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All Journal InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sinkron : Jurnal dan Penelitian Teknik Informatika JurTI (JURNAL TEKNOLOGI INFORMASI) Zero : Jurnal Sains, Matematika, dan Terapan IJISTECH (International Journal Of Information System & Technology) Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal JOURNAL OF SCIENCE AND SOCIAL RESEARCH JURSIMA (Jurnal Sistem Informasi dan Manajemen) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer INFOKUM Community Development Journal: Jurnal Pengabdian Masyarakat Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) LEGAL BRIEF Journal of Computer Networks, Architecture and High Performance Computing IJISTECH Yayasan Cita Cendikiawan Al Khwarizmi Proceeding International Seminar of Islamic Studies Jurnal Minfo Polgan (JMP) sudo Jurnal Teknik Informatika Hello World Factory Jurnal Industri, Manajemen dan Rekayasa Sistem Industri Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat JURSIMA Journal of Innovation in Research, Education and Culture (JIREC) Jurnal Sistem Informasi dan Manajemen Jurnal Intelek Dan Cendikiawan Nusantara Applied Information Technology and Computer Science (AICOMS) Portal Riset dan Inovasi Sistem Perangkat Lunak Al'Adzkiya International of Computer Science and Information Technology Journal Jurnal Pengabdian dan Inovasi Masyarakat
Dicky Apdilah
Teknik Informatika, Universitas Asahan
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Journal : JOURNAL OF SCIENCE AND SOCIAL RESEARCH

 1 
PENERAPAN METODE BACKPROPAGATION DALAM PERAMALAN JUMLAH PERJALANAN WISATAWAN NUSANTARA Ananda, Muhammad Rifky; Apdilah, Dicky
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 3 (2025): August 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i3.4096

Abstract

Abstract: An major part of Indonesia's economy is tourism. Accurate forecast techniques are necessary due to the variation in the amount of domestic tourists visiting different provinces. The goal of this study is to use Artificial Neural Networks (ANN) and the backpropagation technique to create a prediction model. The BPS data utilized spans the years 2018–2024. A binary sigmoid function was used to normalize the data, which were then divided into training and testing sets and trained until the MSE was as low as possible. High forecast accuracy is demonstrated by the results. It is anticipated that the model would facilitate data-driven decision-making in the administration of the tourist industry. Keyword: artificial neural network, backpropagation, prediction, domestic travel, and tourism. Abstrak: Sektor pariwisata memainkan peran yang signifikan dalam pertumbuhan ekonomi Indonesia. Ada cara untuk memprediksi jumlah wisatawan yang datang ke nusantara ke berbagai provinsi. Tujuan dari penelitian ini adalah untuk menggunakan algoritma backpropagation Jaringan Syaraf Tiruan (JST) untuk membuat model yang dapat memprediksi jumlah wisatawan yang akan datang ke setiap provinsi. Data mencakup perjalanan wisatawan dari 2018 hingga 1924, menurut BPS. Data dibagi menjadi data pelatihan dan pengujian setelah dinormalisasi menggunakan fungsi sigmoid biner. Model JST dilatih untuk mencapai nilai MSE minimal. Hasil latihan menunjukkan bahwa JST sangat akurat dalam memprediksi jumlah perjalanan wisatawan. Penelitian ini dimaksudkan untuk berfungsi sebagai referensi dalam penggunaan data dalam proses pengambilan keputusan di industri pariwisata. Kata kunci: wisatawan nusantara; jaringan syaraf tiruan; backpropagation; prediksi; pariwisata.
PENERAPAN ALGORITMA NAIVE BAYES UNTUK KLASIFIKASI PENYAKIT BERDASARKAN GEJALA DAN PROFIL PASIEN Sitorus, Indi Ramadhani; Apdilah, Dicky
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 3 (2025): August 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i3.3961

Abstract

Abstract: This study aims to implement the Naive Bayes algorithm to develop a web-based disease classification system utilizing patient symptoms and profile data. The dataset, obtained from Kaggle, consists of 349 entries with five primary attributes: fever, cough, fatigue, difficulty breathing, and age group. Classification is performed by manually calculating the posterior probability of each disease class using the Naive Bayes approach. The model is integrated into a PHP-MySQL-based system and evaluated using 20 randomly selected test data. Performance evaluation resulted in an accuracy of 45%, with a precision of 0.45, recall of 0.45, and F1-score of 0.45. These results indicate that the Naive Bayes algorithm is applicable as an initial method in developing a symptom- and profile-based disease classification system, although further improvement is needed through feature enrichment and model optimization. Keyword: naive bayes; disease classification; symptoms; patient profile; system evaluation Abstrak: Penelitian ini bertujuan menerapkan algoritma Naive Bayes untuk membangun sistem klasifikasi penyakit berbasis web dengan memanfaatkan data gejala dan profil pasien. Dataset yang digunakan diperoleh dari Kaggle, terdiri atas 349 entri dengan lima atribut utama: demam, batuk, kelelahan, kesulitan bernapas, dan kelompok umur. Proses klasifikasi dilakukan dengan menghitung probabilitas posterior setiap kelas penyakit secara manual menggunakan pendekatan Naive Bayes. Model diterapkan ke dalam sistem berbasis PHP dan MySQL, kemudian diuji menggunakan 20 data acak sebagai data uji. Evaluasi performa menghasilkan akurasi sebesar 45%, precision 0,45, recall 0,45, dan F1-score 0,45. Hasil ini menunjukkan bahwa algoritma Naive Bayes dapat diterapkan sebagai metode awal dalam pengembangan sistem klasifikasi penyakit berbasis data gejala dan karakteristik pasien, meskipun performanya masih perlu ditingkatkan melalui pengayaan fitur dan optimasi algoritma. Kata Kunci: naive bayes; klasifikasi penyakit; gejala; profil pasien; evaluasi sistem
Co-Authors Ade Surya Pranata Adriani, Dian Ayu Afif, Zaid Al Khowarizmi Ananda, Muhammad Rifky Andy Satria Aris Siregar ARIS SIREGAR Asti, Ardian Azrai Sirait Baehaqi Batu Bara, Zulfa Khairina Christina Lestari Ginting Dian Ayu Andriani Emiel Salim Siregar Erdina Dwita Sari Fahrul Rizal, Fahrul Fanny Ramadhani Ferry Fachrizal - Guntur, Surya H Aly, Moustafa Hapzi Ali Harmayani Heru Swanda Ikhwan, Ali Indah Kusuma Dewi, Indah Kusuma Indah Purnama Sari Indah Purnama Sari irma yunita Irwansyah, Bambang Linta Alfafaruq Manurung, Asrar Aspia Mendrofa, Firman Syukur Mhd. Basri Mirza Syapiq Muhammad Khoiruddin Harahap Mutia Mutia, Mutia Novi Sryantika Nur Indah Febriani Nurul Khairina Oris Krianto Sulaiman P, Ririt Dwiputri Purnama Sari, Indah Ramadhani, Fanny Ririt Dwiputri P Rizka Handayani RR. Ella Evrita Hestiandari Rusli Rusli Sartika Sartika Simanjuntak , Pastima Sinambela, Nur Isnaini Sitorus, Indi Ramadhani Suhermanto Suhermanto Syahrunsyah , Syahrunsyah Yuni Syarah Sitorus Zaid Afif ZULFA KHAIRINA BATUBARA