Article Per Year (5 Year)
p-Index From 2021 - 2026
0.882
P-Index
This Author published in this journals
All Journal CCIT (Creative Communication and Innovative Technology) Journal Journal Sensi: Strategic of Education in Information System MOTIVECTION : Journal of Mechanical, Electrical and Industrial Engineering Innovative: Journal Of Social Science Research
Mas’ud, Ibnu
Unknown Affiliation
Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Public Health Other

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

Found 5 Documents
Search

 1 
Visual Analysis Of Body Signals In Smoker Data To Understand Health Impacts On Python Nasrulloh, Anas; Yusuf, Muhamad; Mas’ud, Ibnu; Toifur, Tubagus; Ikhwanudin, Aolia; Syamhalim, Agianto
Journal Sensi: Strategic of Education in Information System Vol 11 No 1 (2025): Journal SENSI
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/sensi.v11i1.3764

Abstract

In this study, researchers found that 44.4% of people had blood pressure less than 120/80, 58.2% had fasting blood sugar <= 99, 47.7% had hemoglobin > 17.2, and 62% had oral problems and teeth caused by smoking. This research was carried out by visualizing the impact of smoking on blood pressure, fasting blood sugar, hemoglobin and the mouth and teeth in the body using body signal of smoking data obtained from Kaggle which was analyzed and presented in the form of a pie chart using Python.
Implementation of Inverter and Modbus RTU RS-485 Communication in Controlling Induction Motor Speed Mas’ud, Ibnu; Anshory, Izza; Jamaaluddin, Jamaaluddin; Wisaksono, Arief
MOTIVECTION : Journal of Mechanical, Electrical and Industrial Engineering Vol 7 No 1 (2025): Motivection : Journal of Mechanical, Electrical and Industrial Engineering
Publisher : Indonesian Mechanical Electrical and Industrial Research Society (IMEIRS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46574/motivection.v7i1.451

Abstract

As industrial technology continues to advance, the demand for efficient and automated motor control systems is increasing. Three-phase induction motors are widely used due to their durability and efficiency. However, controlling their speed remains a challenge, especially in small-scale applications without expensive systems. Therefore, a precise, affordable, and easy-to-implement motor control solution is needed. This study discusses the implementation of a three-phase induction motor speed control system using the LS G100 inverter and LS XBM-DR16S PLC through the Modbus RTU RS-485 communication protocol. The system is designed without additional expansion boards to simplify the circuit and reduce costs. The methodology used is an engineering and experimental approach, focusing on the measurement of motor electrical parameters such as actual speed (RPM), frequency, voltage, and current. Test results show that the system is capable of precisely controlling motor speed, with an average RPM accuracy of 99.6%, voltage accuracy of 97.2%, and current accuracy of 91.1%. The system has proven to be reliable and efficient for small to medium-scale industrial automation applications and facilitates real-time troubleshooting and monitoring through integrated data communication.
Comparison of Naive Bayes, Decision Trees and SVM Algorithms for Sentiment Classification of JMO Applications Nasrulloh, Anas; Yusuf, Muhamad; Mas’ud, Ibnu; Toifur, Tubagus; Ikhwanudin, Aolia; Syamhalim, Agianto
CCIT (Creative Communication and Innovative Technology) Journal Vol 18 No 2 (2025): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/ccit.v18i2.3510

