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All Journal Jurnal Riset Rumpun Ilmu Hewani (JURRIH) Jurnal Ilmu Komputer dan Informatika SULIWA: Jurnal Multidisiplin Teknik, Sains, Pendidikan dan Teknologi
Risni Stefani
Institut Teknologi Alberth Foenay Kupang, Indonesia
Agriculture, Biological Sciences & Forestry Computer Science & IT Electrical & Electronics Engineering Engineering Mathematics

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SISTEM PAKAR DIAGNOSA PENYAKIT PADA IKAN KOI MENGGUNAKAN METODE BACKWARD CHAINING Risni Stefani
JURNAL RISET RUMPUN ILMU HEWANI Vol. 1 No. 2 (2022): Oktober : Jurnal Riset Rumpun Ilmu Hewani
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (868.495 KB) | DOI: 10.55606/jurrih.v1i2.526

Abstract

Penyakit ikan Koi merupakan suatu kendala atau faktor resiko bagi para peternak ikan Koi yang menyebabkan kerugian ekonomis dan menurunnya produksi ikan Koi yang dipelihara. Untuk itu diperlukan suatu perangkat lunak untuk membantu para peternak ikan Koi dalam menangani penyakit pada ikan koi. Saat ini para peternak ikan koi masih berkendala dalam penanganan gejala penyakit yang dilakukan secara manual dengan bertanya jawab bersama pakar ikan. Untuk itu tujuan dari penelitian ini merancang aplikasi sistem pakar diagnosa penyakit pada ikan koi menggunakan metode backward chaining dalam menangani penyakit pada ikan koi. Metode yang dibangun untuk penelitian ini menggunakan beberapa tahapan penelitian dengan melakukan pengumpulan data, proses desain, proses pengkodean dan proses pengujian sistem, proses perancangan aplikasi menggunakan, Visual Studio 2010.net. Hasil yang diperoleh dari penelitian ini adalah suatu aplikasi sistem pakar diagnosa penyakit ikan koi dengan menggunakan metode backward chaining yang dapat menyelesaikan masalah yang dihadapi oleh para peternak ikan koi dan sekaligus membantu para pakar untuk memberikan hasil solusi yang lebih singkat dan tidak memakan waktu.
RANCANG BANGUN SISTEM INFORMASI MANAJEMEN PENCARIAN RUMAH KOST BERBASIS WEB DI DESA PENFUI TIMUR KABUPATEN KUPANG Cyrillus Yuda Mardiyanto Pike; Mohamad Iqbal Ulumando; Risni Stefani
SULIWA: Jurnal Multidisiplin Teknik, Sains, Pendidikan dan Teknologi Vol. 3 No. 2 (2026): SULIWA: Jurnal Multidisiplin Teknik, Sains, Pendidikan dan Teknologi, Juli 2026
Publisher : LEMBAGA KAJIAN PEMBANGUNAN PERTANIAN DAN LINGKUNGAN (LKPPL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62671/suliwa.v3i2.283

Abstract

Advances in information technology offer opportunities to improve the efficiency of data management and information delivery, including in the area of ​​boarding house rentals. In Penfui Timur Village, Kupang Regency, the process of searching for and managing boarding houses is still carried out conventionally, making it less effective in providing fast and accurate information. This research aims to design and build a web-based boarding house search and management information system to facilitate access to information for prospective tenants and assist boarding house owners in managing data in a more structured manner. The method used is the waterfall software development model, which includes the stages of needs analysis, design, implementation, testing, and maintenance. The system was developed using the PHP programming language and a MySQL database and can be accessed through a web browser. The results show that the system is capable of providing boarding house information quickly, structured, and easily accessible. Furthermore, the system helps boarding house owners manage data more effectively than manual methods. Based on testing results, all system features function properly, making this system a potential solution for improving the effectiveness of boarding house information management and delivery.
Sistem Informasi Inventaris Barang Berbasis WEB Pada Institut Teknologi Alberth Foenay Kupang Merlin K. Talnoni; Mohamad Iqbal Ulumando; Risni Stefani
Jurnal Ilmu Komputer dan Informatika | E-ISSN : 3063-9026 Vol. 2 No. 4 (2026): April - Juni
Publisher : GLOBAL SCIENTS PUBLISHER

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

Abstract

Inventory management is a crucial aspect in supporting the smooth running of academic activities at universities. The Alberth Foenay Institute of Technology (ITAF) Kupang has a significant amount of assets, necessitating a structured, accurate, and easily accessible inventory system. This study aims to design and build a web-based inventory information system to improve the effectiveness and efficiency of campus inventory data management. The research method used is a qualitative method with observational data collection techniques, while the software development method applied is the Waterfall approach. The developed system provides data management features for goods, incoming goods, outgoing goods, warehouses, types of goods, units, and a dashboard as an information center. The results show that the web-based inventory system can facilitate faster, more accurate, and more integrated data collection, stock monitoring, and inventory reporting. With this system, inventory management at ITAF Kupang has become more organized, efficient, and easily accessible.
KLASIFIKASI CALON TOP SCORER TURNAMEN SEPAK BOLA ASEAN CHAMPIONSHIP 2026 (AFF CUP) MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE BERDASARKAN DATA STATISTIK PERFORMA PEMAIN Mohamad Iqbal Ulumando; Orry Adrian Mokola; Risni Stefani
SULIWA: Jurnal Multidisiplin Teknik, Sains, Pendidikan dan Teknologi Vol. 3 No. 3 (2026): SULIWA: Jurnal Multidisiplin Teknik, Sains, Pendidikan dan Teknologi, Nopember
Publisher : LEMBAGA KAJIAN PEMBANGUNAN PERTANIAN DAN LINGKUNGAN (LKPPL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62671/suliwa.v3i3.312

Abstract

The 2026 ASEAN Championship (AFF Cup) is a prestigious football tournament in Southeast Asia that consistently captures public interest, particularly regarding the identification of potential top scorers. Historically, identifying these candidates has relied on subjective observation rather than data-driven analysis. This study aims to apply the Support Vector Machine (SVM) algorithm to classify potential top scorers based on performance statistics—specifically goals, shots, and assists—recorded over the past year. Secondary data was utilized, comprising five potential players from each of the ten participating nations, resulting in a dataset of 50 players. The research process involved data collection, preprocessing, Min-Max normalization, class label assignment, splitting the data into training and testing sets (80:20 ratio), applying the SVM algorithm, and evaluating the model using a confusion matrix, accuracy, precision, recall, and F1-score. The results indicate that the SVM algorithm successfully classified 17 players into Class A (High Potential to be Top Scorer), 17 players into Class B (Potential to be Top Scorer), and 16 players into Class C (Low Potential to be Top Scorer). Model evaluation yielded an accuracy of 60.00%, demonstrating the SVM algorithm's ability to objectively classify potential top scorers based on performance statistics. This study is expected to serve as a reference for developing machine learning-based football performance analysis and to support the identification of potential top scorers prior to the tournament.
Co-Authors Cyrillus Yuda Mardiyanto Pike Merlin K. Talnoni Mohamad Iqbal Ulumando Orry Adrian Mokola