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All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal Eksplora Informatika MULTINETICS Infotech: Journal of Technology Information
Kamayani, Mia
Unknown Affiliation
Computer Science & IT Engineering

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Implementasi CMS Pada Media Pembelajaran Mengenal Alat Musik Tradisional Indonesia Sinduningrum, Estu; Suhendra, Renadi Fadino; Kamayani, Mia
MULTINETICS Vol 4, No 2 (2018): MULTINETICS NOPEMBER (2018)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.Vol4.No.2.2018.pp.28-37

Abstract

Traditional musical instruments were born and developed throughout the archipelago in Indonesia, which is still a hereditary habit in the community to date. This musical instrument is spread in almost all corners of the country and each region has different characteristics. Children in learning and knowing traditional musical instruments are less desirable because traditional musical instruments are considered outdated and old-fashioned, so they are reluctant to learn them. children are made media to introduce traditional CMS-based musical instruments and musical instruments made in 3D, so children want to know and learn traditional musical instruments. System modeling on the construction of this CMS use UML (Unified Modelling Language) with tool activity diagram, use case, class diagram and developed using the method waterfall which is run on system. System testing is permormed using alpha testing and beta testing, for beta testing is done by distributing the system testing questionnaire to the 15 listed respondent. For the result of the percentage is 86,67%, which means the result of this CMS assessment can be categorized very well.
Perbandingan Pelabelan Data dalam Analisis Sentimen Kurikulum Proyek di platform TikTok: Pendekatan Naïve Bayes Pratiwi, Anissya Agsani; Kamayani, Mia
Jurnal Eksplora Informatika Vol 14 No 1 (2024): Jurnal Eksplora Informatika
Publisher : Institut Teknologi dan Bisnis STIKOM Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30864/eksplora.v14i1.1093

Abstract

Penelitian ini fokus pada analisis sentimen mahasiswa terhadap perubahan kurikulum berbasis proyek di tingkat pendidikan tinggi yang menghilangkan kewajiban skripsi, Data sentimen diekspresikan melalui platform media sosial TikTok, dan algoritma Naïve Bayes digunakan untuk mengklasifikasikan sentimen menjadi positif atau negatif. Proses penelitian mencakup pengambilan data, pembersihan data, preprocessing data, pelabelan data, hingga klasifikasi menggunakan algoritma Naive Bayes. Penelitian ini melibatkan dua tahap pelabelan dalam 913 data: pelabelan pertama manual menghasilkan 510 sentimen positif dan 403 negatif, sementara pelabelan kedua otomatis dengan RapidMiner menghasilkan 415 sentimen positif dan 498 negatif. Beberapa mahasiswa memberikan ulasan positif menganggap hal ini sebagai langkah inovatif untuk persiapan di dunia kerja. Meskipun beberapa merasa khawatir dengan tingkat kesulitan yang lebih tinggi. Hasil penelitian menunjukkan mayoritas tanggapan positif terhadap kurikulum berbasis proyek, dengan nilai pelabelan manual mencapai accuracy 93.98%, precision 100%, recall 87.99%. Sedangkan pelabelan otomatis dengan Rapidminer memperoleh nilai accuracy 70.41%, precision 80.15%, recall 69.96%.
FAKTOR-FAKTOR YANG MEMPENGARUHI MINAT CALON MAHASISWA BARU MENDAFTAR PADA FTII UHAMKA MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR (K-NN) Rahman Malik, Luqman Abdur; Kamayani, Mia; Hasan, Firman Noor
Infotech: Journal of Technology Information Vol 9, No 1 (2023): JUNI
Publisher : STMIK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v9i1.163

Abstract

In accepting new students at Prof. University. Dr. Hamka, many prospective students or parents of students are looking for registration information, this is a great opportunity for Uhamka to gain the sympathy of prospective students to register at Uhamka, especially the Faculty of Industrial and Informatics Technology. The problem in this study is that there is no data processing related to the factors that influence the interest of prospective new students to choose the Faculty of Industrial and Informatics Technology (FTII) Uhamka. The purpose of this study was to determine the factors that influence the interest of prospective new students in choosing majors at the Faculty of Industrial and Information Technology (FTII) Uhamka. The attributes used in this study were 10 attributes, namely full name, major, tuition fee, FII location with domicile, presence of friends/family, accreditation, facilities, PMB services, PMB information, and information of interest. The method that researchers use in this study is the K-Nearest Neighbor Algorithm (K-NN). From the results of testing the researchers used the K-5 fold technique and the confusion matrix obtained an average accuracy of 72.5%, which means it is good.
Studi Kasus Klik Food dengan Heart Framework dan Double Diamond Pada Pengembangan User Experience. Azzahra, Nabila; Kamayani, Mia
Techno.Com Vol. 23 No. 2 (2024): Mei 2024
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v23i2.10439

Abstract

Kemajuan teknologi yang serba digital telah mengubah cara konsumen berinteraksi dengan layanan e-commerce, khususnya dalam sektor makanan dan minuman. Studi ini mengkaji pengalaman pengguna (user experience) dalam aplikasi Klik Food Indomaret, sebuah platform e-commerce yang menawarkan berbagai produk makanan dan minuman. Penelitian ini bertujuan membuat UI/UX yang dapat menimbulkan kepuasan pengguna dalam proses transaksi di dalam layanan sehingga pengguna senang serta transaksi sukses menggunakan Heart Framework dan Double Diamond. Heart Framework dengan penerapan aspek happiness dan task success yang diteapkan menggunakan metrik SEQ, SUS dan MAUS. Pada penelitian ini heart framework dan double diamond kredibel dalam menciptakan kepuasan pengguna dengan hasil SEQ 5,74 dari 7, SUS 74 dari 100 dan MAUS 86,6. Semua hasil metrik memasuki kategori baik atau hasil kepuasan pengguna terhadap protipe aplikasi dapat diterima.
Co-Authors Azzahra, Nabila Firman Noor Hasan Pratiwi, Anissya Agsani Rahman Malik, Luqman Abdur Sinduningrum, Estu Suhendra, Renadi Fadino