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All Journal TEKNIK INFORMATIKA Reaktor Mechatronics, Electrical Power, and Vehicular Technology TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics ITEj (Information Technology Engineering Journals) Kultivasi JOIV : International Journal on Informatics Visualization Jurnal Sistem dan Manajemen Industri JRSI (Jurnal Rekayasa Sistem dan Industri) Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Mitra Manajemen Jurnal Kimia Terapan Indonesia Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JURTEKSI Jurnal Sistem Cerdas Linguistik Indonesia Teknologi Indonesia Journal of Data Science and Its Applications Jurnal Instrumentasi INVEST : Jurnal Inovasi Bisnis dan Akuntansi Charity : Jurnal Pengabdian Masyarakat Jurnal Ilmiah Teknik Elektro eProceedings of Engineering SEMNASTERA (Seminar Nasional Teknologi dan Riset Terapan) Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal Polimesin AQILA : Acceleration, Quantum, Information Technology and Algorithm Journal Journal of Production, Enterprise, and Industrial Applications
Fakhrurroja, Hanif
Telkom University
Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry 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 Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Transportation

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Pengembangan Wearable Device untuk Monitoring dan Tracking Pasien Isoman Covid-19 Berbasis Mobile Dina Angela; Hans Melkisedek Simanjuntak; Hanif Fakhrurroja
Jetri : Jurnal Ilmiah Teknik Elektro Jetri, Volume 20, Nomor 1, Agustus 2022
Publisher : Website

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (723.471 KB) | DOI: 10.25105/jetri.v20i1.14081

Abstract

Reducing the spread of the Covid-19 virus and handling every patient affected by Covid-19 are the main targets of the Indonesian government in dealing with the current pandemic. It takes cooperation between individuals. For example, between health workers and patients who are undergoing independent isolation (isoman) due to being infected with Covid-19. Body temperature, heart rate, blood oxygen levels, and patient movement are the main parameters of a Covid-19 patient that must be routinely checked and monitored by health workers. Patients in self-isolation also need to monitor their health conditions while undergoing isolation. Besides being routine, examination and monitoring of the condition of isoman patients also need to be carried out continuously because the patient's condition can change at any time. In this study, a mobile-based wireless Covid-19 patient condition monitoring system was developed so that monitoring can be carried out remotely. This system uses MCP9808 as body temperature, MAX30100 as a sensor for heart rate and blood oxygen levels, and GPS as a sensor for patient movement in isolation locations. The data obtained from each of these sensors will be sent wirelessly to the cloud database using the NodeMCU ESP8266. The data received in the cloud database is displayed in real-time on a mobile-based dashboard and analyzed to obtain information on the progress of the patient's condition. This system is to assist health workers in monitoring the condition of Covid-19 patients remotely and help self-isolated patients to monitor their health without always having direct contact with health workers. Health workers are facilitated to find out the tendency of the patient's condition so that they can make the right decisions and actions.
SENTIMENT ANALYSIS OF PUBLIC OPINIONS TOWARDS TELKOM UNIVERSITY POST PANDEMIC Anindya Prameswari Putri Djakaria; Oktariani Nurul Pratiwi; Hanif Fakhrurroja
JURTEKSI (Jurnal Teknologi dan Sistem Informasi) Vol 10, No 1 (2023): Desember 2023
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i1.2645

