, Ine Muhammad Afif Muzakki Muhammad Azra Sabila Muhammad Riza Alifi Muhammad Rizqi Sholahuddin Muhammad Zidan, Rakarizal Mumuh Kustino Muharram Niko Sumanda Sibarani Purwihartuti, Koernia Rahil Jumiyani Rahmani, Ani Said Al Fakhri Santi Sundari Sari, Aprianti Nanda Setiawan Setiawan Setiawan Setiawan Siti Dwi Setiarini Syakrani, Nurjannah Tiafahmi Angestiwi Wendi Wirasta Wira Kusuma Wardana Wulan, Sri Ratna YAYAN FIRMANSYAH, YAYAN Zikri Ariachandra [1] S. Peltonen, L. Mezzalira, and D. Taibi, “Motivations, benefits, and issues for adopting Micro-Frontends: A Multivocal Literature Review,” Inf Softw Technol, vol. 136, Aug. 2021, doi: 10.1016/j.infsof.2021.106571. [2] Y. Prajwal, J. Viren Parekh,