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All Journal TEKNIK INFORMATIKA Speed - Sentra Penelitian Engineering dan Edukasi Jurnal Inovasi Teknologi Pendidikan Proceeding SENDI_U Proceeding of the Electrical Engineering Computer Science and Informatics Format : Jurnal Imiah Teknik Informatika Jurnal Informatika Universitas Pamulang JSiI (Jurnal Sistem Informasi) JURNAL TEKNIK JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI JIKA (Jurnal Informatika) Jurnal Inovasi Informatika Journal of Intelligent Computing and Health Informatics (JICHI) International Journal Of Science, Technology & Management (IJSTM) Jurnal Algoritma, Logika dan Komputasi Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) SPEED - Sentra Penelitian Engineering dan Edukasi Jurnal Minfo Polgan (JMP) Joutica : Journal of Informatic Unisla Jurnal Keuangan dan Akuntansi Terapan (KUAT) Jurnal Pengabdian Pada Masyarakat Prosiding Simposium Nasional Multidisiplin (SinaMu) Prosiding Seminar Nasional Pemberdayaan Masyarakat (SENDAMAS) Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics IJISCS (International Journal of Information System and Computer Science)
Angga Aditya Permana
SINTA ID: 6091531 - SCOPUS ID: 57220893679 - Universitas Multimedia Nusantara
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Enhancing Early Diagnosis of Heart Disease: A Comparative Study of K-NN and Naive Bayes Classifiers Using the UCI Heart Disease Dataset Permana, Angga Aditya; Arsanah, Arsanah
Journal of Intelligent Computing & Health Informatics Vol 5, No 1 (2024): March
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v5i1.11251

Abstract

Heart disease remains a leading cause of mortality globally, necessitating accurate predictive models for early detection and intervention. This study conducted a detailed comparative analysis of the K-nearest neighbor (KNN) and naive bayes classifiers using the UCI Repository Heart Disease dataset to determine the most effective algorithm for heart disease prediction. Our results demonstrate that the proposed KNN outperforms naive bayes in terms of several key metrics: KNN achieved an accuracy of 91.25%, which surpasses naive bayes' accuracy of 88.75%. Additionally, KNN exhibited superior precision (92%), recall (90%), and an F1 score (91%) compared to naive bayes, which demonstrated precision of 89%, recall of 87%, and an F1 score of 88%. The findings of this study have substantial practical implications for medical data analysis. The high accuracy and reliability of the KNN algorithm make it a valuable tool for healthcare professionals in the early diagnosis of heart disease. Implementing KNN-based predictive models can enhance patient outcomes by timely and accurate detection of heart disease, facilitating early intervention, and reducing the risk of severe cardiac events. Moreover, the user-friendly interface of the proposed system streamlines the classification process, making it accessible for clinical use. Future research should explore the integration of additional machine learning algorithms and ensemble methods to further improve prediction accuracy. Developing real-time prediction systems integrated with electronic health records (EHR) could revolutionize patient monitoring and proactive healthcare management, ultimately contributing to better patient outcomes and more efficient healthcare delivery.
IMPLEMENTASI ALGORTIMA NAÏVE BAYES UNTUK PREDIKSI KELULUSAN MAHASISWA Permana, Angga Aditya; Taufiq, Rohmat; Destriana, Rachmat; Nur'aini, Aliya
Jurnal Teknik Vol 13, No 1 (2024): Januari - Juli 2024
Publisher : Universitas Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/jt.v13i1.10996