Abstract

Abstract: Twitter, as a social media platform, has rapidly grown as a means for people to express their opinions and thoughts on various topics, including education. The number of Twitter users surged to 10.645.000 in 2020, with a significant increase during the pandemic. Telkom University, as a private institution of higher education in Indonesia, has become one of the topics of discussion on Twitter. Users’ opinions about Telkom University vary, ranging from positive to negative. To gain deeper insights into public view, sentiment analysis is essential. The analysis follows the Knowledge Discovery in Databases (KDD) process, utilizing the Naive Bayes classification algorithm. The evaluation results indicate the best accuracy achieved with an 80:20 data split, resulting in an accuracy rate of 82.05%, precision of 82.3%, recall of 82.05%, and F1-Score of 82.08%. The Naïve Bayes model demonstrates good performance for sentiment analysis of public views regarding Telkom University on Twitter.            Keywords: naïve bayes; sentiment analysis; twitter; telkom university.  Abstrak: Media sosial Twitter berkembang pesat sebagai sarana masyarakat berekspresi untuk menuangkan opini dan pikiran mereka mengenai topik apapun, termasuk pendidikan. Pengguna Twitter meningkat tajam hingga 10.645.00 pengguna pada tahun 2020 dan terus meningkat selama pandemi. Telkom University sebagai perguruan tinggi menjadi salah satu topik yang dibicarakan yang berkaitan dengan pendidikan. Pendapat mengenai Telkom University yang diungkapkan oleh pengguna Twitter beragam, baik positif maupun negatif. Analisis sentimen diperlukan untuk memahami pandangan publik lebih mendalam. Digunakan tahapan Knowledge Discovery in Databases dan algoritma klasifikasi Naïve Bayes dalam analisis ini. Hasil evaluasi menunjukkan akurasi paling baik dicapai dengan rasio data 80:20, dengan nilai akurasi sebesar 82.05%, nilai presisi sebesar 82.3%, nilai recall sebesar 82.05%, dan nilai F1-Score sebesar 82.08%. Model klasifikasi Naïve Bayes memiliki performa baik untuk analisis sentimen pandangan publik di Twitter mengenai Telkom University. Kata kunci: analisis sentimen; naïve bayes; twitter; telkom university.
Perancangan Front End Dashboard Admin Website Investa Mengenai Platform Investasi Pertanian Menggunakan Metode Iterative incremental Dini Dwi Andayani; Faishal Mufied Al-Anshary; Hanif Fakhrurroja
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 4, No 4 (2023): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v4i4.253

Abstract

The current digitalization era is where technological conditions have developed in aspects of life. Information needs and activities can be collected easily in one platform that can help people communicate plans effectively. One of them is the agricultural capital loan system. Initially, people borrowed capital by going to cooperatives or banks where they borrowed money. In addition, farmers used to borrow farming equipment from nearby farm shops. Notarizable documents must be attached to the capital loan. Based on these problems, the author has a solution, Investa, a web-based platform that connects farmers and investors. The implemented features are suitable for the virtual representation of information and functions. Investa is planned according to the needs realized according to benchmarking and interview results. This design also has a dashboard to monitor the website. Investa's internal parties can only access the admin dashboard, so the admin receives more data from investors and farmers when accessing Investa. The design of the admin dashboard is made by considering the results of analysis. All the research that has been done produces output in software designs, such as UML diagrams and blueprint prototype designs. The result creates a dashboard website that uses the Iterative, incremental methodology, and the testing process is carried out using black box testing, UAT, and stress testing, which gets a total score of 90 with an average percentage of 86.25 which shows this platform is quite good in preparation for future dashboard development.
Perbandingan Analisis Sentimen Aplikasi Traveloka dan Tiket.com pada Twitter dengan Metode Support Vector Machine Rukmana, Putri Utami; Pratiwi, Oktariani Nurul; Fakhrurroja, Hanif
Jurnal Sistem Cerdas Vol. 6 No. 3 (2023)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v6i3.350

Abstract

The emergence of the COVID-19 pandemic in Indonesia resulted in an economic crisis, including in the world of tourism, which caused a decline in the national economy. With the existence of Online Travel Agencies (OTA) such as Traveloka and Tiket.com, it is hoped that they can help improve the tourism sector for the Indonesian economy. As a popular OTA and to see the opinion of the Indonesian people, it can be seen from public opinion in the form of tweets on the Twitter application. The tweets data will be taken and sentiment analysis will be carried out on the OTA Traveloka and Tiket.com applications which will be classified into certain classes based on opinions and modeling will be carried out using the Support Vector Machine (SVM) algorithm method. This research aims to determine the level of accuracy of the SVM algorithm and find out how sentiment analysis compares between Traveloka and Tiket.com. In the sentiment analysis comparison, in terms of price, Traveloka is superior and in terms of service, Tiket.com is superior. After modeling by comparing splitting data and handling imbalanced data using Synthetic Minority Oversampling Technique (SMOTE), the best SVM accuracy results for the Tiket.com price dataset were 68%, for Traveloka prices it was 97%, for Tiket.com services it was 92%, and for Traveloka services it is 89%.
Water quality assessment monitoring system using fuzzy logic and the internet of things Fakhrurroja, Hanif; Nuryatno, Edi Triono; Munandar, Aris; Fahmi, Muhammad; Mahardiono, Novan Agung
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 14, No 2 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2023.v14.198-207

