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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Elkom: Jurnal Elektronika dan Komputer Bulletin of Electrical Engineering and Informatics International Journal of Advances in Intelligent Informatics Martabe : Jurnal Pengabdian Kepada Masyarakat Jurnal Surya Masyarakat Indonesian Journal of Electrical Engineering and Computer Science Computer Science and Information Technologies Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Jurnal Surya Masyarakat Journal of Intelligent Computing and Health Informatics (JICHI) Aspirasi : Publikasi Hasil Pengabdian dan Kegiatan Masyarakat Jurnal Komputer dan Teknologi Informasi
Muhammad Munsarif
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Medicine & Pharmacology Public Health Social Sciences Other

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Creativity: Promotion of the Creative Process; Innovative and Collaborative 21st Century Learning Eny Winaryati; Muhammad Munsarif; Mardiana Mardiana; Suwahono Suwahono
Budapest International Research and Critics Institute (BIRCI-Journal): Humanities and Social Sciences Vol 4, No 4 (2021): Budapest International Research and Critics Institute November
Publisher : Budapest International Research and Critics University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33258/birci.v4i4.2971

Abstract

21st century learning requires the world of education to produce graduates who have creativity, who encourage creative and collaborative processes in solving problems. The purpose of this study was to obtain dimensional data and indicators of creativity skills in students, teachers and school principals. This research method is Mixed Method, with Exploratory Sequential Design model. The conclusions of this study are: (1) The number and names of the dimensions remain the same, namely there are 5 (five) with 21 (twenty one) indicators. (2) There is a change in the number and name of the indicator. The number of indicators for each dimension are: (a) Dimensions of creative thinking ability, there are 4 (four) indicators; (b) Dimensions of working creatively with other people have 3 (three) indicators; (c) There are 6 (six) indicators to interpret a failure; (d) Dimensions of implementing idea innovation into innovation for success, there are 5 (five) indicators; (e) Dimensions of thinking outside the habit there are 3 indicators. Suggestion: Research can be followed up by using dimensions and indicators of 21st century learning creativity skills in students and teachers, with various sample characteristics. The results of the assessment can be used to measure the level of existing creativity skills.
PENGEMBANGAN AGROPREUNERSHIP DAN DIGITALISASI DALAM UPAYA BRANDING DESA WISATA WONOLOPO Meike Amelia Hanifah; Shabrina Mirza; Kholifatul Afwah; Salsabila Rahma; Alfi Widianto; Galih Ratna; Alif Hardika; Jian Janata; Siti Muzdalifah; Ahmad Miftakhul; Tirta Ramadhani; Javier Rayhan; Muhammad Munsarif
Martabe : Jurnal Pengabdian Kepada Masyarakat Vol 5, No 4 (2022): Martabe : Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jpm.v5i4.1286-1290

Abstract

Usaha Mikro Kecil dan Menengah (UMKM) dalam perekonomian Indonesia mempunyai peran dan potensi yang besar dalam membangun perekonomian sektoral maupun nasional. Pelaku UMKM di Desa Wonolopo, Kecamatan Mijen, Kota Semarang masih menghadapi permasalahan yang terkait kurangnya pengetahuan masyarakat terhadap Digital Marketing strategi. Keterbatasan ini merupakan permasalahan yang penting bagi UMKM dalam mengembangkan usahanya. Sehingga dalam penelitian ini kami akan memaparkan upaya pengembangan branding yang dilakukan kepada masyarakat Desa Wonolopo. Beberapa kegiatan akan dilaksanakan dalam bentuk kegiatan sosialisasi yang rutin setiap minggu. Dalam pelaksanaanya hanya 20 peserta yang dapat mengikuti, sehubungan masih dalam kondisi Pemberlakuan Pembatasan Kegiatan Masyarakat(PPKM) yang terus menerus berkelanjutan. Hasil dari kegiatan ini, diharapkan para peserta yang mengikuti dapat lebih terbuka secara pengetahuan tentang bagaimana cara mempromosikan potensi Desa Wonolopo dengan mengikuti perkembangan zaman.
Analisis Legalitas Tanah Wakaf Muhammadiyah Jawa Tengah dengan menggunakan Algoritma ID3 Muhammad Munsarif
Elkom : Jurnal Elektronika dan Komputer Vol 13 No 1 (2020): Juli: Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v13i1.134