Abstract

Pada tingkat perguruan tinggi, pencapaian kelulusan tepat waktu adalah indikator kunci dari keberhasilan mahasiswa. Namun, mengidentifikasi faktor-faktor yang berpotensi memengaruhi kelulusan mahasiswa merupakan tantangan yang kompleks. Oleh karena itu, penelitian ini bertujuan untuk mengembangkan sistem prediksi tingkat kelulusan mahasiswa dengan menggunakan metode Naïve Bayes. Langkah-langkah penelitian mencakup pengumpulan data dari dataset Kaggle, pembersihan data untuk menangani nilai yang hilang atau tidak relevan, transformasi data untuk mempersiapkannya untuk analisis, dan penerapan metode Naïve Bayes sebagai model prediktif. Variabel yang digunakan dalam analisis meliputi jenis kelamin, status mahasiswa, usia, nilai Indeks Prestasi Semester (IPS), nilai Indeks Prestasi Kumulatif (IPK), dan status kelulusan. Hasil eksperimen menunjukkan bahwa model prediksi mencapai akurasi sebesar 89%, dengan presisi sekitar 88% untuk kelas 0 dan 89% untuk kelas 1. Selain itu, recall mencapai sekitar 85% untuk kelas 0 dan 91% untuk kelas 1. Diharapkan hasil penelitian ini dapat memberikan kontribusi penting dalam meningkatkan efektivitas prediksi tingkat kelulusan mahasiswa, sehingga institusi pendidikan dapat mengambil tindakan preventif yang lebih tepat untuk mendukung keberhasilan akademis mahasiswa.
Implementasi Algoritma Naïve Bayes Terhadap Review Aplikasi KFCKU Permana, Angga Aditya; Taufiq, Rohmat; Wijaya, Muhammad Ibnu
Jurnal Teknik Vol 12, No 2 (2023): Juli - Desember 2023
Publisher : Universitas Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/jt.v12i2.10646

Abstract

Analisis sentimen atau Sentimen analysis dalam bahasa Indonesia adalah teknik atau metode yang digunakan untuk identifikasi bagaimana perasaan diungkapkan melalui teks dan bagaimana Perasaan ini dapat diklasifikasikan sebagai positif atau negatif. Salah satu perusahaan makanan cepat saji yang sering mendapatkan sentimen analisis yaitu KFC ( Kentucky Fried Chicken ). Untuk melihat sentimen analisis penelitian ini mengambil sumber data dari Google Play Store. Pada penelitian ini juga digunakan metode Naive Bayes yang bertujuan untuk mengklasifikasikan data dan meningkatkan tingkat akurasi dari metode klasifikasi. Penelitian ini bertujuan untuk menganalisis sentimen konsumen terhadap restoran cepat saji KFC menggunakan pendekatan Naive Bayes berbasis data dari platform Google Play Store. Data diambil dari percakapan dan ulasan pengguna Aplikasi terkait KFCKU dalam kurun waktu tertentu. Metode Naive Bayes digunakan untuk mengklasifikasikan sentimen konsumen menjadi tiga kategori, yaitu positif, negatif, dan netral. Hasil analisis sentimen kemudian dievaluasi untuk menilai tingkat kepuasan dan persepsi konsumen terhadap KFC. Penelitian ini dapat memberikan informasi berharga bagi manajemen KFC untuk meningkatkan kualitas pelayanan dan produk mereka berdasarkan umpan balik konsumen.
Mobile Educational Game of Animal Guess in Android Platform Permana, Angga Aditya; Perdana, Analekta Tiara; Ramadhan, Yanuardi Eka
Jurnal Informatika Vol 6, No 3 (2022): JIKA (Jurnal Informatika)
Publisher : University of Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/jika.v6i3.6811

Abstract

The purpose of this research is to create educative digital learning media, easy to understand by children using the waterfall method, educational games guessing animal names with various categories of animals, which can display animal images, animal sounds and animal animations. All designs in the educational game guess the name of the animal
SENTIMENT ANALYSIS PUBLIC OPINION OF CFW (CITAYAM FASHION WEEK) ON SOCIAL MEDIA TWITTER USING NAÏVE BAYES CLASSIFIER Permana, Angga Aditya; Putra, Permana Perdana
Jurnal Informatika Vol 7, No 1 (2023): JIKA (Jurnal Informatika)
Publisher : University of Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/jika.v7i1.7410

