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All Journal CESS (Journal of Computer Engineering, System and Science) Jurnal Ilmiah Flash Jurnal Pengabdian Pada Masyarakat Jurnal SOLMA Prosiding Seminar Nasional Teknoka Jurnal Sains dan Informatika Jurnal Ilmiah Matrik Jurnal Eksplora Informatika KOMPUTEK JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Seling: Journal of PGRA Study Program Jurnal Linguistik Komputasional Jurnal ICT : Information Communication & Technology MULTINETICS Progresif: Jurnal Ilmiah Komputer Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Sistem Komputer dan Informatika (JSON) Infotech: Journal of Technology Information Jurnal Computer Science and Information Technology (CoSciTech) Jurnal Pendidikan dan Teknologi Indonesia KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Abdimas ADPI Sosial Dan Humaniora J-SAKTI (Jurnal Sains Komputer dan Informatika) International Journal Software Engineering and Computer Science (IJSECS) Jurnal Minfo Polgan (JMP) Jurnal Sains Informatika Terapan (JSIT) Acta Pedagogia Asiana JURNAL TEKNIK INFORMATIKA DAN KOMPUTER The Indonesian Journal of Computer Science
Kamayani, Mia
Universitas Muhammadiyah Prof.Dr.HAMKA, Jakarta, Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Social Sciences Other

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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.
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.
Analisis Sentimen Pengguna Aplikasi Livin' by Mandiri Menggunakan Metode Support Vector Machine (SVM) dengan Ekstraksi Fitur TF-IDF dan Word2Vec Suharman, Anas; Kamayani Sulaeman, Mia
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 8 (2025): JPTI - Agustus 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.941

Abstract

Pesatnya perkembangan aplikasi mobile banking di Indonesia, termasuk Livin’ by Mandiri, menimbulkan kebutuhan untuk memahami respons pengguna secara lebih mendalam. Studi ini bertujuan untuk mengevaluasi sentimen pengguna terhadap aplikasi tersebut berdasarkan ulasan yang diperoleh dari Google Play Store. Penelitian ini menerapkan algoritma Support Vector Machine (SVM) dengan dua teknik ekstraksi fitur, yaitu Term Frequency–Inverse Document Frequency (TF-IDF) dan Word2Vec. Sebanyak 15.000 ulasan dianalisis dan diklasifikasikan ke dalam sentimen positif maupun negatif, setelah melalui tahapan pra-pemrosesan. Hasil analisis menunjukkan bahwa model SVM dengan TF-IDF menghasilkan akurasi 87%, precision 90% untuk sentimen positif, serta recall sebesar 82%. Sebaliknya, pendekatan Word2Vec mencatatkan akurasi 83%, precision positif 92%, dan recall 71%. Temuan ini mengindikasikan bahwa TF-IDF lebih konsisten dalam klasifikasi umum, sedangkan Word2Vec lebih efektif dalam mengenali sentimen negatif.
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.v4i2.1345

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
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%.
ANALISIS SENTIMEN TERHADAP ULASAN PENGGUNAAN SHOPEE MELALUI TWEET PADA TWITTER MENGGUNAKAN ALGORITMA NAÏVE BAYES Muflih, Hilmy Zhafran; Al Assyam, Hafizh Dhery; Pangestu, Faisal Akbar; Kamayani, Mia
Jurnal Teknik Informatika dan Komputer Vol. 2 No. 2 (2023): Jurnal Teknik Informatika dan Komputer
Publisher : Universitas Muhammadiyah Prof. DR. HAMKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/jutikom.v2i2.12199

Abstract

The increasing use of the internet among the public is because it is a means to carry out various activities, one of which is buying and selling online or known as e-commerce. One of the largest e-commerce in Indonesia is Shopee. Shopee offers various features for its users. The large number of shopee users results in the large number of responses given to shopee, so the researcher wants to carry out a sentiment analysis process regarding user responses to shopee, whether the response of shopee users is negative or positive. The responses or opinions of Shopee users are taken from tweets in the Twitter application. Tweets typed and written and published by Twitter users about shopee. In this study, researchers used the RapidMiner application to collect tweets data from Twitter users and to apply the Naïve Bayes algorithm. The researcher collected 200 data regarding shopee from Twitter. The results obtained from sentiment analysis using the Naïve Bayes algorithm get 78% negative sentiment and 22% positive sentiment from 200 datasets. The process of testing the Naïve Bayes algorithm using the confusion matrix obtains an accuracy value of 77.50%.
Social Media Sentiment Analysis of Twitter Regarding People's Housing Savings (TAPERA) Using Naïve Bayes Avry Liyanah Dewy; Mia Kamayani
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4126