Abstract

Waqf information system In April 2020 shows the number of waqf land in Indonesia has an area of ​​51,259.84 Ha. More waqf received in the form of land creates a problem of disputes and disputes that lead to legal cases Muhammadiyah is the second-largest Islamic organization that has assets in the form of waqf land that has not been able to resolve existing problems. In this study, an analysis of legal potential and waqf land disputes is used using ID3 Algorithm to classify potential land disputes based on the status of the land deed, owner's name, location of waqf and its use so that it can produce data on the ownership rights of waqf land which has the potential for legal disputes and no legal disputes. research shows that potential legal problems are still present. The ID3 algorithm is able to produce information as a basis for reducing disputes and the loss of waqf land.
Pelatihan Kecerdasan Artifisial (KA) kepada Guru SD di Kabupaten Blora Jawa Tengah untuk Peningkatan Kemampuan di Bidang Digital Muhammad Munsarif; Samsudi Raharjo; Muhammad Sam'an
Jurnal Surya Masyarakat Vol 5, No 1 (2022): November 2022
Publisher : Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsm.5.1.2022.101-105

Abstract

In this era of digitalization, the Government is trying from an early age to introduce programming concepts and Artificial Intelligence, which in the future can be used to support the learning process of elementary school education. This training aims to provide new knowledge about how coding programs are included in the subject matter of elementary school children. The teachers are given lessons on basic things suitable to be applied in class and immediately put into practice their projects. With this method, teachers learn to adapt to the new model, where the material will be taught to students in class. Activities are carried out offline at the Arra Cepu Hotel. Stages of Training through Presentations, Videos, and Quizzes. In this activity, the teachers gain knowledge and skills in coding programs for beginners; pre-test and post-test will be used as a measure to assess it. In the future, teachers will experiment with coding lessons with students. An early introduction to programming and artificial intelligence for elementary school teachers is expected to positively impact students, mainly in their ease of receiving and understanding a lesson.
Peer to peer lending risk analysis based on embedded technique and stacking ensemble learning Muhammad Munsarif; Muhammad Sam’an; Safuan Safuan
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.3927

Abstract

Peer to peer lending is famous for easy and fast loans from complicated traditional lending institutions. Therefore, big data and machine learning are needed for credit risk analysis, especially for potential defaulters. However, data imbalance and high computation have a terrible effect on machine learning prediction performance. This paper proposes a stacking ensemble learning with features selection based on embedded techniques (gradient boosted trees (GBDT), random forest (RF), adaptive boosting (AdaBoost), extra gradient boosting (XGBoost), light gradient boosting machine (LGBM), and decision tree (DT)) to predict the credit risk of individual borrowers on peer to peer (P2P) lending. The stacking ensemble model is created from a stack of meta-learners used in feature selection. The feature selection+ stacking model produces an average of 94.54% accuracy and 69.10 s execution time. RF meta-learner+Stacking ensemble is the best classification model, and the LGBM meta-learner+stacking ensemble is the fastest execution time. Based on experimental results, this paper showed that the credit risk prediction for P2P lending could be improved using the stacking ensemble model in addition to proper feature selection.
Pelatihan Kecerdasan Artifisial (KA) kepada Guru SD di Kabupaten Blora Jawa Tengah untuk Peningkatan Kemampuan di Bidang Digital Muhammad Munsarif; Samsudi Raharjo; Muhammad Sam'an
Jurnal Surya Masyarakat Vol 5, No 1 (2022): November 2022
Publisher : Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsm.5.1.2022.101-105

