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All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal Eksplora Informatika J-SAKTI (Jurnal Sains Komputer dan Informatika) KOMPUTEK Infotech: Journal of Technology Information Bulletin of Computer Science Research J-SAKTI (Jurnal Sains Komputer dan Informatika) International Journal Software Engineering and Computer Science (IJSECS) Acta Pedagogia Asiana The Indonesian Journal of Computer Science
Kamayani, Mia
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Mechanical Engineering Other

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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 : ISTEK 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.
Menerapkan Algoritma Neural Network Pada Chatbot Mengenai Pariwisata Di Provinsi Bangka Belitung Mahendra, Ristian; Kamayani, Mia
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 2 (2023): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v7i2.678

Abstract

Bangka Belitung Province, precisely in South Bangka regency, is one of the areas that have the potential to be visited by tourists. However, not all attractions are known by tourists due to lack of information. From these problems, researchers tried to develop a chatbot system. Chatbot is a program that conducts conversations between humans and machines using human language. This chatbot system aims to help tourists do questions and answers automatically to find information about tourist attractions in South Bangka.  The chatbot system applies a model with a natural language processing approach and neural network algorithms. This study aims to create a chatbot model that can provide information with good accuracy about paratourism in Bangka Belitung Province, especially South Bangka district. The data used in this study were the results of interviews and filling out questionnaires to the community. Then the data obtained is stored and converted into JSON format consisting of 173 tags, 618 patterns, and 187 responses. Then preprocessing the data was carried out by taking 25 random test questions. The results of the chatbot system accuracy test got an accuracy score of 92% from 25 questions asked randomly by getting an error value of 8%. From the results of accuracy testing, the chatbot system gets a response by looking at the appropriate questions asked by users based on tags, so that they can get the right answer.
Menerapkan Algoritma Neural Network Pada Chatbot Mengenai Pariwisata Di Provinsi Bangka Belitung Mahendra, Ristian; Kamayani, Mia
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 2 (2023): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v7i2.678

Abstract

Bangka Belitung Province, precisely in South Bangka regency, is one of the areas that have the potential to be visited by tourists. However, not all attractions are known by tourists due to lack of information. From these problems, researchers tried to develop a chatbot system. Chatbot is a program that conducts conversations between humans and machines using human language. This chatbot system aims to help tourists do questions and answers automatically to find information about tourist attractions in South Bangka.  The chatbot system applies a model with a natural language processing approach and neural network algorithms. This study aims to create a chatbot model that can provide information with good accuracy about paratourism in Bangka Belitung Province, especially South Bangka district. The data used in this study were the results of interviews and filling out questionnaires to the community. Then the data obtained is stored and converted into JSON format consisting of 173 tags, 618 patterns, and 187 responses. Then preprocessing the data was carried out by taking 25 random test questions. The results of the chatbot system accuracy test got an accuracy score of 92% from 25 questions asked randomly by getting an error value of 8%. From the results of accuracy testing, the chatbot system gets a response by looking at the appropriate questions asked by users based on tags, so that they can get the right answer.
Comparative Analysis of the Effectiveness of Informatics Course Learning Utilizing Chatgpt Utami, Arneitta Dwicahya; Kamayani, Mia; Siduningrum, Estu; Azhar, Nur Chalik
Acta Pedagogia Asiana Volume 4 - Issue 1 - 2025
Publisher : Tecno Scientifica Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53623/apga.v4i1.553

Abstract

This study examined the effectiveness of conventional teaching methods and ChatGPT in an introductory Algorithms and Programming course at the university level. ChatGPT, an AI-based NLP technology, assisted students in understanding course material through automated responses. However, its effectiveness relative to conventional methods required further evaluation, particularly concerning motivation, interaction, self-regulation, instructional structure, and the instructor's role. Using a sample of 10 students for pretest-posttest analysis, 38 respondents for the User Experience Questionnaire (UEQ), and accuracy analysis via prompt engineering, the results revealed that conventional methods better enhanced motivation and interaction. ChatGPT demonstrated strengths in attractiveness (1.982) and efficiency (2.053) but scored lower in accuracy (1.395) and novelty (1.053). Prompt engineering significantly improved response accuracy when tailored to learning modules, highlighting the importance of precise inputs. The findings suggested that while ChatGPT excelled as a supplementary tool, it was less effective as a standalone teaching method. This study contributed to the growing field of educational technology by providing insights into the integration of AI tools in learning environments.
Perbandingan Algoritma SVM Dan Naïve Bayes Pada Analisis Sentimen Penghapusan Kewajiban Skripsi Yunita, Rani; Kamayani, Mia
The Indonesian Journal of Computer Science Vol. 12 No. 5 (2023): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i5.3415

Abstract

Pada Agustus 2023 Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi membuat peraturan salah satunya menghapus kewajiban skripsi sebagai syarat kelulusan di semua perguruan tinggi di Indonesia. Pro dan kontra saling bertukar tempat di berbagai media sejak peraturan menteri tersebut diumumkan. Banyak yang mendukung kebijakan tersebut tetapi tidak sedikit yang menentang. Dari Issue tersebut, peneliti melakukan analisis sentimen di twitter tentang kebijakan yang menghapus kewajiban skripsi sebagai syarat kelulusan menggunakan 700 data. Penelitian ini membandingkan hasil evaluasi algoritma Support Vector Machine (SVM) dengan Naïve Bayes. Berdasarkan hasil yang diperoleh dari penelitian ini didapatkan 331 sentimen positif serta 369 sentimen negatif dan ditarik kesimpulan bahwa Support Vector Machine (SVM) menjadi algoritma yang terbaik dengan accuracy 80%, recall 83%, precision 76%, dan F1-Score 79%.
Perbandingan Algoritma Klasifikasi untuk Prediksi Kelulusan Mahasiswa Teknik Informatika dengan Orange Data Mining Attyyatullatifah, Iqlimah; Kamayani, Mia
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3796

