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All Journal INTEGER: Journal of Information Technology Network Engineering Research Operation [NERO] Prosiding Seminar Nasional Sains dan Teknologi Terapan JURIKOM (Jurnal Riset Komputer) International Journal of Management Science and Information Technology (IJMSIT) Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) Jurnal Ilmu Komputer dan Sistem Informasi Jurnal Pengabdian Masyarakat
Sulistyowati Sulistyowati
Institut Teknologi Adhi Tama Surabaya
Religion Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Library & Information Science Social Sciences

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Penerapan Metode K-NN untuk Klasifikasi Pencari Kerja pada Dinas Tenaga Kerja Budanis Dwi Meilani; Mochammad Reza Dwi Afriansyah; Sulistyowati Sulistyowati; Zuli Maulidati; Resa Uttungga
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 5 No. 2 (2025): Mei 2026
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v5i2.328

Abstract

The Pasuruan Manpower Office is one of the agencies that tries to assist companies in the selection process for job seekers who match the criteria for available job vacancies. A common problem in the Job Placement section is the inefficiency in determining suitable job classifications for job seekers. In addition to the lack of human resources in the job selection process, there is also no system that helps the workforce sector in selecting suitable jobs for job seekers. The purpose of this study is to design and analyze a system that can assist the Pasuruan Regency Manpower Office in finding Fields / Classes in Placement according to the criteria of job seekers. The job seeker criteria used are Education Level, Work Experience, Language Proficiency, Last Educational Grade, Major, Expertise, and Training Certificate. The method used in this study is the K-NN method. The K-NN method is a method for classifying objects based on learning data that is closest to the object, by selecting the appropriate K data can be classified based on the nearest neighbor. From the results of the tests carried out 12 times on the testing system against 50 data with training data parameters of 25 data to 50 data and the K values ​​used were 1, 2, 3, 4, 5 and 6, the average classification had an accuracy value of 81.17% and an error value of 18.87%.
Peningkatan Kompetensi Siswa SMK Melalui Pelatihan Konsep Relational Database dan SQL Dasar Sulistyowati Sulistyowati; Budanis Dwi Meilani; Zuli Maulidati; Ruli Utami; Resa Uttungga
Jurnal Pengabdian Masyarakat Vol. 5 No. 1 (2026): Juni 2026
Publisher : Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/japamas.v5i1.322

Abstract

Penguasaan konsep relational database dan Structured Query Language (SQL) merupakan kompetensi fundamental dalam pendidikan vokasi bidang teknologi informasi. Berbagai studi pengabdian masyarakat menunjukkan bahwa lulusan SMK masih menghadapi kesenjangan antara kompetensi yang dipelajari di sekolah dan kebutuhan industri berbasis data. Hasil evaluasi awal melalui pre-test pada siswa SMK Negeri 10 Surabaya menunjukkan bahwa tingkat pemahaman awal siswa terhadap relational database dan SQL masih rendah, dengan skor rata-rata 45–52 pada aspek konsep database, struktur tabel dan relasi, query SQL dasar, serta operasi CRUD. Kondisi ini berpotensi menghambat proses pembelajaran lanjutan dan kesiapan kerja lulusan. Kegiatan pengabdian kepada masyarakat ini bertujuan meningkatkan pemahaman konseptual dan keterampilan praktis siswa melalui pelatihan relational database dan SQL dasar berbasis praktik dengan pendekatan learning by doing. Metode evaluasi menggunakan pre-test dan post-test. Hasil menunjukkan peningkatan skor rata-rata menjadi 78–85 pada seluruh aspek penilaian. Temuan ini menunjukkan bahwa pelatihan berbasis praktik efektif dalam meningkatkan kompetensi vokasi siswa dan dapat menjadi model penguatan pembelajaran di SMK.
Pelatihan UI/UX Berbasis Proyek dalam Pengembangan Portofolio Digital Menggunakan Figma untuk Siswa SMK Zuli Maulidati; Resa Uttungga; Anwar Sodik; Rachman Arief; Sulistyowati Sulistyowati; Adib Pakarbudi
Jurnal Pengabdian Masyarakat Vol. 5 No. 1 (2026): Juni 2026
Publisher : Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/japamas.v5i1.324

Abstract

Transformasi digital turut meningkatkan kebutuhan akan kompetensi di bidang User Interface (UI) dan User Experience (UX) sebagai bagian penting dalam pengembangan produk digital. Dalam konteks pendidikan vokasi, kompetensi ini tidak cukup hanya dipahami secara konseptual, tetapi juga perlu diwujudkan melalui keterampilan implementatif yang dapat ditunjukkan dalam bentuk karya nyata seperti portofolio digital. Berangkat dari kondisi tersebut, kegiatan pengabdian kepada masyarakat ini dirancang untuk memberikan pengalaman belajar yang lebih aplikatif melalui pengembangan dan implementasi model pelatihan UI/UX berbasis proyek. Kegiatan dilaksanakan pada Januari – Februari 2026 dengan pendekatan Project-Based Learning yang disusun dalam empat tahapan, yaitu pemahaman konseptual, penguasaan perangkat/tools, pengembangan proyek, serta evaluasi dan umpan balik. Evaluasi dilakukan melalui pre-test dan post-test, observasi, serta analisis hasil desain siswa. Hasil menunjukkan adanya peningkatan pemahaman siswa, meningkatnya keterlibatan selama pembelajaran, serta peningkatan kemampuan menghasilkan portofolio digital yang lebih terstruktur dan sesuai dengan prinsip dasar UI/UX.
AI-Based Data Engineering Model for Adaptive Billing Systems in Digital Economy Monetization Sulistyowati Sulistyowati; Fitriyani Fitriyani; Zikrul Khalid
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.7789

Abstract

This research aims to develop an AI-driven data engineering model tailored for adaptive billing systems in the realm of digital economy monetization. As digital services evolve, traditional billing mechanisms often struggle to accommodate the varied demands of users. The model proposed integrates user profiles, transaction histories, and payment patterns, facilitating precise cost assessments that respond dynamically to user behaviors. A descriptive qualitative methodology was employed, concentrating on the framework of the model, system workflows, and essential analytical functions. Findings indicate that this approach enhances both accuracy and transparency in billing processes while fostering stronger relationships between businesses and their clients. By utilizing artificial intelligence, the system adapts to shifts in consumption patterns, identifies anomalies, and adjusts pricing based on real-time usage. These insights lay the groundwork for developing more agile and efficient billing solutions, offering a practical roadmap for digital enterprises aiming to optimize revenue management based on service utilization.
Co-Authors Abdul Kholiq Al Anam Amalia Anjani Arifiyanti Andi Wijaya Andy Rachman Anggi Yhurinda Perdana Putri Anwar Sodik, Anwar Bagus Eko Prasetyo Basma Eno Ketherin Bayu Fahmi Agustin Budanis Dwi Meilani Dynda Cendikya Di Putri Edy Santoso Fitriyani Hendra Thesna Prayoga Hendro Nugroho Ilham Agus Mardiko Isa Albanna Isa Albanna M. Anandi Ferdiansyah Mochammad Reza Dwi Afriansyah Muhammad Ainul Rozi Nanang Fakhrur Rozi Pakarbudi, Adib Pascal Brilliandy Kristianto Pratama Sandi Alala Pratama Sandi Alala Putri, Anggi Yhurinda Perdana Rachman Arief Resa Uttungga Ridlwan Rabbani Nugroho Ruli Utami, Ruli Shah Khadafi Wahyu Widodo Yanuar Efendi Zikrul Khalid Zuli Maulidati