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All Journal Teknologi dan Kejuruan: Jurnal teknologi, Kejuruan dan Pengajarannya Jurnal Pendidikan Vokasi APTEKINDO JIPTEK : Jurnal Ilmiah Pendidikan Teknik dan Kejuruan ELECTRANS INVOTEC JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) Jurnal ULTIMA Computing JURNAL PENDIDIKAN TAMBUSAI Jurnal Teknologi Terpadu JURNAL BUDIDAYA PERTANIAN Journal of Vocational Education Studies (JOVES) TECHNO-SOCIO EKONOMIKA REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat International Journal of Electronics and Communications Systems Eduvest - Journal of Universal Studies IJIS Edu : Indonesian Journal of Integrated Science Education SNTE Pedagogia : Jurnal Ilmiah Pendidikan
Iwan Kustiawan
Universitas Pendidikan Indonesia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Neuroscience Social Sciences Other

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One-Phase Smart Switch using OpenCV Hand Gesture Recognition Fauzan, Mochamad Rizal; Khairi, Saiqa Fatur; Kaniarudi, Neneng Puspita; Ath Thahirah Al Azhima, Silmi; Arief Hakim, Nurul Fahmi; Kustiawan, Iwan; Al Qibtya, Mariya; Elvyanti, Siscka
Ultima Computing : Jurnal Sistem Komputer Vol 16 No 1 (2024): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v16i1.3633

Abstract

The need for simplicity in various activities encourages further technological development. One of them is a system to turn lights on and off with just a hand gesture. This hand gesture-based One-phase smart switch uses OpenCV, Arduino Nano, relays, and webcam cameras to recognize hand gestures. Static finger movements are used as buttons to turn on the lights. The results show that the algorithm used has high reliability with a precision score of 0.90, sensitivity of 0.90, accuracy of 0.96, and F1-score of 0.90. The accuracy of the system is affected by light intensity, distance, and hand tilt angle. At a light intensity of 70 LUX, the accuracy reaches 100%, while at 40 LUX the accuracy ranges from 98-99%. A distance of 30-60 cm gave the best accuracy of 100%, but decreased at longer distances. A hand tilt of 0° gives 100% accuracy, while at an angle of 60° the accuracy drops significantly, especially for the fifth finger with 64% accuracy. The average response time of the light to finger movement is 0.133 seconds. This device can recognize a variety of finger patterns well, thus meeting the desired needs.
Kewenangan Pemerintah Kota Banjar dalam Pelaksanaan Pasal 44 Huruf A Undang-Undang Nomor 22 Tahun 2009 tentang Lalu Lintas dan Angkutan Jalan Asmara, Anjar; Kustiawan, Iwan; Lubis, Fahmi Zulkifli
Jurnal Pendidikan Tambusai Vol. 5 No. 3 (2021): 2021
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jptam.v5i3.3213

Abstract

Permasalahan dalam penelitian ini yaitu mengenai sejauhmanakah kewenangan Pemerintah Kota Banjar dalam pelaksanaan Pasal 44 Huruf a Undang-undang Nomor 22 Tahun 2009 tentang Lalu Lintas dan Angkutan Jalan; kendala-kendala dan upaya-upayanya. Metode yang digunakan dalam penelitian ini adalah metode deskriptif analitis, dengan metode pendekatan yuridis normatif. Berdasarkan hasil penelitian maka dapat disimpulkan bahwa pelaksanaan Pasal 44 Huruf A Undang-Undang Nomor 22 Tahun 2009 Tentang Lalu Lintas Dan Angkutan Jalan belum optimal. Hal ini dapat dilihat dengan masih banyaknya pengguna kendaraan yang memarkir kendaraannya di luar area parkir yang telah disediakan karena tempat parkir penuh dan sering menimbulkan kemacetan. Kendala-kendalanya adlah terbatasnya anggaran yang disediakan oleh Pemerintah Kota Banjar; kurangnya kesadaran dan responsif masyarakat dalam penetapan dan pembangunan fasilitas parkir; terbatasnya Sumber Daya Manusia yang berkualitas dalam penetapan dan pembangunan fasilitas parkir; pertumbuhan penduduk dan jumlah kendaraan bermotor yang semakin meningkat; dan kecenderungan pertumbuhan kawasan bisnis atau komersil yang terus bekembang semakin banyak. Upaya-upayanya adalah yang dilakukan dalam kewenangan Pemerintah Kota Banjar Dalam meningkatkan peran serta pemerintah daerah melalui bimbingan teknis dan bantuan teknis yang diperlukan untuk pelaksanaan penetapan lokasi dan pembangunan fasilitas parkir; pemerintah daerah merevisi Perda Nomor 6 Tahun 2004 Tentang Rencana Tata Ruang Wilayah Kota Banjar yang sudah tidak sesuai dengan keadaan sekarang khususnya untuk lokasi parkir dikawasan komersil; dan meningkatkan koordinasi, pembinaan dan pengawasan oleh dinas-dinas terkait dalam hal penetapan lokasi dan pembangunan fasilitas parkir.
Hybrid Machine Learning Model untuk memprediksi Penyakit Jantung dengan Metode Logistic Regression dan Random Forest Al Azhima, Silmi Ath Thahirah; Darmawan, Dwicky; Arief Hakim, Nurul Fahmi; Kustiawan, Iwan; Al Qibtiya, Mariya; Syafei, Nendi Suhendi
Jurnal Teknologi Terpadu Vol 8 No 1: Juli, 2022
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v8i1.539

