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All Journal Tekno : Jurnal Teknologi Elektro dan Kejuruan Jurnal Ilmiah Informatika Komputer Prosiding SNATIF Jurnal Informatika dan Teknik Elektro Terapan Sistem : Jurnal Ilmu-Ilmu Teknik INTEGER: Journal of Information Technology JIKO (Jurnal Informatika dan Komputer) JEEMECS (Journal of Electrical Engineering, Mechatronic and Computer Science) JURNAL ILMIAH INFORMATIKA Jurnal Infomedia JURNAL PENDIDIKAN TAMBUSAI Jurnal Teknik Elektro dan Komputer TRIAC Jurnal Riset Informatika Jurnal Teknologi Terpadu JEECAE (Journal of Electrical, Electronics, Control, and Automotive Engineering) JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) JISKa (Jurnal Informatika Sunan Kalijaga) Jurnal Informatika dan Rekayasa Elektronik bit-Tech JE-Unisla ILKOMNIKA: Journal of Computer Science and Applied Informatics Generation Journal JATI (Jurnal Mahasiswa Teknik Informatika) CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Journal of Computer Networks, Architecture and High Performance Computing Jurnal Pengabdian kepada Masyarakat Nusantara Nusantara Science and Technology Proceedings Jurnal Restikom : Riset Teknik Informatika dan Komputer Jurnal Ilmiah Teknologi Informasi dan Robotika Journal of Information System and Technology (JOINT) Jurnal Teknologi dan Manajemen TIERS Information Technology Journal Jurnal Informatika, Komputer dan Bisnis (JIKOBIS) Decode: Jurnal Pendidikan Teknologi Informasi International Journal Of Computer, Network Security and Information System (IJCONSIST) ALINIER: Journal of Artificial Intelligence & Applications Jurnal Sistem Informasi, Teknik Informatika dan Teknologi Pendidikan (JUSTIKPEN) Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) SinarFe7 Jurnal Informatika Software dan Network (JISN) Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Journal of Informatics and Electronics Engineering J-Icon : Jurnal Komputer dan Informatika TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi "JAMASTIKA" Jurnal Mahasiswa Teknik Informatika Jurnal Informatika Polinema (JIP) VISA: Journal of Vision and Ideas Journal of Innovative and Creativity Journal of Technology and System Information Journal of Software Engineering and Multimedia (JASMED) Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Himpunan: Jurnal Ilmiah Mahasiswa Pendidikan Matematika Brilliant International Journal of Management and Tourism
Anggraini Puspita Sari
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Journal : Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research

 1 
Implementasi Speech to Text untuk Mempermudah Catatan Praktik Diagnosis Pasien Dengan Metode NLP Ridho Fajar Fahturohman; Nafis Pratama Putra; Panggih Santri; Anggraini Puspita Sari
MISTER: Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research Vol. 1 No. 3c (2024): JULI (Tambahan)
Publisher : UNIVERSITAS SERAMBI MEKKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/mister.v1i3c.1935

Abstract

Medical diagnoses in students' field study practice activities are very important, as data in preparing field study practice reports. The large amount of diagnostic data that has to be retyped manually makes time ineffective. Based on this problem, this research implements Speech to Text (STT), a feature that can convert voice into text using the Natural Language Processing (NLP) method using the Python programming language. The NLP method is used in this research because its role is to interpret a language, both written and spoken, so it really supports the operation of STT. Students just need to record the diagnostic conversation with the patient, then the .wav format file is processed in a system that will provide written output, so students just have to copy it into a report. The test used some audio files that had different durations and noise levels. The system can convert voice into text with a success percentage of 93,34%.
Sistem Rekomendasi Linimasa Facebook Berdasarkan Topik Kesukaan Pengguna Menggunakan Metode Content-Based Filtering & Term Frequency-Inverse Document Frequency Bayu Setiawan; Bagus Satrio Wicaksono; Muhammad Hilmy Aziz; Anggraini Puspita Sari
MISTER: Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research Vol. 1 No. 3c (2024): JULI (Tambahan)
Publisher : UNIVERSITAS SERAMBI MEKKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/mister.v1i3c.2004