Abstract

Water utilization has recently been at its highest level of demand. The water needed to be clean, healthy, and determined to be suitable for consumption. Therefore, it is necessary to have a system that can monitor the water quality so thatinformation related to wate r suitability can be received regularly and in real-time. This paper addresses the critical need for real-time water quality monitoring systems. This study proposed a novel approach integrating the Tsukamoto fuzzy algorithm into an internet of things (IoT)-based framework, forming part of the Fuzzy Inference System. Our system serves as a decision support tool, enabling continuous assessment of water quality. The method categorizes water quality into three levels: good, moderate, and unhealthy, providing timely and precise suitability information. The results demonstrate the effectiveness of the fuzzy logic method in delivering accurate output. Through remotely deployed IoT devices, water suitability and status can be monitored and analyzed in real-time over the internet. This research bridges the gap between traditional water quality assessment methods and the demands of our modern, technology-driven society, ensuring a reliable supply of safe and consumable water.
The role of nutrient solutions on Phosphate-solubilizing bacteria population, Phosphorus availability, Phosphorus uptake, growth and yield of Red Chili (Capsicum annuum L.) Fitriatin, Betty Natalie; Ghifari, Raden Faqih Hilmiy; Sofyan, Emma Trinurani; Widiantini, Fitri; Fakhrurroja, Hanif; Simarmata, Tualar
Kultivasi Vol 23, No 3 (2024): Jurnal Kultivasi
Publisher : Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/kultivasi.v23i3.58764

Abstract

Red chili consumption in Indonesia has increased every year. However, with large chili production to meet large consumption, land conversion for various purposes has reduced the harvested area. The efforts to increase the harvested area of chili using Inceptisols soil by providing nutrient solutions to overcome the infertility of the soil using its nutrients. This experiment aims to determine the effect of nutrient solution application on the population of phosphate-solubilizing bacteria, phosphorus availability, phosphorus uptake, growth, and yield of Red Chili (Capsicum annuum L.) in Inceptisols. The experiment was conducted from August 2023 to February 2024 at Ciparanje Experimental Field, Faculty of Agriculture, Padjadjaran University, and the analysis process was conducted at the Laboratory of Soil Biology and Soil Chemistry and Plant Nutrition, Department of Soil Science and Land Resources, Faculty of Agriculture, Universitas Padjadjaran., using a factorial randomized block design with two factors, nutrient solutions concentrates (1200, 1600, 2000 ppm) and nutrient solutions doses (200, 400, 600 mL), resulting in nine treatments and three replications. The results showed that the treatment of nutrient solution concentration and dose increased the number of fruits per plant, fruit weight per plant, and yield of chili with grade A. Treatment with 2000 ppm concentrate + 600 mL dose gave the best results on the number of fruits per plant (44.7 fruits), fruit weight per plant (725g), and grade A chili yield (73 fruits).
PELUANG DAN TANTANGAN TEKNOLOGI ARTIFICIAL INTELLIGENCE (AI) PADA PROSES ROASTING BIJI KOPI Wibowo, Jony Winaryo; Muhaemin, Mimin; Fakhrurroja, Hanif
SEMNASTERA (Seminar Nasional Teknologi dan Riset Terapan) Vol 6 (2024)
Publisher : SEMNASTERA (Seminar Nasional Teknologi dan Riset Terapan)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Kopi adalah salah satu minuman paling umum dan favorit yang dikonsumsi banyak orang di seluruh dunia. Proses roasting kopi memegang peranan penting dalam menentukan rasa kopi. Tahapan dalam proses roasting kopi terdiri dari pengeringan, penguningan, pecahan pertama, roast development, dan pecahan kedua. Dari kelima tahapan tersebut, proses pecahan pertama kopi merupakan awal mula terbentuknya karakteristik biji kopi. Pada tahap ini, seorang penyangrai biji kopi profesional harus memastikan suhu dan waktu yang sesuai agar biji kopi tidak hangus/gosong. Pada alat roasting kopi manual, hal ini menimbulkan ketidakonsistenan hasil roasting biji kopi karena sangat bergantung dari kemampuan dan pengalaman sang penyangrai biji kopi sedangkan pada smart coffee roaster menggunakan sensor dan control cerdas untuk mengoperasikan roaster dan mendapatkan kopi dengan konsistensi terbaik dan akurat. Makalah kali ini membahas tentang peluang dan tantangan yang diperlukan untuk membuat versi terbaik dari smart coffee roaster dari sisi system elektronik, desain, dan Artificial Intelligence (AI). Sistem elektronik terdiri dari sensor, control, dan aktuator. Desain yang Ergonomis, estetis, serta kenyamanan pengguna menjadi kunci utama yang diperlukan untuk membuat desain terbaik. Aplikasi AI mendeteksi kematangan biji kopi dan deteksi suara “retak” dengan memanfaatkan teknologi machine learning. Studi awal dilakukan dengan format audio hasil roasting dan dipisahkan antara audio yang mengandung suara retakan biji kopi dan audio yang tidak mengandung suara retakan biji kopi. Dataset audio tersebut kemudian diubah ke dalam format gambar menggunakan metode Mel-frequency cepstral coefficients (MFCC), untuk kemudian dilakukan pemodelan dengan menggunakan supervised learning convolutional neural network (CNN).
The Influence of IT Leadership on Business Continuity: Analysis of the Role of Digital Governance in Increasing Company Competitiveness Adillah, Muhammad Fauzan Nur; Fakhrurroja, Hanif
INVEST : Jurnal Inovasi Bisnis dan Akuntansi Vol. 4 No. 2 (2023): INVEST : Jurnal Inovasi Bisnis dan Akuntansi
Publisher : Lembaga Riset dan Inovasi Al-Matani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55583/invest.v4i2.704

