Article Per Year (5 Year)
p-Index From 2021 - 2026
0.882
P-Index
This Author published in this journals
All Journal Antivirus : Jurnal Ilmiah Teknik Informatika Telcomatics International Journal of Applied Mathematics, Sciences, and Technology for National Defense
Fajri Farid
Institut Teknologi Sumatera
Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mathematics Physics

Published : 5 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 5 Documents
Search

 1 
The conceptual model to improve failure risk management water distribution system using ordinary differential equation model to support water resilience in military residential facilities Fulkan Kafilah Al Husein; Muhamad Syazali; Suhaila Saidat; Nursyiva Irsalinda; Fajri Farid
International Journal of Applied Mathematics, Sciences, and Technology for National Defense Vol. 2 No. 3 (2024): International Journal of Applied Mathematics, Sciences, and Technology for Nati
Publisher : FoundAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/app.sci.def..v2i3.341

Abstract

Water resilience is still big problem in Indonesia.  In border and underdeveloped areas in Indonesia, the use of water sources is still considered not resilience. Especially in military context, where water needs are bigger and also more fundamental, this water resilience problem demanding a comprehensive solution. To address this issue, this research proposes the use of ordinary differential equations as a mathematical tool to model the dynamics of system damage over time, consumption, maintenance scheme, water crisis scheme, and other factors affecting water distribution resilience in military facilities. This journal presents a conceptual model of failure risk management water distribution system using a differential equation model approach to support water resilience. Specifically, the derivation of failure equation in the “reliability and maintenance system technical” textbook will be the basic reference for generating mathematical model. It is used because our model will be focused in improving failure risk management. By using the model, there are a lot of problem will be tackled such as Identify and manage failure risks in the water supply system, design an efficient water distribution maintenance scheme, and predict how strong the system to face water crisis. But before the model applied, the prediction of model will be tested by applying it in form of computer program. The case study of this research will be focused in testing the model in form of computer program with some simplicity and assumption. Through this approach, it is expected to find solutions that improve water usage efficiency, support the well-being of military personnel, and contribute to national water resilience to bolster national defense especially in case of water crisis happened. This research holds significant benefits for scientific advancement by providing a conceptual model that can serve as a reference for future research. It has the potential to make a tangible contribution but also still need so much development especially for application in real data, adding others variables that can be included for next research, conducting the interpretation, and better defining the measurement boundaries.
THE APPLICATION OF MULTINOMIAL NAIVE BAYES FOR SENTIMENT ANALYSIS OF CULTURAL TOURISM REVIEWS: A CASE STUDY OF BOROBUDUR AND PRAMBANAN TEMPLES Irvan Alfaritzi; Baruna Abirawa; Smertniki Javid Ahmedthian; M. Syamsuddin Wisnubroto; Fajri Farid; Meida Cahyo Untoro
Antivirus : Jurnal Ilmiah Teknik Informatika Vol 20 No 1 (2026): Mei 2026
Publisher : Universitas Islam Balitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35457/dj70zr92