Abstract

This research aims to identify Facebook timeline recommendation systems based on user habits using Content-Based Filtering (CBF) and Term Frequency-Inverse Document Frequency (TF-IDF) methods. By utilizing historical user activity data, this system will customize content recommendations for individual users. The CBF method is used to compare the similarity of the content to be recommended with the user's habits, while TF-IDF is used to evaluate various keywords in the content. The results of this study show that the combination of CBF and TF-IDF methods can improve the accuracy of recommendation in Facebook timeline, resulting in a more convenient and relevant user experience.
Analisis Perbandingan Metode Fuzzy Mamdani dan Tsukamoto dalam Prediksi Estimasi Konsumsi Listrik Aldito Restu Wintama; Alif Bayu Ammarizky; Muhammad Lizamul Arsi; Anggraini Puspita Sari
MISTER: Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research Vol. 1 No. 3c (2024): JULI (Tambahan)
Publisher : UNIVERSITAS SERAMBI MEKKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/mister.v1i3c.2019

Abstract

This study aims to compare the Fuzzy Mamdani and Tsukamoto methods in estimating electricity consumption in Romania during the period 2019-2024. Daily electricity consumption data were obtained from the Kaggle dataset, which records electricity production and consumption based on energy source types. The Mamdani method employs triangular membership functions to define rules and provides output in the form of membership degrees for low, medium, and high efficiency levels. On the other hand, the Tsukamoto method utilizes a linear membership function-based approach to compute output based on direct correlations between input variables and output. Comparative analysis reveals differences in the accuracy and sensitivity of both methods to variations in electricity consumption data. The findings highlight the strengths and weaknesses of each method in the context of complex electricity consumption predictions.
Implementasi Sistem Pengenalan Wajah dengan Integrasi Firebase untuk Manajemen Kehadiran Real-Time Syamjovanka, Revelin Putri; Citra Firdausi, Putri Aulia; Ana, Vika Rafi; Sari, Anggraini Puspita
Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research Vol. 1 No. 4 (2024): AGUSTUS-OKTOBER 2024
Publisher : UNIVERSITAS SERAMBI MEKKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/mister.v1i4.2111

Abstract

In the era of digitalization of education, administrative efficiency is the main focus of educational institutions to improve services. This research examines the application of a facial recognition system as a solution for updating the student attendance system at the University Pembangunan Nasional “Veteran” Jawa Timur. The manual methods currently used were identified as the main cause of inefficiencies and inaccuracies. Through Firebase integration, this system is implemented to enable real-time attendance management. Tests carried out on the University Pembangunan Nasional “Veteran” Jawa Timur (UPN Jatim) campus showed significant improvements in managing student attendance. The results show that this system provides an effective and efficient solution to administrative problems, with high accuracy and significant time reduction in the student attendance process.
Analisis Sentimen Ulasan Pengguna Aplikasi Disney+ Hotstar Menggunakan Naive Bayes Classifier Siharta, Niken Febrinikmah; Bhaswara, Maulana Muzakki; Firmantara, Wahyu; Sari, Anggraini Puspita
Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research Vol. 1 No. 4 (2024): AGUSTUS-OKTOBER 2024
Publisher : UNIVERSITAS SERAMBI MEKKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/mister.v1i4.2120

Abstract

This research suggests an approach using Naive Bayes classification to analyze the sentiment from the user reviews of the Disney+ Hotstar application on the Google Play Store. Review data is processed using the Naive Bayes classification method. This aims to create a text representation then Naive Bayes will group it into positive, negative or neutral categories. The expression results show that this model is able to overcome problems in terms of sentiment analysis with good accuracy. Evaluation uses several standards, namely accuracy, precision, recall, and F1-Score.With accuracy results of 81,6 %, precision of 58 %, recall of 83%, and f1-score of 68%. The results of this research shows useful information for application developers in improving the quality of their products. Apart from that, they can also see public sentiment towards the Disney+ Hotstar application. The research results can also be adapted to analyze sentiment on other applications available on digital platforms and have a positive impact on technological progress.
Analisis Perbandingan Klasifikasi Obesitas Menggunakan Metode K-Nearest Neighbor dan Ensemble Learning Septyana, Dwitamara; Maharani, Dian; Elizabeth, Caritta; Agustiardani, Salsa Pramudhita; Sari, Anggraini Puspita
Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research Vol. 1 No. 4 (2024): AGUSTUS-OKTOBER 2024
Publisher : UNIVERSITAS SERAMBI MEKKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/mister.v1i4.2161