Abstract

Meningkatnya minat para remaja di Indonesia terhadap fashion brand lokal menjadi sebuah kesempatan untuk membawa industry fashion Indonesia kepasar internasional, hal tersebut memicu keinginan masyarakat untuk menjadi seorang fashion designer. Perkembangan fashion inilah yang membuat banyak para remaja untuk dapat mengekspresikan hobinya, salah satunya yaitu di jalan umum tepatnya di kawasan sudirman, atau lebih sering disebut Citayam Fashion Week (CFW). CFW sangatlah menjadi sebuah fenomena pada pertengahan tahun 2022, tetapi banyak sekali masyarakat memiliki pandangan yang berbeda, ada yang menyikapinya dengan positif, adapula yang malah mengkritik, dari sinilah penelitian ini perlu dilakukan untuk dapat menganalisa sentiment yang ada pada media sosial yaitu twitter, langkah penelitian terbagi menjadi beberapa fase yaitu, pengambilan data, preprocesing, klasifikasi data, dan Kesimpulan serta saran lalu metode yang diimplementasikan yaitu naïve bayes classifier dengan evaluasi menggunakan confusion matrix, dengan hasil akurasi sebesar 84%. Penelitian ini bermanfaat untuk  mengekstraksi opini – opini dari media social twitter terkait CFW dengan hasil lebih banyak respon positif terhadap CFW
Development of Virtual Painting Method using OpenCV Library with Finger Gesture on Online Learning Platform Ramadhan, Glenn; Wiratama, Jansen; Permana, Angga Aditya
Jurnal Informatika Vol 6, No 3 (2022): JIKA (Jurnal Informatika)
Publisher : University of Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/jika.v6i3.6875

Abstract

With the pandemic situation that has occurred for the last two years to date, educators and students carry out many learning activities online. Learning activities are carried out using virtual meeting media, the concept of meetings and discussion processes that are carried out virtually with existing digital communication devices. From the problems, it was found that students were likelier to be less active when learning theory than practice, which made it difficult for educators to find various media that would be given to students to support online learning activities to be more interactive. This study discusses the creation of a system that can be a medium for delivering helpful material to improve the quality of interaction between educators and students. A virtual painter is one of the media to support the online interactive learning process, where educators can complete the material presented with a clearer picture that educators provide to students. Virtual painters are used to tracking finger pattern movements where the user moves his hand as needed, namely drawing and release, which educators can use to deliver more interactive material to students in theoretical and practical learning. The system design method used in building the virtual painting is Rapid Application Development (RAD) which is carried out through 8 stages, starting from Requirements Analysis to Operation and Maintenance. Next, the diagram design uses UML notation and the phyton with OpenCV coding process. After the virtual painter had been made, an evaluation was conducted and resulted in a positive impression of all six scales: attractiveness, efficiency, clarity, precision, stimulation, and novelty.
Enhancing Website Marketing Through Effective Seo Strategies: A Case Study of Entrefine Ferdinand, Rico; Permana, Angga Aditya
JURNAL FASILKOM Vol. 14 No. 2 (2024): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v14i2.7392

Abstract

The Industrial Revolution 4.0 has influenced consumer behavior, as they use the internet to seek information. This has led to businesses shifting their marketing strategies towards digital marketing. Entrefine sells products such as data management analysis systems and Excel training for corporate employees. One crucial aspect to consider the high number of companies selling similar products, resulting in fierce competition among businesses. The solution to this problem is to design and develop a new website as an information system to offer Excel training services, enhance management efficiency and cost-effectiveness, and implement SEO on the website to improve its search engine rankings, thereby increasing the chances of attracting internet users. The System Development Life Cycle (SDLC) method using the Waterfall model is employed in website development, as it is suitable for systems with low complexity, ensuring well-scheduled and easily controlled project execution. The built system can be deemed successful as the website scored 100% in functionality testing and operates smoothly. The implementation of SEO has proven to be effective, generating a total of 341 traffic and achieving an average ranking of 8.4 within a short period.
Sosialisasi Aplikasi Nutrition Monitoring (NUTRIMO) Pencegah Stunting di Puskesmas Kecamatan Pasar Kemis Permana, Angga Aditya; Perdana, Analekta Tiara; Mulyati, Sri; Amanda, Ivan Nur
Jurnal Pengabdian Pada Masyarakat Vol 10 No 2 (2025): Jurnal Pengabdian Pada Masyarakat
Publisher : Universitas Mathla'ul Anwar Banten