Abstract

In this study, the researchers found that SVM achieved a precision of 0.75 for negative sentiment and 0.93 for positive sentiment, with recalls of 0.86 and 0.94, and f1-scores of 0.80 and 0.94, and an overall accuracy of 0.88. Naive Bayes showed similar results with a precision of 0.74 for negative and 0.93 for positive, recalls of 0.87 and 0.94, f1-scores of 0.80 and 0.94, and an accuracy of 0.88. Meanwhile, Decision Tree had the lowest precision for negative (0.71) and positive (0.91) sentiment, with recalls of 0.73 and 0.93, f1-scores of 0.72 and 0.92, and an accuracy of 0.85. These findings suggest that SVM and Naive Bayes offer excellent performance in sentiment classification, while Decision Tree, while still effective, performed slightly lower. These results provide valuable guidance in selecting the right algorithm for sentiment analysis on app data. This study compares the effectiveness of three machine learning algorithms—Naive Bayes, Decision Trees, and Support Vector Machine (SVM)—in sentiment classification of JMO apps using review data taken from Google Play Store via web scraping and processed with a Python application. The evaluation is done based on precision, recall, f1-score, and accuracy metrics.
Implementation of Lean UX to Improve the Quality of User Experience (Case Study: PT. XYZ) Yusuf, Muhamad; Nasrulloh, Anas; Ikhwanudin, Aolia; Toifur, Tubagus; Ramadhan, Aditya Duta; Mas’ud, Ibnu
CCIT (Creative Communication and Innovative Technology) Journal Vol 18 No 2 (2025): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/ccit.v18i2.3530

Abstract

The importance of websites in the modern digital world encourages various companies to develop effective user interfaces (UI) and user experiences (UX). This study aims to design the UI/UX design of PT. XYZ's website using the Lean UX method, which focuses on active collaboration with users in developing a Minimum Viable Product (MVP). The Lean UX method involves four main stages: Declare Assumptions, Create MVP, Run Experiments, and Feedback and Research. Testing was carried out using the System Usability Scale (SUS) to measure the level of usability. The results of the study showed that the new UI/UX design significantly improved efficiency and user satisfaction, with a SUS value of 80, which is included in the "Excellent" category. This study makes a significant contribution to website development in the digital sector, especially in designing user-friendly interfaces that are centered on user needs.
The Influence of Islamic Leadership Style on Job Satisfaction with Islamic Work Environemt as a Moderating Varaible Abroza, Ahmad; Ismanto, Bambang; Mas’ud, Ibnu; Fahmi, Arsyad Ali; Agustin, Fatma
Innovative: Journal Of Social Science Research Vol. 4 No. 1 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i1.9006

Abstract

Peneliti berpendapat apabila Gaya Kepemimpinan Partisipatif dapat mempunyai hubungan yang positif dan memberikan pengaruh yang signifikan terhadap Kepuasan Kerja, maka Gaya Kepemimpinan Islami juga dapat mempunyai hubungan yang lebih positif dan memberikan pengaruh yang signifikan terhadap Kepuasan Kerja. Apalagi Gaya Kepemimpinan Islami didukung oleh Lingkungan Kerja Islami. Para peneliti yakin dampaknya akan lebih signifikan. Penelitian ini merupakan penelitian kuantitatif dengan pendekatan eksplanatori. Data yang digunakan dalam penelitian ini adalah data primer yang peneliti sebarkan melalui kuesioner kepada 250 pegawai office boy Bank Muamalat dan Bank Syari'ah Indonesia yang tersebar di seluruh Indonesia. Kuesioner berisi 14 item pertanyaan yang terdiri dari 6 item pertanyaan untuk variabel Gaya Kepemimpinan Partisipatif, 4 item pertanyaan untuk variabel Kepuasan Kerja, dan 4 item pertanyaan untuk variabel Lingkungan Kerja Islami. Kuesioner juga berisi pernyataan sangat setuju, setuju, biasa saja, tidak setuju, dan sangat tidak setuju. Pendistribusian kuisioner memakan waktu selama 1 bulan dengan minggu pertama merupakan pemilihan responden yang memenuhi kriteria telah bekerja minimal 6 bulan/1 semester, minggu kedua penyebaran kuisioner, minggu ketiga tahap pengumpulan kuisioner, dan minggu terakhir tahap memasukkan kuisioner ke dalam excel dan alat analisis. Data yang diperoleh dari alat analisis ini dianalisis menggunakan alat analisis smart PLS 4.0.
Co-Authors Abroza, Ahmad Agustin, Fatma Arief Wisaksono Bambang Ismanto Fachry Abda El Rahman Fahmi, Arsyad Ali Ikhwanudin, Aolia Izza Anshory Jamaaluddin Muhamad Yusuf, SE., M.Si. Nasrulloh, Anas Ramadhan, Aditya Duta Syamhalim, Agianto Toifur, Tubagus