Abstract

Abstract : Candi Borobudur dan Candi Prambanan dikenal sebagai dua situs warisan dunia UNESCO, yang memiliki nilai sejarah dan budaya tinggi. Penelitian ini berfokus pada analisis komparatif sentimen wisatawan berdasarkan 10.000 ulasan yang diambil dari Google Maps. Tujuannya adalah mengidentifikasi persepsi wisatawan terhadap dua destinasi sekaligus mengevaluasi aspek kekuatan dan kelemahannya untuk memberikan umpan balik berbasis data bagi pengelola wisata. Metodologi yang diterapkan menggunakan pendekatan hibrida: data ulasan dikumpulkan melalui web scraping, diterjemahkan ke Bahasa Inggris dan dilabeli secara otomatis menggunakan VADER (Valence Aware Dictionary and sEntiment Reasoner). Setelah tahap preprocessing dan pembobotan fitur menggunakan TF-IDF, model klasifikasi Multinomial Naive Bayes dilatih untuk memprediksi polaritas sentimen. Hasil analisis menunjukkan bahwa Candi Prambanan memiliki proporsi sentimen positif sebesar 82,5%, lebih tinggi dibandingkan Candi Borobudur sebesar 73,7%. Model klasifikasi mencapai akurasi 81,9% untuk Prambanan dan 74,7% untuk Borobudur. Visualisasi word cloud mengindikasikan keluhan negatif yang berulang, seperti “panas”, “harga tiket”, dan “parkir”. Analisis ini menunjukkan adanya perbedaan signifikan dalam persepsi pengunjung terhadap kedua destinasi dan memberikan kontribusi praktis dalam pengembangan strategi peningkatan kualitas layanan wisata berbasis analisis sentimen. English Abstract: Borobudur Temple and Prambanan Temple are known as two UNESCO world heritage sites, possessing high historical and cultural value. This research focuses on a comparative sentiment analysis of tourists based on 10,000 reviews taken from Google Maps. The objective is to identify tourist perceptions of the two destinations while also evaluating their strengths and weaknesses to provide data-driven feedback for tourism management. The methodology applied uses a hybrid approach: review data is collected via web scraping, translated into English, and automatically labeled using VADER (Valence Aware Dictionary and sEntiment Reasoner). After the preprocessing stage and feature weighting using TF-IDF, a Multinomial Naive Bayes classification model is trained to predict sentiment polarity. The analysis results show that Prambanan Temple has a higher proportion of positive sentiment at 82.5%, compared to Borobudur Temple at 73.7%. The classification model achieved an accuracy of 81.9% for Prambanan and 74.7% for Borobudur. Word cloud visualizations indicated recurring negative complaints, such as “panas” (hot), “harga tiket” (ticket price), and “parkir” (parking). This analysis indicates a significant difference in visitor perceptions of the two destinations and provides a practical contribution to developing strategies for improving tourism service quality based on sentiment analysis.
Penerapan Algoritma K-Means untuk Pengelompokan Halte Transjakarta Berdasarkan Aktivitas Harian Penumpang Esteria Rohanauli Sidauruk; Anisa Fitriyani; Akmal Faiz Abdillah; M Syamsuddin Wisnubroto; Fajri Farid
Telcomatics Vol. 11 No. 1 (2026)
Publisher : Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/telcomatics.v11i1.11462

Abstract

Ketidakseimbangan aktivitas di halte bus Transjakarta, yang menyebabkan kemacetan dan penumpukan penumpang pada titik-titik tertentu, menjadi tantangan penting dalam peningkatan efisiensi layanan transportasi publik perkotaan. Penelitian ini bertujuan untuk mengelompokkan halte bus Transjakarta berdasarkan pola aktivitas penumpang harian (pagi, siang, sore, dan malam) menggunakan algoritma K-Means Clustering pada dataset transaksi Transjakarta. Setelah tahap pra-pemrosesan data dan penentuan jumlah klaster optimal dengan metode Elbow, diperoleh dua klaster (K=2) yang menunjukkan perbedaan signifikan.Klaster 0 merepresentasikan halte dengan tingkat aktivitas rendah yang menandakan pemanfaatan minimal, sedangkan Klaster 1 mencakup halte dengan volume aktivitas tinggi, terutama padaperiode sore hari. Visualisasi peta interaktif menunjukkan distribusi geografis yang jelas: halte dengan aktifitas sibuk (berwarna merah) terkonsentrasi di pusat kota Jakarta, sementara halte dengan aktifitas rendah (berwarna biru) tersebar di wilayah pinggiran. Hasil pengelompokan ini dapat dimanfaatkan oleh manajemen Transjakarta dan Dinas Perhubungan DKI Jakarta sebagai dasar dalam pengambilan keputusan strategis, seperti pengalokasian armada dan penyesuaian jadwal keberangkatan yang lebih adaptif terhadap tingkat permintaan di Klaster 1, serta evaluasi efektivitas operasional halte di Klaster 0. Evaluasi model menghasilkan nilai Silhouette Score sebesar 0.7205 yang menandakan pemisahan klaster yang baik, dan Davies-Bouldin Index sebesar 0.8763, yang mengindikasikan klaster yang cukup kompak dan terpisah. Penelitian ini memberikan kontribusi praktis bagi perencanaan transportasi publik berbasis data dalam mendukung kebijakan distribusi layanan yang lebih merata di seluruh jaringan Transjakarta.
Implementasi K-Means Mengelompokkan Kabupaten/Kota Berdasarkan Faktor Sosial-Ekonomi untuk Prioritas Alokasi Bantuan Sumatera Selatan 2023 Asa Do'a Uyi; Siti Nur Aarifah; Dwi Ratna Anggraeni; M. Syamsuddin Wisnubroto; Fajri Farid
Telcomatics Vol. 11 No. 1 (2026)
Publisher : Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/telcomatics.v11i1.11546