Abstract

The advancement of technology has transformed how people interact and express opinions on social media platforms. This research examines Twitter conversations regarding Indonesia's government-initiated Housing Savings Program (TAPERA) through sentiment analysis. The study employed Naïve Bayes classification methodology, with data acquisition conducted via Google Colab platform utilizing the tweet-harvest library. The collection process yielded 1,800 tweets matching predetermined search parameters. Data underwent rigorous preprocessing, including text cleaning and manual sentiment annotation to establish reliable training datasets. Examination of 720 test tweets revealed 473 (65.69%) expressed negative sentiment while 247 (34.31%) conveyed positive sentiment toward the program. The implemented Naïve Bayes model achieved 84.17% accuracy, with negative class precision at 88.71% and recall at 88.60%, while positive class precision reached 78.54% with 76.08% recall. Results indicate the Naïve Bayes approach effectively categorizes public sentiment regarding the TAPERA program, offering valuable feedback for stakeholders responsible for program assessment and enhancement.
Penerapan Metode User-Centered Design dalam Redesign UI/UX Aplikasi Mobile Transjakarta Luthfia Masruroh Syah; Mia Kamayani
Progresif: Jurnal Ilmiah Komputer Vol 21, No 2 (2025): Agustus
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v21i2.2900

Abstract

The Transjakarta mobile application plays a vital role in supporting public transportation in Jakarta, but many users report poor usability, complicated navigation, and unintuitive interface design. Based on an initial survey involving 20 active users, the application scored only 26.8 on the System Usability Scale (SUS), placing it in the “Poor” category. This study adopts the User-Centered Design (UCD) approach in the redesign process of the application's UI/UX, involving four key stages: understanding the context of use, identifying user needs, designing appropriate solutions, and evaluating the alignment of those solutions with the identified needs. Evaluation was conducted using the SUS method and A/B Testing. The redesign process led to a significant improvement, raising the SUS score 85.25 and showing that 86% of users preferred the new design. Additional features such as “Top-up Balance” and “Transaction History” also received positive feedback. These findings demonstrate that the UCD approach effectively improves usability and user satisfaction, and can serve as a reference for future developments in public service applications.Keywords: A/B Testing; Redesign; System Usability Scale; Transjakarta; User Centered Design AbstrakAplikasi mobile Transjakarta merupakan layanan pendukung transportasi publik di Jakarta yang penting, namun masih menghadapi berbagai masalah dalam kemudahan penggunaan, integrasi fitur, dan tampilan antarmuka yang kurang intuitif. Berdasarkan survei awal terhadap 20 pengguna, skor System Usability Scale (SUS) hanya mencapai 26,8 yang termasuk kategori Poor. Penelitian ini menggunakan pendekatan User-Centered Design (UCD) dalam proses perancangan ulang UI/UX aplikasi, yang melibatkan empat tahapan inti: memahami konteks penggunaan, mengidentifikasi kebutuhan pengguna, merancang solusi desain, serta mengevaluasi kesesuaian solusi terhadap kebutuhan tersebut. Evaluasi dilakukan menggunanan SUS dan A/B Testing. Hasilnya menunjukkan peningkatan signifikan, dengan skor SUS yang naik menjadi 85,25 (kategori Excellent) dan 86% responden lebih menyukai desain baru. Selain itu, fitur baru seperti “Isi Saldo” dan “Riwayat Transaksi” mendapat tanggapan positif dari mayoritas pengguna. Penelitian ini menunjukkan bahwa UCD efektif dalam meningkatkan kualitas pengalaman pengguna serta dapat menjadi acuan dalam pengembangan aplikasi layanan publik berbasis digital.Kata kunci: A/B Testing; Perancangan Ulang; System Usability Scale; Transjakarta; User Centered Design
Pendekatan Metode UCD dan SUS dalam Redesign UI/UX Aplikasi Mobile iPusnas Oktaviani Ariyaningsih; Mia Kamayani
Progresif: Jurnal Ilmiah Komputer Vol 21, No 2 (2025): Agustus
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v21i2.2826