Abstract

Penyelesaian studi tepat waktu merupakan indikator penting dalam menilai kompetensi lulusan. Meskipun demikian, muncul tantangan karena tidak semua mahasiswa dapat menyelesaikan studi mereka sesuai jadwal yang telah ditentukan. Penelitian ini mengembangkan model prediksi status kelulusan mahasiswa menggunakan empat algoritma klasifikasi: Decision Tree, Naïve Bayes, K-NN, dan SVM. Data penelitian mencakup 500 data mahasiswa angkatan 2018-2020 di Universitas Muhammadiyah Prof. Dr. Hamka, dengan 60% data latihan dan 40% data uji. Analisis dilakukan menggunakan perangkat lunak Orange Data Mining, dengan evaluasi menggunakan K-Fold Cross Validation (k=5), Confusion Matrix, dan ROC. Hasil analisis menunjukkan bahwa model K-NN memiliki performa tertinggi dengan akurasi 92%, recall 90%, dan presisi 92%. Decision Tree menempati posisi kedua dengan akurasi 90%, presisi 87%, dan recall 90%. SVM mencapai akurasi sebesar 84%, dengan presisi 90%, recall 73%. Sementara itu, model Naïve Bayes menunjukkan akurasi 83%, presisi 80%, dan recall 83%.
Implementasi Algoritma Naïve Bayes Pada Analisis Sentimen Terhadap Ulasan Aplikasi DeepL Translate Di Play Store Komarudin, Ahmad; Ayyubi, Reza Al; Arif, Zainul; Kamayani, Mia
KOMPUTEK Vol. 8 No. 1 (2024): April
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/jkt.v8i1.2604

Abstract

Perkembangan teknologi semakin maju dengan pesat, hingga terciptanya sebuah smartphone yang didalamnya tersedia berbagai fitur-fitur canggih. Play Store merupakan layanan yang dibuat oleh Google untuk pengunduhan berbagai aplikasi, game, buku digital, film secara gratis maupun berbayar. Salah satu aplikasi yang tersedia pada Play Store adalah DeepL Translate, yang merupakan aplikasi yang bisa menerjemahkan berbagai bahasa dengan menerapkan Artificial Intelegent (AI) didalamnya. Tujuan penelitian ini yaitu untuk mengevaluasi aplikasi DeepL Translate melalui analisis sentimen pada ulasan menggunakan algoritma Naïve Bayes untuk mengetahui seberapa puas pengguna dalam menggunakan aplikasi ini. Pengambilan data ulasan dilakukan menggunakan teknik scrapping dengan Google Colab sebanyak 995 data, kemudian jumlah dataset berubah menjadi 939 ulasan setelah melalui proses preprocessing dengan data positif sebanyak 771 dan 168 untuk data negatif. Dataset kemudian diseimbangkan menggunakan SMOTE dan diklasifikasikan dengan algoritma Naïve Bayes. Algoritma ini dipakai karena menggunakan probabilitas yang sederhana dan efektif dalam mengklasifikasikan sebuah data. Hasil implementasi algoritma diperoleh accuracy sebesar 93,71%, precision sebesar 98,84%, dan recall sebesar 88,85%, dengan teknik evaluasi yang digunakan adalah confussion matrix.
Perancangan Ulang Desain UI/UX pada Aplikasi ibisPaint X dengan Penerapan Metode The Wheel Novianti, Eka; Kamayani, Mia
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.614

Abstract

Rapid technological developments have made smartphones not only function as communication devices, but can also be used as a place to draw digitally. Mobile-based graphic design applications, namely ibisPaint X. found problems experienced by users, such as difficulty in using the application, features that are difficult to find, and confusing displays. This study uses the wheel method to overcome problems faced by users which has four main stages, namely analysis, design, prototype, and evaluation focusing on user needs analysis, prototype design using figma, and usability testing using a system usability scale to measure the effectiveness of the resulting design. The results of this study showed a score before the redesign of 38.33, far from the minimum average value of the system usability scale of 68. After the redesign, the score increased very well, the score obtained was 82 indicating success in improving user experience and needs. Changes occurred on the login page, main menu, and the presence of a brush type search feature to make it easier for users when using the ibisPaint X application. This study provides a good contribution to the development of the ibisPaint X application in meeting user needs and is expected to be a reference in order to compete in the increasingly advanced digital era.
Co-Authors Arif, Zainul Attyyatullatifah, Iqlimah Ayyubi, Reza Al Azhar, Nur Chalik Azzahra, Nabila Dewy, Avry Liyanah Eka Novianti, Eka Firman Noor Hasan Komarudin, Ahmad Mahendra, Ristian Pratiwi, Anissya Agsani Rahman Malik, Luqman Abdur Siduningrum, Estu Utami, Arneitta Dwicahya Yunita, Rani