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All Journal Jurnal Komputer Terapan Prosiding Seminar Nasional Program Pengabdian Masyarakat International Journal of Humanities Education and Social Sciences Jurnal Ilmiah Research Student Jurnal Sains Student Research Neraca Manajemen, Akuntansi, dan Ekonomi The Indonesian Journal of Computer Science Journal of Big Data Analytic and Artificial Intelligence
Muhammad Fadlan
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Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Medicine & Pharmacology Social Sciences Other

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Journal : Journal of Big Data Analytic and Artificial Intelligence

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Klasifikasi Siswa berdasarkan Nilai pada Bidang Ekstrakurikuler Menggunakan Metode K-Nearest Neighbor Ernie Kustanti; Umi Ba’diah; Sinawati; Muhammad Fadlan
Journal of Big Data Analytic and Artificial Intelligence Vol 4 No 1 (2018): JBIDAI Juni 2018
Publisher : STMIK PPKIA Tarakanita Rahmawati

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Abstract

Pentingnya kegiatan ekstrakurikuler sebagai sarana pengembangan diri siswa, membuat pemilihan ekstrakurikuler tidak dapat dilakukan sembarangan. Tidak sedikit siswa yang mengalami kesulitan dalam menentukan ekstrakurikuler yang akan diikuti. Salah satu cara untuk mengatasi permasalahan ini adalah dengan menerapkan metode K-Nearest Neighbor. Prinsip kerja K-Nearest Neighbor (KNN) ini adalah mencari jarak terdekat antara data yang akan dievaluasi dengan K-Nearest (neighbor) terdekatnya dalam data pelatihan. Menurut hasil analisa program yang telah dikembangkan menyimpulkan bahwa penerapan metode Knn (K-Nearest Neighbor) berhasil diterapkan aplikasi penentuan nilai siswa, dari pembuatan aplikasi tersebut ada beberapa kelebihan dan kekurangan yang dialami, adapun kelebihan aplikasi ini yaitu lebih memudahkan siswa dalam memilih kriteria ekstrakurikuler sesuai nilai siswa. Oleh karena itu penulis mengklasifikasikan nilai siswa yang paling banyak diminati dan yang memuaskan. Sedangkan kekurangan dari Metode KNN adalah jarak tidak jelas mengenai jenis jarak apa yang harus digunakan dan atribut yang harus digunakan untuk mendapatkan hasil yang terbaik.
Analisis Sentimen pada Ulasan Penyedia Layanan Menggunakan Algoritma C4.5 Miske Marcillia; Muhammad Fadlan; Hartono, Lies
Journal of Big Data Analytic and Artificial Intelligence Vol 6 No 2 (2023): JBIDAI Desember 2023
Publisher : STMIK PPKIA Tarakanita Rahmawati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71302/jbidai.v6i2.45

Abstract

Sentiment analysis is essential for understanding and processing textual data to derive meaningful insights. PT. XYZ, a company operating in the GSM cellular telecommunications sector, faces a challenge due to the lack of a specific application for analyzing visitor reviews on their services. This gap impedes their ability to gain detailed insights into consumer feedback, hindering efforts to improve service quality. This research addresses this issue by developing an application that utilizes the C4.5 algorithm to analyze PT. XYZ's reviews. The study uses 140 consumer reviews collected from Google Maps. The C4.5 algorithm, which creates decision trees to find relationships among variables, is employed for classifying and predicting service review sentiments. The research involves several stages: data crawling, text preprocessing, term frequency (TF) calculation, and applying the C4.5 algorithm for classification.The results demonstrate the effectiveness of this approach. With 126 training data samples and 14 test samples, the model achieved an accuracy of 78.57%, precision of 83.33%, and recall of 90.91%. These findings indicate that increasing the amount of training data enhances pattern recognition and accuracy. The study successfully meets its objectives, proving that sentiment analysis using the C4.5 algorithm can effectively predict service review sentiments and aid in improving service quality.
Co-Authors AA Sudharmawan, AA Alfia Utami Anto Asmah Asmah Ernie Kustanti Hadriansa Hadriansa Hartono, Lies Maya Jannah Miske Marcillia Muhammad Amrizal Arripai Mussalimah Mussalimah Nasution, Muhammad Irwan Padli Nurbaiti Pinasthika Alya Disti Selvi Sinawati Sinawati Sinawati Siregar, Risdalina Umi Ba?diah Umi Ba’diah Ummi Syafiqoh