Abstract

Penyakit obesitas adalah suatu permasalahan yang tidak mudah dihindari oleh manusia karena berkaitan dengan kesehatan serta gaya hidup sehari hari. Oleh karena itu, penting untuk memberikan kontribusi dalam pengembangan alat diagnostik yang lebih cerdas dan berbasis data yang dapat dimanfaatkan oleh tenaga kesehatan profesional dalam mengidentifikasi seorang individu yang berisiko mempunyai permasalahan obesitas dan merancang intervensi yang lebih personal dan efektif. Tujuan dari penelitian ini untuk mengembangkan model prediksi obesitas dengan mengimplementasikan metode K-Nearest Neighbor (KNN) dan Ensemble Learning dari Naive Bayes dan Random Forest. Pada penelitian ini mengindikasikan bahwa algoritma KNN menghasilkan nilai akurasi sebesar 89,60%, sedangkan metode Ensemble Learning dari Naive Bayes dan Random Forest menghasilkan nilai akurasi sebesar 89,36%. Dari kedua metode yang digunakan, KNN lebih efektif dalam mendeteksi jenis obesitas berdasarkan dataset yang digunakan, dibandingkan dengan metode Ensemble Learning dari Naive Bayes dan Random Forest. Hasil ini menunjukkan bahwa pemilihan algoritma yang tepat sangat penting dalam pengembangan sistem klasifikasi obesitas yang lebih akurat dan efisien
Sistem Rekomendasi Film Berbasis Konten Menggunakan Teknik Cosine Similarity dan TF-IDF AZMI, ANDRA HUSNUL; MAHARDIKA, NAUFAL INDRA; ANUGRAH PRASETYA, RAJAWALI SHAKTIKA; PUSPITA SARI, ANGGRAINI
Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research Vol. 1 No. 4 (2024): AGUSTUS-OKTOBER 2024
Publisher : UNIVERSITAS SERAMBI MEKKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/mister.v1i4.2206

Abstract

The goal of the research is to develop a content-based movie recommendation system that utilizes cosine similarity techniques to get better accuracy and relevance of recommendations to users.The methods used include text analysis of movie synopsis for feature extraction, representation vector generation, and cosine similarity calculation to determine the similarity between movies. Natural language processing is used to understand user preferences and compose recommendations accordingly.The results show that the developed recommendation system is able to enhance the accuracy of movie recommendations based on content, as well as provide a more personalized and relevant experience for users.
Full-Body Tracking Berbasis OpenCV dan MediaPipe untuk Interaksi Objek Virtual Putricia Hendra, Ria Amelia Shinta; Prapatoni, Velian; Arryanto, Bahiskara Ananda; Sari, Anggraini Puspita
Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research Vol. 1 No. 4 (2024): AGUSTUS-OKTOBER 2024
Publisher : UNIVERSITAS SERAMBI MEKKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/mister.v1i4.2212

Abstract

This research introduces a system that tracks full body movements in real-time to interact with virtual objects by combining OpenCV and MediaPipe in the Unity3D game engine. The system aims to overcome the drawbacks of current tracking solutions, which typically need unique hardware and are complicated, thus restricting their usability. The suggested method uses OpenCV for capturing and preparing images, while MediaPipe Pose is chosen for its precise and efficient real-time body landmark detection. The information on the user's body position is sent to Unity3D through a named pipe system, allowing accurate management of a 3D character's actions. Tests on two devices with varying hardware specifications indicated that the system successfully monitors body positions and movements in real-time, enabling interactive interaction with virtual objects in Unity3D. An examination of performance indicated that the processing speed, accuracy of landmark detection, and frame rate are all notably affected by the hardware specifications, especially the processor and GPU. Devices with higher specifications significantly offered a more seamless and speedy user experience. The study suggests that merging OpenCV and MediaPipe provides a precise and effective method for tracking full body movements, suitable for different interactive settings like virtual and augmented reality.
Klasifikasi Uang Kertas Rupiah Baru Menggunakan Metode CNN Syahrul Amin, Akhmad; Riandi Zahra, Muhammad Alvin; Jibran, Kemal Fahreza; Puspita Sari, Anggraini
Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research Vol. 1 No. 4 (2024): AGUSTUS-OKTOBER 2024
Publisher : UNIVERSITAS SERAMBI MEKKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/mister.v1i4.2218