Abstract

In this era of digitalization, the Government is trying from an early age to introduce programming concepts and Artificial Intelligence, which in the future can be used to support the learning process of elementary school education. This training aims to provide new knowledge about how coding programs are included in the subject matter of elementary school children. The teachers are given lessons on basic things suitable to be applied in class and immediately put into practice their projects. With this method, teachers learn to adapt to the new model, where the material will be taught to students in class. Activities are carried out offline at the Arra Cepu Hotel. Stages of Training through Presentations, Videos, and Quizzes. In this activity, the teachers gain knowledge and skills in coding programs for beginners; pre-test and post-test will be used as a measure to assess it. In the future, teachers will experiment with coding lessons with students. An early introduction to programming and artificial intelligence for elementary school teachers is expected to positively impact students, mainly in their ease of receiving and understanding a lesson.
The evaluation of convolutional neural network and genetic algorithm performance based on the number of hyperparameters for English handwritten recognition Muhammad Munsarif; Edi Noersasongko; Pulung Nurtantio Andono; Moch Arief Soeleman
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 12, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v12.i3.pp1250-1259

Abstract

Convolutional neural network (CNN) has been widely applied to image recognition, especially handwritten English recognition. CNN's performance is good if the hyperparameter values are correct. However, the determination of precise hyperparameters is not a trivial task. This task is made more difficult when combined with a larger number of hyperparameters resulting in a high dimensionality of the search space. Usually, hyperparameter optimization uses a finite number. Previous studies have shown that a large number of hyperparameters can result in optimal CNN performance. However, the studies only apply to text mining datasets. This study offers two novelties. First, it applied 20 hyperparameters and their ranges to handwritten English. Second, this paper conducted seven experiments based on different hyperparameters and the number of hyperparameters. This paper also compares the existing methods, namely random and grid search. The experiment resulted in the proposed model being superior to the existing methods. EX3 is better than other experiments and a larger number of hyperparameters and layer-specific hyperparameter values are unimportant.
Improving convolutional neural network based on hyperparameter optimization using variable length genetic algorithm for english digit handwritten recognition Muhammad Munsarif; Edi Noersasongko; Pulung Nurtantio Andono; Mochammad Arief Soeleman
International Journal of Advances in Intelligent Informatics Vol 9, No 1 (2023): March 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v9i1.881

Abstract

Convolutional Neural Networks (CNNs) perform well compared to other deep learning models in image recognition, especially in handwritten alphabetic numeral datasets. CNN's challenging task is to find an architecture with the right hyperparameters. Usually, this activity is done by trial and error. A genetic algorithm (GA) has been widely used for automatic hyperparameter optimization. However, the original GA with fixed chromosome length allows for suboptimal solution results because CNN has a variable number of hyperparameters depending on the depth of the model. Previous work proposed variable chromosome lengths to overcome the drawbacks of native GA. This paper proposes a variable length GA by adding global hyperparameters, namely optimizer and learning speed, to systematically and automatically tune CNN hyperparameters to improve performance. We optimize seven hyperparameters, such as the learning rate. Optimizer, kernel, filter, activation function, number of layers and pooling. The experimental results show that a population of 25 produces the best fitness value and average fitness. In addition, the comparison results show that the proposed model is superior to the basic model based on accuracy. The experimental results show that the proposed model is about 99.18% higher than the baseline model.
Peningkatan Kompetensi Guru Madrasah Ibtidayah Duren dan Sabilul Huda Bandungan melalui Pelatihan Pembelajaran Berbasis Teknologi Informasi Ahmad Ilham; Akhmad Fathurrohman; Muhammad Sam'an; Safuan Safuan; Muhammad Munsarif; Luqman Assaffat; Asdani Kindarto; Arfido Ramadhani; Juyus Muhammad Adinullhaq; Febrianto Febrianto; Irvan Nurmantoro; Yevi Alviatul Ardhani; Nova Ariyanto
Jurnal Surya Masyarakat Vol 5, No 2 (2023): Mei 2023
Publisher : Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsm.5.2.2023.264-269