Abstract

This research aims to explore and analyze the influence of leadership in Information Technology (IT) on company business continuity with a focus on the role of Digital Governance in increasing competitiveness. Using qualitative literature study methods, this research details the background to the importance of digital transformation in the modern business context, as well as investigating the key role played by IT leadership in guiding organizations towards digital success. The data and research objects involve analysis of texts and scientific literature that includes various sources and frameworks related to IT leadership and Digital Governance. It is hoped that the results of this research will provide a deeper understanding of how effective IT leaders can influence a company's business continuity through the application of Digital Governance principles, which in turn will increase the company's competitiveness in the digital era.  
Comparison Of Sentiment Analysis Of Traveloka And Tiket.Com Applications On Twitter Using The Naive Bayes Method Agustiana, Nathifa; Pratiwi, Oktariani Nurul; Fakhrurroja, Hanif
ITEJ (Information Technology Engineering Journals) Vol 8 No 2 (2023): December
Publisher : Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/itej.v8i2.119

Abstract

The country of Indonesia has a strategic geographical position and is also said to be a country that is very rich in natural resources and cultural diversity. One of the supporters of economic growth in Indonesia is tourism. To support the potential of the tourism sector in Indonesia, many online travel agent applications have started to appear. Of the many OTAs, the top two applications were selected, namely the Traveloka and Tiket.com applications. This sentiment analysis requires data from Twitter. This research compares sentiment analysis on the Traveloka and Tiket.com applications in terms of price and service. The method used is naïve Bayes. The goal is to get sentiment information contained in a text with a positive or negative view. With this research, it is hoped that we can see a comparison of sentiment analysis between the Traveloka and Tiket.com applications and be able to find out the level of accuracy of naïve bayes on the Traveloka and Tiket.com applications. The price dataset that gets more positive sentiment is the Traveloka price of 97.2%. In the service dataset that has positive sentiment, Tiket.com is 46.9%. Then, the greatest accuracy was obtained after oversampling the Tiket.com price dataset by 73%, Traveloka prices by 94%, Ticket services by 87% and Traveloka services by 86%.
Penerapan Algoritma Yolo V8 Untuk Pengenalan Pengendara Sepeda Motor Tanpa Helm Dalam Sistem Pemantauan Pelanggaran Lalu Lintas Rais, Muhammad Haidar; Musnansyah, Ahmad; Fakhrurroja, Hanif
eProceedings of Engineering Vol. 12 No. 1 (2025): Februari 2025