Abstract

The heart is the main organ that must work properly and regularly. If there is interference, it will be fatal, namely the onset of a heart attack. Heart attack is included in the 10 diseases with a high risk of death. This is caused by stress factors, blood pressure, excessive work, blood sugar, and others. The purpose of this study is to predict heart disease using Machine Learning (ML) algorithms as an early preventive measure on desktop-based information systems. With Machine Learning models, the hybrid model can increase the accuracy value of an ML method that is added to other ML methods. The accuracy value obtained from the Hybrid Model Machine Learning using the Random Forest and Logistic Regression methods is 84.48%, which is an increase of 1.32%.  
A Bibliometric Analysis of the Employability Skills Research Trends in Vocational Education Maharbid, Allan Anugraha; Kustiawan, Iwan
Teknologi dan Kejuruan: Jurnal Teknologi, Kejuruan, dan Pengajarannya Vol 45, No 2: September 2022
Publisher : Fakultas Teknik Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um031v45i22022p114-122

Abstract

Employability skills are the skills needed to acquire, retain, and do a good job. Employability skills are essential in helping prepare students to increase competitiveness and work productivity. The world of work wants graduates to be competitive and technically competent with skills relevant to technological developments. This study aims to analyze research trends related to employability skills in vocational education. We use bibliometric analysis procedures on 1123 published articles in the Scopus database. The results of this study reveal citation, co-authorship, co-citation, and keyword analyses producing a pattern of research maps in vocational education. The findings identify publication trends, widely cited articles, contributing countries, productive journals, and obtain information for future research on employability skills
Exploring disruptive power: Acceptance of digital technologies in mechanical engineering education among Ghanaian technical university teachers Tettehfio, Emmanuel Obobi; Setiawan, Agus; Kustiawan, Iwan; Andoh, Prince Yaw
Jurnal Pendidikan Vokasi Vol. 13 No. 3 (2023): November
Publisher : ADGVI & Graduate School of Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jpv.v13i3.63606

Abstract

The paper examines the effect of perceived ease of use, user acceptance, and quality assurance practices on the acceptance of digital technology among mechanical engineering teachers in Technical Universities in Ghana. The paper adopts a quantitative research approach using a descriptive survey design. A sample of 167 mechanical engineering teachers was selected using stratified and simple random sampling techniques. Data was collected through a structured questionnaire that included demographic information and variables related to digital technology acceptance. The collected data were analyzed using structural equation modeling with the aid of SmartPLS 4 software. The study's findings reveal that perceived ease of use, user acceptance, and quality assurance practices significantly and positively influence mechanical engineering teachers' acceptance of digital technology. Specifically, the acceptance of quality assurance practices was found to have the strongest impact on technology acceptance among the three factors examined. The study focused on mechanical engineering teachers in Ghana's Technical universities, limiting the generalizability of the findings to other educational contexts. Future research should consider expanding the sample size and including participants from different educational institutions and other disciplines. This study contributes to the existing literature on digital technology acceptance by examining the specific context of mechanical engineering education in Ghana. The findings also contribute to the broader discourse on digital skills development and closing the digital divide in educational settings.
Digital Maturity in Vocational Secondary Schools (SMK) Yarmanto, Edhy Sri; Setiawan, Agus; Kustiawan, Iwan
Journal of Vocational Education Studies Vol. 8 No. 2 (2025): Vol 8 No 2
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/joves.v8i2.12243