Abstract

Pembangunan manusia merupakan salah satu indikator utama keberhasilan pembangunan suatu daerah yang menjadi dasar perencanaan pembangunan berkelanjutan. Penelitian ini bertujuan mengelompokkan kabupaten/kota di Provinsi Sumatera Selatan berdasarkan indikator sosial-ekonomi yang membentuk Indeks Pembangunan Manusia (IPM) dengan menerapkan algoritma K-Means Clustering. Data yang digunakan berasal dari Badan Pusat Statistik (BPS) tahun 2023. Kualitas hasil klasterisasi dievaluasi melalui Davies-Bouldin Index dan Silhouette Score untuk menilai tingkat pemisahan antar klaster dan konsistensi data. Hasil analisis menunjukkan terbentuknya tiga kelompok wilayah rendah, sedang, dan tinggi dengan distribusi masing-masing 3, 13, dan 1 daerah. Temuan ini mengindikasikan masih adanya ketimpangan kualitas pembangunan manusia di Sumatera Selatan, terutama pada aspek pendidikan dan pengeluaran riil per kapita. Nilai Davies-Bouldin Index sebesar 0,9698 dan Silhouette Score sebesar 0,3313 menunjukkan bahwa hasil pengelompokan cukup baik dan dapat digunakan sebagai acuan dalam penentuan prioritas alokasi bantuan. Dengan demikian, penerapan algoritma K-Means dapat membantu pemerintah daerah dalam memetakan kondisi pembangunan manusia secara objektif dan mendukung pengambilan kebijakan yang lebih tepat sasaran.
Public Sentiment Analysis Toward the Ministry of Finance 2025 Using Recurrent Neural Network Methods Based on Data from Sosial Media X Muhammad Regi Abdi Putra Amanta; M. Syamsuddin Wisnubroto; Fajri Farid; Aditya Rahman; Sofyan Fauzi Dzaki Arif
Telcomatics Vol. 11 No. 1 (2026)
Publisher : Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/telcomatics.v11i1.11645

Abstract

The Ministry of Finance plays a strategic role in maintaining national economic stability through fiscal policy management, taxation, public debt administration, and state budget control. In today’s digital era, social media platforms such as X have become important channels for the public to express opinions about government policies. This study analyzes public perceptions of the Ministry of Finance’s performance using machine-learning-based sentiment analysis and identifies the most effective classification model. Data were collected from public posts on X and processed using text mining and Natural Language Processing (NLP). Three Recurrent Neural Network (RNN) models were tested: Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and an improved variant, LSTM_G. The findings show that negative sentiment dominates at 43.0%, followed by neutral at 33.9% and positive at 23.1%. Among the models, LSTM_G achieved the highest accuracy of 78.98%, indicating strong capability in capturing sequential patterns in dynamic, unstructured social media text. These results reflect substantial public concerns regarding fiscal policies and demonstrate the usefulness of sentiment analysis as a data-driven tool for decision-making and for strengthening public communication strategies to enhance the Ministry’s digital reputation.
Co-Authors Aditya Rahman Akmal Faiz Abdillah Anisa Fitriyani Asa Do'a Uyi Baruna Abirawa Dwi Ratna Anggraeni Esteria Rohanauli Sidauruk Fulkan Kafilah Al Husein Irvan Alfaritzi M Syamsuddin Wisnubroto M. Syamsuddin Wisnubroto M. Syamsuddin Wisnubroto Muhamad Syazali Muhammad Regi Abdi Putra Amanta Nursyiva Irsalinda Siti Nur Aarifah Smertniki Javid Ahmedthian Sofyan Fauzi Dzaki Arif Suhaila Saidat Untoro, Meida Cahyo