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30653/jppm.v10i2.1026

Abstract

Kekurangan gizi kronis pada anak di bawah lima tahun (balita) dapat menyebabkan stunting. Stunting memengaruhi kecerdasan anak sehingga dapat menurunkan kualitas sumber daya manusia. Salah satu upaya untuk menurunkan kasus stunting adalah pendampingan kabupaten/kota, desa dan masyarakat. Puskesmas Pasar Kemis merupakan salah satu fasilitas kesehatan di Kecamatan Pasar Kemis. Berdasarkan survei terhadap warga Kecamatan Pasar Kemis, permasalahan yang terjadi adalah minimnya pengetahuan masyarakat tentang standar penilaian status gizi serta penggunaan aplikasi berbasis teknologi informasi untuk memantau status gizi belum optimal. Kegiatan pengabdian kepada masyarakat (PkM) ini bertujuan memberikan edukasi melalui sosialisasi perkembangan kondisi stunting di Indonesia, deteksi dini tumbuh kembang balita melalui kartu menuju sehat dan memanfaatkan teknologi dalam memantau tumbuh kembang anak dalam hal ini aplikasi nutrition monitoring (nutrimo). Kegiatan sosialisasi dilakukan di Aula Kantor Desa Pasar Kemis. Sejumlah 50 peserta sosialisasi dievaluasi menggunakan metode quassy experiment design (desain eksperimen semu) dengan one group pretest – posttest untuk mengukur tingkat pengetahuan peserta. Kegiatan PkM berlangsung dengan baik dan lancar. Hasil evaluasi menunjukkan peningkatan persentase pengetahuan peserta terkait standar yang digunakan untuk mengukur status gizi balita dan aplikasi pemantauan status gizi balita berbasis perangkat bergerak (mobile) android. Berdasarkan hasil evaluasi, aplikasi nutrimo mudah digunakan dan memiliki fitur-fitur yang bermanfaat. Chronic malnutrition in children under five years old (toddlers) can cause stunting. Stunting affects children's intelligence so that it can reduce the quality of human resources. One effort to reduce stunting cases is assistance from districts/cities, villages and communities. Pasar Kemis Health Center is one of the health facilities in Pasar Kemis District. Based on a survey of residents of Pasar Kemis District, the problems that occur are the lack of public knowledge about nutritional status assessment standards and the use of information technology-based applications to monitor nutritional status is not optimal. This community service (PkM) activity aims to provide education through socialization of the development of stunting conditions in Indonesia, early detection of toddler growth and development through healthy cards and utilizing technology in monitoring child growth and development in this case the nutrition monitoring application (nutrimo). The socialization activity was carried out in the Pasar Kemis Village Office Hall. A total of 50 socialization participants were evaluated using the quasi-experimental design method with one group pretest - posttest to measure the level of participant knowledge. The PkM activity went well and smoothly. The evaluation results showed an increase in the percentage of participant knowledge related to the standards used to measure toddler nutritional status and the toddler nutritional status monitoring application based on Android mobile devices. Based on the evaluation results, the nutrimo application is easy to use and has useful features.
INTERNAL RESEARCH BUDGET PROPOSAL FEATURES DEVELOPMENT ON RESEARCH AND COMMUNITY OUTREACH SERVICES WEB-BASED INFORMATION SYSTEM AT PRIVATE CAMPUS Noveriyanti, Dea; Wiratama, Jansen; Permana, Angga Aditya; Wijaya, Santo Fernandi; Nugroho, Antonius Sony Eko
IJISCS (International Journal of Information System and Computer Science) Vol 7, No 3 (2023): IJISCS (International Journal of Information System and Computer Science)
Publisher : Bakti Nusantara Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/ijiscs.v7i3.1595

