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All Journal Jurnal Teknologi dan Manajemen Informatika Jurnal Simantec DINAMIKA DOTCOM INFORMAL: Informatics Journal Proceeding SENDI_U SMATIKA Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Informatika dan Multimedia JEEMECS (Journal of Electrical Engineering, Mechatronic and Computer Science) SENTIA 2016 Jurnal Teknologi Informasi dan Terapan (J-TIT) Jurnal Jaringan Telekomunikasi International Conference on Industrial Revolution for Polytechnic Education Asian Journal Science and Engineering Seminar Nasional Ilmu Terapan Pangripta Jurnal Ilmiah Kajian Perencanaan Pembangunan Jurnal Informatika Polinema (JIP) Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research Jurnal Pengabdian Kepada Masyarakat Journal of Evrimata: Engineering and Physics
Yan Watequlis Syaifudin
Politeknik Negeri Malang
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Social Sciences Other

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Journal : INFORMAL: Informatics Journal

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Prediksi Kuantitas Hasil Budidaya Ikan Konsumsi Menggunakan Penerapan Metode Regresi Data Syaifudin, Yan Watequlis; Al Masyriqi, Syifa’ul Ikrom Syifa’ul Ikrom; Saputra, Pramana Yoga; Fatmawati, Triana
INFORMAL: Informatics Journal Vol 9 No 1 (2024): INFORMATICS JOURNAL (INFORMAL)
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v9i1.43292

Abstract

In the present era, the industrial 4.0 revolution marks technological advancements in the fisheries sector, making fish farming industries increasingly effective and efficient. Predictions related to future fish harvest production can be used as considerations in planning. This research aims to build a prediction system for fish farming harvests by comparing four regression methods: linear regression, polynomial regression, random forest regression, and support vector regression to obtain accurate predictions. With the existence of this harvest prediction system, it is expected to provide information about the quantity of future harvests, enabling harvest partners to take appropriate steps to enhance their profitability. Based on the research results, the best regression model is polynomial regression. This model yields an average Root Mean Square Error (RMSE) value of 4.39 and an average Mean Absolute Percentage Error (MAPE) value of 0.41%. This indicates that the regression model has good and accurate prediction capabilities.
Penggunaan Metode Analisis Data Untuk Rekomendasi Menu Makanan Berdasarkan Persediaan Bahan dan Preferensi Pengguna Syaifudin, Yan Watequlis; Ardyningrum, Nabilah Argyanti
INFORMAL: Informatics Journal Vol 9 No 1 (2024): INFORMATICS JOURNAL (INFORMAL)
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v9i1.43263

Abstract

Cooking represents a significant and enjoyable activity, enabling individuals to create delectable dishes. However, the challenge of discovering recipes that align with available ingredients and personal preferences persists. To tackle this issue, a recommendation system is introduced, employing a content-based filtering approach that utilizes Jaccard similarity to harness users' ingredient ownership. Additionally, an item-based collaborative filtering approach employing cosine similarity is utilized to propose recipes based on user preferences and those of fellow users. This comprehensive approach delivers precise and pertinent recipe recommendations, optimizing ingredient utilization and elevating the cooking experience. Furthermore, the assessment of recommendations based on user preferences reveals varying outcomes.
Co-Authors Abdullah, Zaed Achmad, Ence Adevian Fairuz Pratama Al Masyriqi, Syifa’ul Ikrom Syifa’ul Ikrom Ardyningrum, Nabilah Argyanti Arida Ferti Syafiandini Ariyanto, Yuri Astiningrum, Mungki Atiqah Nurul Asri Auliya B, Muhammad Ayu, Tiara Imas Bariroh Isriya Nur Aini Budi Harijanto, Budi Devany Christabella Wijaya Dodo Zulkarnain DWI PUSPITASARI Dwi Puspitasari Erfan Rohadi Excellina Excellina Excellina, Excellina Fadelis Sukya, Fadelis Fahrur R, Imam Fanani, Muhamad Zainul Fatmawati, Triana Hafizh Rizqi Prisadana Hani’ah, Mamluatul Hudriyah Mundzir, Hudriyah Ika Oktavia Pristisari Imam Fahrur Rozi Irawan, Rizki Andi Kyaw, Htoo Htoo Sandy Mochamad Panggih Nirwanto Mufidah, Nursita Al Muhamad Aslam Amzazka, Muhamad Aslam Muhamad Zainul Fanani Muhammad Ashari Fajar Nugroho Muhammad Sofiul Fuad Ruslan Mustika Mentari Nabilah Argyanti Ardyningrum Nabilah Argyanti Ardyningrum Nadhila, Annisa Aulia Nadia Layra Aziza Nirwanto, Mochamad Panggih Nobuo Funabiki Nobuo Funabiki, Nobuo Nofyandi, Resqy Dwi Nur Aini, Bariroh Isriya Nursita Al Mufidah Pratama, Muhammad Irgy Prisadana, Hafizh Rizqi Pristisari, Ika Oktavia Priyanto, Febryan Senja Rahmad, Cahya Rahmadani, Alfiandi Aulia Resqy Dwi Nofyandi Rizki Andi Irawan Rosa Andrie Asmara Rudy Ariyanto Rudy Ariyanto Saputra, Pramana Yoga Satria, Banni Setiadi, Chandrasena Setiawan, Budhy Siradjuddin, Indrazno Siti Muzdalifatus Sa’adah Syafiandini, Arida Ferti Tiara Imas Ayu Tita Wijayanti Toga Aldila Cinderatama Utama, Cahyarizki Adi Yoppy Yunhasnawa Yunhasnawa, Yoppy Yuri Arianto Yuri Ariyanto Yuri Ariyanto Yuri Ariyanto Zulkarnain, Dodo