Abstract

Madrasah Ibtidaiyah (MI) Duren Village and Sabilul Huda Jimbaran Bandungan District Semarang Regency want to produce quality graduates. However, the competence of teachers is still conventional learning aids so the learning process is not optimal. To answer this problem, the Department of Informatics, Faculty of Engineering at Universitas Muhammadiyah Semarang, Indonesia proposed information technology-based learning training activities for madrasah teachers. The purpose program is to strengthen human resources for teachers in MI Desa Duren and Sabilul Huda Jimbaran. The proposed program is divided into three learning schemes, (1) interactive presentation media, (2) online classroom learning, and (3) online learning evaluation. The results of this program are that the participants proved to be able to produce effective, elaborative, and interactive teaching materials based on information technology so that students are not bored and enthusiastic about following lessons in the classroom. It can be cancluded the program with the theme "Strengthening Teacher Competencies Through Information Technology-Based Learning Training" can overcome problems in Madrasah Ibtidaiyah (MI) Duren Village and Sabilul Huda Jimbaran Bandungan District Semarang Regency.
Convolutional neural network hyperparameters for face emotion recognition using genetic algorithm Muhammad Sam'an; Safuan Safuan; Muhammad Munsarif
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp442-449

Abstract

The development of artificial intelligence in facial emotion recognition (FER) is rapidly growing and has been widely applied in various fields. Deep learning (DL) techniques with evolutionary algorithms have become the preferred choice for solving various security, health, gaming, and other related problems. This research proposes the use of a genetic algorithm (GA) as the main method to optimize hyperparameters in the convolutional neural network (CNN) model for FER. The required computation time is approximately 37 hours 57 minutes 55 seconds, with generation 3 taking the longest time at around 16 hours 45 minutes 4 seconds. However, generation 3 achieved an accuracy of 76.11%, which is the highest compared to other generations. The results indicate that the more generations are involved, the higher the achievable accuracy. Furthermore, the proposed CNN-GA model in this study outperforms previous models that have been examined. Thus, this study makes a significant contribution to improving the understanding of using GAs to optimize the performance of CNN models for FER.
Co-Authors A. Awoseyi, Ayomikun Abdollahi, Jafar Adinullhaq, Juyus Muhammad Agatra, Denaya Ferrari Noval Ahmad Ilham Ahmad Miftakhul Akhmad Fathurrohman Akhmad Fathurrohman Alfi Widianto Alif Hardika Ardhani, Yevi Alviatul Arfido Ramadhani ARIF KURNIAWAN Ariyanto, Nova Asdani Kindarto Caesarizky, Ovien Yoga Cornella, Barisma Ami Edi Noersasongko Edi Noersasongko Eny Winaryati Fahrezi, Andrian Febrianto Febrianto Febrianto Febrianto, Febrianto Galih Ratna Hakim, Muhammad Ilham Ilham, Ahmad Irvan Nurmantoro Javier Rayhan Jian Janata Juyus Muhammad Adinullhaq Kholifatul Afwah Kindarto, Asdani Luqman Assaffat Luqman Assaffat Mardiana Mardiana Meike Amelia Hanifah Moch Arief Soeleman Mochammad Arief Soeleman Muhammad Sam'an Muhammad Saman Muhammad Sam’an Muza'in, Muhammad Nova Ariyanto Nurmantoro, Irvan Pulung Nurtantio Andono Purbandanu, Muhammad Wigig Ramadhani, Arfido Safuan Safuan Safuan Safuan Safuan Safuan Safuan Safuan Salsabila Rahma Sam'an, Muhammad Samsudi Raharjo SAMSUDI RAHARJO Sefrina Ainun Shabrina Mirza Siti Muzdalifah Suwahono Suwahono Tirta Ramadhani Wibowo, Bhanu Lintang Yanuarta, Rizky Yevi Alviatul Ardhani