Abstract

Digital transformation has taken place in various sectors of life, and has also penetrated into Vocational Secondary Schools (SMK). Research on digital maturity in vocational schools is still rare. The purpose of this study is to develop a digital maturity model that includes the dimensions and the level of digital maturity, digital maturity measurement instruments, and to measure digital maturity in vocational schools. The instrument developed has met the validity and reliability test and can be used for quantitative research on digital maturity measurement. The dimensions of digital maturity include: management and organization, people and culture, products and services, technology, and organizational operations. Meanwhile, the maturity level consists of 5 levels: not ready, initial readiness, intermediate readiness, mature readiness, and already implemented. The measurement results showed that the vocational school that was the subject of the study was in mature readiness. This study concludes that digital transformation in vocational schools is a necessity. The resulting assessment models and instruments can be used to measure digital maturity in vocational schools. This study was conducted at a vocational school, which opened up space for future study. The form of research can deepen the dimension of digital maturity, or research for high schools, both public or private high schools.
Digital maturity models and instruments for vocational high schools in Indonesia Setiawan, Agus; Yarmanto, Edhy Sri; Kustiawan, Iwan
Jurnal Pendidikan Vokasi Vol. 14 No. 3 (2024): November
Publisher : ADGVI & Graduate School of Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jpv.v14i3.72957

Abstract

Research on digital maturity models in education, particularly vocational education, remains limited, despite the urgent need for schools to adapt to digital transformation. Vocational High Schools (SMK) in Indonesia are mandated to prepare graduates as skilled workers ready to meet industry demands, and therefore require a clear framework to assess their digital readiness. This study aims to develop a model and an instrument to measure the digital maturity level of vocational schools. The research employed a literature review of existing digital maturity models from both education and industry, followed by synthesis and adaptation to the vocational school context. The resulting model consists of five dimensions: strategy and organization, people and culture, products and services, technology and infrastructure, and organizational operations. It defines five levels of maturity: not ready, initial readiness, medium readiness, mature readiness, and fully applied. An instrument with 29 indicators was developed and tested through a pilot study in one vocational school, with results showing strong validity and reliability (Cronbach’s Alpha = 0.935). The findings highlight the inclusion of the products and services dimension as a novel contribution compared to existing educational models. This model and instrument provide practical benefits for vocational school leaders to assess current digital maturity, identify areas for improvement, and plan targeted digital transformation strategies. The study also opens avenues for future research through larger-scale validation and integration of field observations.
Profile of the Need for STEM Teaching Materials in Science Learning in Vocational Schools Susilawati, Aay; Rochintaniawati, Diana; Hasanah, Lilik; Kustiawan, Iwan; Rustaman, Nuryani; Kaniawati, Ida
IJIS Edu : Indonesian Journal of Integrated Science Education Vol 5, No 2 (2023): July 2023
Publisher : UIN Fatmawati Sukarno Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29300/ijisedu.v5i2.3297

Abstract

Science education in vocational schools has undergone several changes in subject characteristics. Scienceteachers need to understand these characteristics to facilitate the delivery and implementation of learning inthe classroom. Therefore, the purpose of this article is to describe the requirements profile of needs forSTEM teaching materials in science learning at vocational schools. The research methods used aredescriptive and qualitative through field observations (field studies) derived from professional research inthe form of curriculum documents, lesson plans, learning videos, and analysis of six science textbooks invocational school. The results of a curriculum analysis from document, videos and textbooks on theavailability of project-based STEM components in learning equipment plans and existing materials are stillinadequate to support the life skills of 21st century professional students, and the following curriculumrequirements are: Not yet supported. So, in future research need integration, project-based, and underlyingskills according to competency skills in vocational school.
Pengembangan Sistem Prediksi Waktu Penyiraman Optimal pada Perkebunan: Pendekatan Machine Learning untuk Peningkatan Produktivitas Pertanian Anggarda, Mohammad F; Kustiawan, Iwan; Nurjanah, Deasy R; Hakim, Nurul F A
JURNAL BUDIDAYA PERTANIAN Vol 19 No 2 (2023): Jurnal Budidaya Pertanian
Publisher : Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/jbdp.2023.19.2.124