Abstract

This study introduces an advanced system for classifying Indonesian Rupiah (IDR) banknotes using Convolutional Neural Networks (CNNs). By harnessing sophisticated image processing techniques, the system analyzes surface patterns on banknotes and categorizes them based on distinct visual features to determine their denominations. The research utilizes a comprehensive dataset containing 1190 images across various IDR denominations, captured at a standardized resolution of 224x224 pixels. Prior to model training, meticulous data preprocessing techniques such as resizing, augmentation, and normalization are employed to optimize dataset quality and enhance model robustness. The CNN architecture is specifically designed with convolutional and pooling layers to automatically extract intricate features from banknote images, culminating in a softmax output layer for precise classification. Training the model through multiple epochs ranging from 50 to 150 showcases notable enhancements in accuracy, achieving up to 100% accuracy with minimal loss, indicative of its reliable performance. This research underscores the effectiveness of CNNs in automating banknote classification tasks, promising improved accuracy and efficiency in real-world applications.
Co-Authors Abd Rabi’ Achmad Junaidi Achmad Junaidi, Achmad Achmad Yusuf Yulestiono Adhi Dwi Saputra Adiguna Yudhanto Adila, Mar’atul Aditya, Wigananda Firdaus Putra Adiyatma, Hesel Faza Afandi, Rizki Baehtiar Afina Lina Nurlaili Agung Darmawansyah Agung Mustika Rizki, Agung Mustika Agussalim, Agussalim Agustiardani, Salsa Pramudhita Aji Paringga Jati Akbar, Fawwaz Ali Akbar, M.Azriel Yaqi Al-Ayyubi, Iqbal Alam, Fajar Indra Nur Aldito Restu Wintama Alfajr, Achmad Yuneda Alfi Hendri Alhamda, Denisa Septalian Alif Bayu Ammarizky Alif Ernanda Putra Amrullah, Ahmad Wildan Ana, Vika Rafi Andre Leto Andreas Nugroho Sihananto Andreas Nugroho Sihananto Anindhyta, Erisa Dwi Xena Aninidta, Sophia ANUGRAH PRASETYA, RAJAWALI SHAKTIKA Aqil Salim, Mas Muhammad Ar Rafi, Mohammad Hafiz Ardelia, Danika Najwa Ardiansyah, Muhammad Dafa Ardiansyah, Muhammad Naufal Arhinza, Rayhan Saneval Ariando, Aldo Pradana Aries Boedi Setiawan Arif Nur Cahyo Arif Rahman Hakim Arif Widiasan Subagio Arifani, Kahpi Baiquni Arifin, Hilda Desfianty Arini, Andhini Putri Ariningtyas, Imelda Dwi Arryanto, Bahiskara Ananda Arthansa, Radendha Muhammad Aryananda, Rangga Laksana Awang Mohammad Ziadhasya Rizqaarrafi AZMI, ANDRA HUSNUL Azzahra Adelia Sabrina Salsabila Azzahra Asti Khairunnisa Bagus Satrio Wicaksono Basuki Rahmat Masdi Siduppa Bayu Setiawan Belva Cynara Trana Putri, Prudencia Bhaswara, Maulana Muzakki Bimantoro, Ryan Bagus Binti Hasim, Norhaslinda Budiman, Daniel cahyono, wahyu eko Cinta Ramayanti Citra Firdausi, Putri Aulia Damai Arbaus, Damai Damayanti, Natasya Meryl Daniswara, Sena Danu Satrio Dea Rajwa Zahra Athaya Dela Puspita Lasminingrum Deswita Choirun Nisa Dewi, Shanty Kurnia Dian Maharani, Dian Dimas Satria Prayoga Dody Pintarko Dwi Arman Prasetya Dwi Arman Prasetya Dwi Arman Prasetya Eka Maurita Eka Prakarsa Mandyartha Ekawati, Anies Eko Kuncoro Eko Kuncoro EKO WAHYUDI Elizabeth, Caritta Endyarni, Regina Caeli Eva Salsabilla Fahlefi, Muhammad Reza Fajrina, Nur Septia Farhans, Muhammad Izzudin Fatchur Rozci Fauzan, Daffa Athallah Firdaus Putra Aditya, Wigananda Firmansyah, Fahrul Firmantara, Wahyu Firza Prima Aditiawan Firzannabeel Aqila Rafid Gatot Yulisianto Gatut Yulisusianto Hendri, Alfi Hilya ‘Zada