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All Journal Jurnal Sustainable: Jurnal Hasil Penelitian dan Industri Terapan Jurnal Imiah Pengabdian Pada Masyarakat (JIPM) SISFOTENIKA
Nadia Ayu Putri Priyani
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Religion Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

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Information System for AK1 Management and Job Vacancies (Case Study: Diskominfo Tanjungpinang City) Magfira, Fortia; Nadia Ayu Putri Priyani; Adinda
SISFOTENIKA Vol. 15 No. 2 (2025): SISFOTENIKA
Publisher : STMIK PONTIANAK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30700/sisfotenika.v15i2.558

Abstract

Digital transformation is a strategic effort to improve the quality of public services in the era of information technology, including in the employment sector. The Tanjungpinang City Manpower Office (Disnaker) faces various challenges in managing job seeker and job vacancy data due to the use of manual systems that are still inefficient. To answer these problems, a web-based Disnaker Admin System was developed using the Laravel framework which aims to facilitate the management of AK1 (yellow card) administration, job seeker data, companies, and job vacancy information. The testing process was carried out using the User Acceptance Testing (UAT) method and involved periodic reviews by the Tanjungpinang City Communication and Informatics Office (Diskominfo) to ensure the suitability of the system with the needs and standards of digital public services. Diskominfo plays an active role as a development partner and supervisor in ensuring that this digital transformation runs according to the direction of local government policy. The implementation results show that this system is able to improve admin work efficiency, accelerate the service process, improve data accuracy, and support more modern and integrated employment data management. Thus, this system provides a real contribution in supporting digital transformation and improving the quality of public services in the employment sector, while strengthening cross-agency collaboration in developing regional information technology solutions.
KLASIFIKASI JENIS POHON MANGROVE BERDASARKAN CITRA DAUN MENGGUNAKAN METODE K-NEAREST NEIGHBOUR (KNN) Irfan Ibrahim; Maulana Fitra Ramadhani; Muhammad Ridho; M. Wisnu Adjie Pramudya; Putri Suci Renita; Apriliani Putri; Nadia Ayu Putri Priyani; Seffi Rozahana; Adinda; Nurul Hayaty
Sustainable Vol 13 No 2 (2024): Jurnal Sustainable : Jurnal Hasil Penelitian dan Industri Terapan
Publisher : Fakultas Teknik Universitas Maritim Raja Ali Haji

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31629/h45hyv18

Abstract

Studi ini dilakukan untuk mengimplementasikan algoritma KNN (K-Nearest Neighbour) dalam klasifikasi bakau menggunakan citra daun. Penelitian ini menggunakan 1.550 data citra daun Mangrove dengan menggunakan python dibagi menjadi empat kelas oleh Avicennia alba, Bruguiera gymnorrhiza, Rhizophora apiculata dan Sonneratia alba. Tingkat keberhasilan klasifikasi yang dicapai oleh sistem menggunakan metode K-Nearest Neighbour mencapai 93,75% dengan nilai k = 3. Hasil penelitian ini menunjukkan bahwa model KNN bisa mengklasifikasi jenis Avicennia alba dan Sonneratia alba dengan jelas, namun terdapat sedikit kesalahan dalam spesies Bruguiera gymnorrhiza dan Rhizophora apiculata karena memiliki kemiripan ciri tekstur antara satu dengan yang lain.
SISTEM KLASIFIKASI JENIS KERANG BERDASARKAN CITRA CANGKANG MENGGUNAKAN SUPPORT VECTOR MACHINE (SVM) Adinda; Seffi Rozahana; Nadia Ayu Putri Priyani; Apriliani Putri; Irsyad Widiansyah; Nurul Hayaty
Sustainable Vol 13 No 2 (2024): Jurnal Sustainable : Jurnal Hasil Penelitian dan Industri Terapan
Publisher : Fakultas Teknik Universitas Maritim Raja Ali Haji

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31629/hdnn8e89

Abstract

This study aims to build an automatic classification system to identify shellfish types based on shell images by applying the Support Vector Machine (SVM) algorithm. This study classifies three types of shellfish, namely blood cockles with the scientific name Anadara granosa, green mussels (Perna viridis), and scallops (Amusium pleuronectes). Image data was obtained from the internet and each class consisted of 150 images, so the total dataset was 450 images. The research stages include image pre-processing to normalize image size and quality, feature extraction to obtain visual information in the form of texture (with GLCM), color (RGB histogram), and shape (Canny edge detection), and classification using SVM. This application is web-based and functions to receive uploaded shellfish images from users and provide automatic shellfish type recognition results. The test results show that the developed SVM model is able to classify shellfish types with high accuracy, reaching 93,83%. This research is expected to contribute to the development of digital shellfish species identification technology to support the fields of fisheries, marine resource conservation, and marine biota research. 
Peran Mahasiswa KKN dalam Meningkatkan Kesadaran Pendidikan Masyarakat untuk Menekankan Angka Putus Sekolah di Desa Nosari Barat, Kecamatan Bintan Timur, Kabupaten Bintan M. Pemberdi Intasir; Anggi Octa Hendriawan; Gustia Andini; Said Muhamad Ahyar; Muhamad Aldo Wirawan; Nadia Ayu Putri Priyani; Delvina Dea Anisa; Damayanti Simangunsong; Syafiq Maulana; Daniesa Aryanti; Destri Mardina
Jurnal Imiah Pengabdian Pada Masyarakat (JIPM) Vol 3 No 1 (2025): Juli - September
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The Community Service Program (KKN) in Nosari Barat Village, East Bintan District, was initiated due to the high risk of school dropouts caused by the low learning interest among children and adolescents. Economic limitations, lack of awareness of the importance of education, and insufficient motivation from the environment were identified as major contributing factors. The program applied a participatory approach through socialization, interactive lectures, motivational video screenings, and group discussions with children, parents, and the community. The results revealed an increase in educational awareness, stronger motivation among children to continue schooling, and greater parental involvement in supporting learning. This program highlights the significant role of KKN students as agents of change in reducing dropout rates. In conclusion, educational socialization activities effectively foster community awareness and should be sustained to ensure long-term impact.
Co-Authors Adinda Anggi Octa Hendriawan Apriliani Putri Damayanti Simangunsong Daniesa Aryanti Delvina Dea Anisa Destri Mardina Fortia Magfira Gustia Andini Hayaty, Nurul Irfan Ibrahim Irsyad Widiansyah M. Pemberdi Intasir M. Wisnu Adjie Pramudya Maulana Fitra Ramadhani Muhamad Aldo Wirawan Muhammad Ridho Putri Suci Renita Said Muhamad Ahyar Seffi Rozahana Syafiq Maulana