Abstract

Modern agriculture relies heavily on technology, especially in irrigation management and crop watering. Several previous studies have applied field data-based predictive techniques to improve crop yields. This research aims to develop a prediction system for optimal watering time in plantations and agriculture using a machine learning approach. The rigorous methodology includes data capture, pre-processing, model evaluation and testing, validation, and visualization. High accuracy demonstrates the system's reliability in determining optimal watering needs to improve resource efficiency and crop yields in agriculture. The data obtained from the automatic weather station (AWS) via thingsboard is processed sequentially, starting from data retrieval in json format using postman to transformation into csv files with proper timestamp adjustment. The pre-processing stage includes data cleaning, variable selection, data integration, and generating a clean dataset. In the evaluation stage, the dataset is divided into training data and test data, with the application and comparison of logistic regression, random forest and decision tree models applied as classifiers. Furthermore, the validation and results stage includes prediction, performance testing using the confusion matrix, and visualization of prediction results in the form of text and icons that aim to increase interpetability for users through Google Collaboratory. The results of this research provide an overview of the optimal watering time based on the dataset from the automatic weather station. Further analysis shows that the implementation of machine learning models significantly improves the prediction accuracy, proving the effectiveness of the system in providing more precise watering time recommendations to increase agricultural productivity. The main objective is to develop a machine learning-based watering time prediction system using data from the automatic weather station and evaluate various classifier algorithms to select the best model.
One-Phase Smart Switch using OpenCV Hand Gesture Recognition Fauzan, Mochamad Rizal; Khairi, Saiqa Fatur; Kaniarudi, Neneng Puspita; Ath Thahirah Al Azhima, Silmi; Arief Hakim, Nurul Fahmi; Kustiawan, Iwan; Al Qibtya, Mariya; Elvyanti, Siscka
ULTIMA Computing Vol 16 No 1 (2024): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v16i1.3633

Abstract

The need for simplicity in various activities encourages further technological development. One of them is a system to turn lights on and off with just a hand gesture. This hand gesture-based One-phase smart switch uses OpenCV, Arduino Nano, relays, and webcam cameras to recognize hand gestures. Static finger movements are used as buttons to turn on the lights. The results show that the algorithm used has high reliability with a precision score of 0.90, sensitivity of 0.90, accuracy of 0.96, and F1-score of 0.90. The accuracy of the system is affected by light intensity, distance, and hand tilt angle. At a light intensity of 70 LUX, the accuracy reaches 100%, while at 40 LUX the accuracy ranges from 98-99%. A distance of 30-60 cm gave the best accuracy of 100%, but decreased at longer distances. A hand tilt of 0° gives 100% accuracy, while at an angle of 60° the accuracy drops significantly, especially for the fifth finger with 64% accuracy. The average response time of the light to finger movement is 0.133 seconds. This device can recognize a variety of finger patterns well, thus meeting the desired needs.
Co-Authors Aa Juhanda Aay Susilawati Ade Andri Hendriadi Ade Gafar Abdullah, Ade Gafar Agus Setiawan Al Azhima, Silmi Ath Thahirah Al Qibtiya, Mariya Al Qibtya, Mariya Alam, Sahirul Andoh, Prince Yaw Anggarda, Mohammad F Anjar Asmara Arjuni Budi Pantjawati Ath Thahirah Al Azhima, Silmi Bandiyah Sri Aprillia Budi, Agus Heri Setya Darmawan, Dwicky Deni Irawan Diana Rochintaniawati Didin Wahyudin Didin Wahyudin, Didin Dwicky Darmawan Eki Nugraha Emmanuel Obobi Tetehfio Erik Haritman Fauzan, Mochamad Rizal Hakim, Nurul F A Hasbullah Hasbullah Ida Kaniawati Imanudin, Rizkia Fahmi Noviansyah Isma Widiaty Johar Maknun, Johar Kaniarudi, Neneng Puspita Khairi, Saiqa Fatur Khan, Muhammad Lookman Hossain Kurnia Santi Lilik Hasanah Lubis, Fahmi Zulkifli Lukman Hakim, Dadang Maharbid, Allan Anugraha Maman Somantri Mandasari, R Deasy Mariya Al Qibtiya Mohamad Iqbal Rosyadi Mohamad Ramdhani Muhammad Adli Rizqulloh Muhammad Randi Alwi Nendi Suhendi Syafei Neris Peri Ardiansyah Noor, Tubagus Firman Iskandar Nurjanah, Deasy R Nurul Fahmi Arief Hakim Nuryani Rustaman Quinera Joshua R. Ajeng Herty P Resa Pramudita Roer Eka Pawinanto, Roer Eka Ronald Adrian, Ronald Salsabilla Dwita Putri Shaymanov, Farxod Xushbakovich Silmi Ath Thahirah Al Azhima Siscka Elvyanti Siscka Elvyanti Siscka Elvyanti, Siscka Susilawati, Aay Tettehfio, Emmanuel Obobi Wasimudin Surya Saputra Yadi Mulyadi Yarmanto, Edhy Sri Yoyo Somantri