Publisher : eProceedings of Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Abstrak — Penggunaan teknologi kecerdasan buatan (AI) telah menjadi relevan dalam berbagai sektor, termasukpenegakan hukum lalu lintas. Berdasarkan Undang-Undang Nomor. 22 Tahun 2009 tentang Lalu Lintas dan AngkutanJalan di Indonesia, Pasal 106 ayat (8) [1] memerintahkan setiap pengendara dan penumpang sepeda motor untukmemakai helm yang memenuhi Standar Nasional Indonesia (SNI) saat melakukan perjalanan. Dalam konteks ini, sisteme-tilang telah diterapkan di banyak kota di Indonesia. Penelitian sebelumnya telah menunjukkan bahwapenggunaan YOLO V8 dapat meningkatkan tingkat akurasi deteksi plat nomor kendaraan dengan menggunakankekuatan komputasi yang lebih sedikit dibandingkan dengan versi sebelumnya. Metodologi CRISP DM digunakan dalampenelitian ini, yang menghasilkan tingkat akurasi yang untuk pendeteksian pengguna sepeda motor yangmenggunakan helm sebesar 86% untuk deteksi pengguna motor yang tidak menggunakan helm sebesar 87% untukpengguna kendaraan roda dua yang menggunakan helm. Selain itu, framework Flask digunakan untukmengembangkan website yang memungkinkan deteksipelanggaran lalu lintas tidak menggunakan helm melalui akses online. Kata kunci — YOLOV8, E-tilang, AI, deteksi helm, CRISP DM
Co-Authors Adi Sutrisno Adi Waskito Adillah, Muhammad Fauzan Nur Agustiana, Nathifa Ahmad Musnansyah Andry Alamsyah Anindya Prameswari Putri Djakaria Anto Tri Sugiarto Arif Abdul Aziz Aris Munandar Asriana Asriana, Asriana Azwar Farrel Wirasena Betty Natalie Fitriatin Binashir Rofi’ah Carmadi Machbub Cindy Septiani Hudaya Deden Witarsyah Deni Kurnia Denis Gresan Yubelas Deris Stiawan Dermawan, M Farhan Hussaini Derry Destian Didit Adytia Dina Angela Dini Dwi Andayani Dita Pramesti Djakaria, Anindya Prameswari Putri Edy Tanu Elsa Melati Nurrachmat Emma Trinurani Sofyan Erlangga, Gilang Faishal Mufied Al Anshary Faishal Mufied Al-Anshary Firdaus, M Ridwan Fitri Widiantini Ghifari, Raden Faqih Hilmiy Hakim, Aqil Rahman Hans Melkisedek Simanjuntak Hariyadi , Karina M., Rahma Kemahyanto Exaudi Lidanta, Fairuz Zahirah Mahardiono, Novan Agung Mimin Muhaemin, Mimin Muharman Lubis Nopendri Nopendri Novan Agung Mahardiono Novan Agung Mahardiono Novan Agung Mahardiono Nuryatno, Edi Triono Oktariani Nurul Pratiwi Permatasari, Yessy Prahastiwi, Narita Ayu Prima Audina Wibowo Puspitasari, Devi Ambarwati Putra Perdana Prasetyo, Aditya Rahayu, Indah Sari Rahman, Jodi Rizki Rahmat Budiarto Rahmat Mulyana Rais, Muhammad Haidar Ramdhani, Fiqri Rimba Pratama Putra Rukmana, Putri Utami Sadewa, Rizki Salsabila, Syifa Aria Sarmayanta Sembiring Sendhitasari, Aulia Ferina Seno Adi Putra Setyorini Setyorini Sudaryati Cahyaningsih Sugiono, - Sutoyo, Edi Syamsiar, Syamsiar Tanu, Edy Tatang Mulyana Tien Fabrianti Kusumasari Tualar Simarmata Utama, Muhammad Hasbi Juri V. Luvita Veithzal Rivai Zainal Veny Luvita Veny Luvita Wibowo, Jony Winaryo Wibowo, Nanang Roni Widianto Soekarnen Wijaya, I Made Darma Putra Yolanda, Mitra Marlina Zuhdi, Hafidh