Mardhatilla Al Haadiy Hiroshi Suzuki Icham, Maulana Izuddin Audadi idhom, Mohammad Intan Putri Mansyur Pratama Iqbal Bagus Satriawan Irsyadi, Muhamad Haidir Irsyadi, Muhammad Haidir Irsyadi, Muhammad Rohman Irwansyah, Ferry Ishak Febrianto Ismail, Jefri Abdurrozak Jaka Subagja Jamaludin . Jeki Saputra Jibran, Kemal Fahreza Joko Lasmono Jonathan Teguh Samuel Kaeng Julastri, Bregsi Atingsari Kartini Kartini Kartini Kartini KEZIA, KEZIA Khairul Anwar Khairunnisa Khairunnisa Khofifah, Nada Firda krisna krisnawati wati Krisnawati Kuncoro, Eko Ledjap, Adventus Michael Bala Letkol Arh Desyderius Minggu Lina Nurlaili, Afina Lisanthoni, Angela Listanto, Evan Adwitiya Dwi M Julius St M. Rafi Ardiansyah Made Hanindia Prami Swari Maharani, Ardiana Deka MAHARDIKA, NAUFAL INDRA Mahendra, Zenryo Yudi Arnava Darva Makarim, Irsyad Fadhil Maliq Reynanda , Revano Marsanda, Dea Ayu Eka Masyhuri, Alif Syahda Adji Maulana, Hendra Maulana, M. Zaky Pria Maurisa Arimbi Putri Mawadah, Divia Astrina Mayya, Kalfin Syah Kilau Millati, Fina Amru Millati Minggu, Desi Derius Minggu, Desi Derius Moh Avin Dharma Wijaya MOH MARIO SUBAGIO Moh. Misbahul Musthofah Mohammad Idhom Mohammad Quthbul Widad Mohammad, Bawazir Fadhil Muhammad Hilmy Aziz Muhammad Lizamul Arsi Muhammad Muharrom Al Haromainy Mulyani Satya Bhakti Mulyo, Budi Mukhamad Nachrowie, Nachrowie Nadia, Prasinta Hari Nadirco, Daniel Gloryo Nafis Pratama Putra Nandana Wahyu Rizqullah Nicholas, Sandy Ninis Herawati Noor Imansyah Basoeki, Dandy Nugraini Dewi Puspitasari Nur Rachman Nur Rachman Supadmana Muda Nur'afifah, Anya Ningrum Nurdiansyah, Titis Fajar Nurdianto, Muhammad Akbar Oktavia Nur Khasanah OKTAVIAN, JAGUAR DEVA NANGGALASAKTI OKTAVIAN Olivia Dewi Ramadhani Suryoningsih Panggih Santri Paramita, Maheswari Dian Pintarko, Dody Prakoso, Akbar Tri Pramudyo, Leon Ddewandaru Prapatoni, Velian Prasetyo, Edi Dwi Pratama Putra, Moch Aditya Pratama, Hendrico Edhent Surya Pratama, Moch Nasikh Andhyka Prismahardi Aji Riyantoko Putra Dwi Wira Gardha Yuniahans Putra, Chrystia Aji Putri Salsabila, Belia Putricia Hendra, Ria Amelia Shinta Rahman, Fatan Izzatur Rahman, Muhammad Fadhillah Rahmawati, Deisya Dzakiyyah Rahmawati. S, Abel Dwi Ramadhani, Aimee Natya Ramadhani, Neo Rendra Ardika Resti Indah Paramita Sari Revano Maliq Reynanda Riandi Zahra, Muhammad Alvin Ridho Fajar Fahturohman Riky Hermawan Ririn Wanandi Rizki, Agung Mustika Rochmawati, Febriyan Putri Rofiah, Muflichatur Romadhoni, Firman Rozi, Atiqur Ryan Purnomo Sagita, Dhea Intan SALMAN ALFARIZI Samdono, Arif Sampurno Utomo, Moch Wahyu Sanjaya, I Wayan Indra Sakti Sanjaya Santoso, Aries Satriya Yudha Saskia Rafika, Chesa Satrio Dharma Putra Satwika, I Kadek Susila Septyana, Dwitamara Setiawan, Aries Buedi Siharta, Niken Febrinikmah Silitonga, Paulenta Silvania Sischa Wahyuning Tyas Siti Sri Wahyuni Subairi Subairi Sugeng Harianto SUGENG HARIANTO Sugiarto S Suherman Suherman Suryahadi, Farrel Zikri Suryangga, Nova Suryantari, Putu Anggi Syahbana, Ahmad Nadhif Fikri Syahrul Amin, Akhmad Syamjovanka, Revelin Putri Takahiro Kitajima Takashi Yasuno Tanjung, Mutiq Anisa Tatipang, Angeline Riendra Torrilynn Farrell Zuriely Tresna Maulana Fahrudin Ulummuddin, Ikhya Wardana, Nabila Sya’bani Wicaksono, Faris Hakim Widoretno, Astrini Aning Widya Indah Sujatmoko, Amanda Wisnu Murti, Hapsoro Yisti Vita Via Yogi Dwi Arsanti Yossie Triwinanda, Rizqullah Sandya Yunizar, Sri Fatmawati Zahran, Muhammad Sulthan Zidan, Ahmad Ziddan, Muhtasar Zulkarnaen, Fahri Izzuddin