Abstract

This study aims to improve the quality of user experience when accessing the iPusnas mobile application, a digital library platform available in Indonesia. Based on observations and interviews, several issues were identified, including an overly crowded user interface that lacks visual appeal, a navigation flow that is perceived as unintuitive, and features that are considered less relevant to users’ needs. To address these problems, a redesign process was carried out by applying the User Centered Design (UCD) approach, which emphasizes user involvement at every stage of development. The evaluation of the redesigned version was conducted using the System Usability Scale (SUS) method. The test results showed an increase in the SUS score from 33.5 to 82.83 after the redesign. This improvement indicates that applying the UCD approach, accompanied by SUS evaluation, can effectively enhance the usability level of the iPusnas application.Keywords: iPusnas application; System usability scale; User centered design; Usability AbstrakPenelitian ini dimaksudkan untuk meningkatkan mutu pengalaman pengguna ketika menggunakan aplikasi iPusnas versi mobile, yang merupakan platform perpustakaan digital di Indonesia. Berdasarkan hasil observasi dan wawancara, ditemukan sejumlah permasalahan yang dialami oleh pengguna, antara lain tampilan antarmuka yang dianggap terlalu padat sehingga kurang menarik secara visual, alur navigasi yang dirasa kurang intuitif, serta beberapa fitur yang dinilai kurang relevan dengan kebutuhan pengguna. Untuk menjawab permasalahan tersebut, dilakukan proses perancangan ulang dengan menerapkan pendekatan User Centered Design (UCD), yaitu metode yang berfokus pada pengguna di setiap langkah proses pengembangan. Evaluasi terhadap desain baru dilakukan melalui pengukuran menggunakan metode System Usability Scale (SUS). Hasil pengujian menunjukkan bahwa nilai SUS meningkat dari 33.5 menjadi 82,83 setelah dilakukan redesign. Peningkatan ini mengindikasikan bahwa penerapan pendekatan UCD yang disertai evaluasi menggunakan SUS mampu secara efektif meningkatkan tingkat kegunaan aplikasi iPusnas.Kata Kunci: Aplikasi iPusnas; System usability scale; User centered design; Usability   
Co-Authors Abdul Aziz Alfaraby Ahmad Komarudin Ahmad Rayhaan Yusri Yusri Aji, Arielio Bayu Al Assyam, Hafizh Dhery Alfaraby, Abdul Aziz Anhari, Tirta Arif, Zainul Ariska, Amelia Atiqah M. Hilda Attyyatullatifah, Iqlimah Avorizano, Arry Avry Liyanah Dewy Ayyubi, Reza Al Azhar, Nur Chalik Azzahra, Nabila Daffa Anas Darman Dais Isnafirlah Dimas Febriawan Dwi Anugrah Putra Emilia Roza Estu Sinduningrum Estu Sinduningrum Faisal Akbar Pangestu Fikri Kurnia Ramadhan Firman Noor Hasan Fitri Yatusholihah Gunawan, PH Hafizh Dhery Al Assyam Hilda, Atiqah M. Hilmy Zhafran Muflih Ikhsan Wahyudi Imam Safi'i Intania Widyaningrum Iqbal Musyaffa Khusniyati Masykuroh Komarudin, Ahmad Kusuma, Miftahul Ari Luthfia Masruroh Syah M. Asep Rizkiawan Mahendra, Ristian Miftahul Ari Kusuma Mohammad Reza Saputra Mohammad Suryadi Syarif Muflih, Hilmy Zhafran Muhammad Irfan Faris Muhammad Izzaturrahman Muhammad Rafly Al Fattah Zain Nur Aini Puspitasari Oktaviani Ariyaningsih Pangestu, Faisal Akbar PH Gunawan Prananda, Dimas Adi Pratiwi, Anissya Agsani Rahman Malik, Luqman Abdur Rahmi Imanda Rani Yunita Rasiyah Shafa Azizah Reza Al Ayyubi Ridwan Maulana Subekti Roslaini Roslaini Sherina Nurul Kautsar Siduningrum, Estu Sinduningrum, Estu Siti Nurhalimah Sriyono Sriyono Sriyono Sriyono Suciana Wijirahayu Suharman, Anas Suhendra, Renadi Fadino Sulistiawati, Risa Utami, Arneitta Dwicahya Wijaya, Farid Rizky Yogi Fachriyatul Utama Yunita, Rani Zainul Arif