Abstract

Service processes using conventional methods have many limitations and have the potential to result in data accumulation and repetitive work. Transforming a service model that initially used Linktree into an Information System has become necessary for the Research and Community Service Institute (LPPM) of Multimedia Nusantara University (UMN). One of the features developed is the budget Proposal of Internal Research service feature. The Agile Development Method, a renowned software development methodology, is used to optimize the feature development of the RCOS Information System. The development process is carried out by benchmarking, user interviews, and prototyping, following the stages contained in the Agile Development Method. The leverage of the Laravel framework and Tailwind CSS play a pivotal role in developing a website-based RCOS information system. The service model was successfully transformed using the RCOS feature, and the test results with the User Acceptance Test (UAT) show that the Budget Proposal of Internal Research features in the RCOS information system can function well following the UMN LPPM service needs.
Graph Analysis for the Discovery of Key Proteins in Type 2 Diabetes Mellitus Permana, Angga Aditya; Romdendine, Muhammad Fahrury; Perdana, Analekta Tiara
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 5 No. 4 (2023): November
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v5i4.189

Abstract

One of the metabolic diseases with a rising prevalence in Indonesia is Type 2 Diabetes Mellitus (T2DM). A collective effort from various sectors is required to seek solutions for T2DM. The proteomic approach, which focuses on proteins and their interactions related to T2DM, can be used to understand this condition. This research aims to model protein interactions associated with T2DM using a network graph, enabling the identification of key proteins that have the potential to serve as therapeutic targets or T2DM biomarkers. The graph analysis method used in this study involved four centrality measures: degree centrality, closeness centrality, betweenness centrality, and eigenvector centrality. The validation method used to confirm the identified proteins is gene set enrichment analysis. The results obtained from the graph analysis using four centrality measures highlighted that seven out of 27 T2DM-related proteins are key proteins; these are: ABCC8, HNF4A, INS, KCNJ11, NEUROD1, PDX1, and SLC30A8. This study concludes that graph analysis on the interaction graph of T2DM-related proteins successfully identified key proteins that could potentially serve as T2DM biomarkers. Further medical investigation is imperative because computational identification alone is not sufficient to confirm the validity of the findings in this study.
Co-Authors Abdul Azis, Muhamad Malik Adhi Kusnadi Ahmad Bregas Prakoso Ahmad Rodoni Alina Primasari Priambudi Alma Pertiwi Amanda, Ivan Nur Analekta Tiara Perdana Analekta Tiara Perdana Anggita Nauli Marpaung Aprilia Damayanti Arsanah, Arsanah Bayu Septian Erlangga Bemby fadillah Deden Kusnanda Destriana, Rachmat Dinar Ajeng Kristiyanti Dinar Ajeng Kristiyanti Dinar Ajeng Kristiyanti Elisabet Dela Marcela Eva Sadiah Fahira Fahira Ferdinand, Rico Habib Amna Henny Leidiyana Henry, Amir Acalapati Herdiansah, Arief Husain, Syepry Maulana Irfan Nasrullah Luigi Ajeng Pratiwi Manorang Sihotang Maskurudin, Muhamad Mifta Alliandry Marfino Muhamad Aldi Setiawan Muhammad Dzulfiqar Ramadhan Wibawanto Muhammad Fany Fahrezi Muhammad Fany Fahrezi Muhammad Nabil Yafi Muhammad Wisnu Prayuda Natasya Yuasan Noveriyanti, Dea Nugroho, Antonius Sony Eko Nur'aini, Aliya Nurdiana Handayani Nurdiana Handayani nurnaningsih, Desi Perdana, Analekta Tiara Permana Perdana Putra Pradipta, Allan Putra, Permana Perdana R Taufiq Ramadhan, Glenn Ramadhan, Muhammad Chezar Ramadhan, Yanuardi Eka Ramadhina, Salsabila Ramadhina, Salsabila Raul Andrian Reynaldy, Deva Alfian RIFQI RIADHI Risma Rohmatul Ummah Rohmat Taufik Rohmat Taufiq Romdendine, Muhammad Fahrury Rudi Firmansyah Salsabila Ramadhina Salsabila Ramadhina Santo Fernandi Wijaya Sri Mulyati Sufyan, Ammar Syafiq, Zahra Syifa Fauziyah Tamam, Gusti Syihabuddin Taufiq, R Taufiq, Rochmat Wahyu Aldhi Noviyanto Wijaya, Muhammad Ibnu Wiratama, Jansen Yanuardi Yanuardi