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All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING JCES (Journal of Character Education Society) JURTEKSI Bakti Sekawan : Jurnal Pengabdian Masyarakat
Qulub, Mudawil
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Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Health Professions Social Sciences Other

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Improvement of Spelling Correction Accuracy in Indonesian Language through the Application of Hamming Distance Method Qulub, Mudawil; Hammad, Rifqi; Irfan, Pahrul; Yuliana, Yuliana
Journal of Applied Informatics and Computing Vol. 7 No. 2 (2023): December 2023
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v7i2.5926

Abstract

Spelling correction is a critical feature in software to reduce typing errors, commonly found in document processing software and smartphone keyboards. This research aims to evaluate the accuracy of the Hamming Distance method in correcting words in the Indonesian language, both standard and non-standard forms. The research data is derived from a previous study and comprises 60 standard and non-standard Indonesian words. Typos are generated by considering the layout of letters on the QWERTY keyboard. Typing error data is divided into two groups, namely words with 1 and 2 character differences. The first test is conducted on standard words, achieving an accuracy rate of 98.33% for 1 and 2 character differences. Subsequent testing on non-standard words shows an accuracy rate of 100% for 1 character difference and 96.67% for 2 character differences. The results of this research highlight the potential of the Hamming Distance method in improving the quality of spelling correction in the Indonesian language.
OPTIMALISASI USAHA EKONOMI KREATIF PADA ERA REVOLUI INDUSTRI 4.0 MELALUI IMPLEMENTASI TEKNOLOGI DIGITAL DI SMK NEGERI 5 MATARAM Zahrah, Zahrah; Widyati, Baiq Dinna; Qulub, Mudawil; Budiarta, Meiza Ariya; Alfia, Kharunia
JCES (Journal of Character Education Society) Vol 8, No 1 (2025): Januari
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jces.v8i1.28784

Abstract

Abstrak: SMKN 5 Mataram, merupakan salah satu sekolah kejuruan di Kota Mataram yang memproduksi produk dengan unsur nilai budaya yang berpotensi untuk mencapai pasar nasional dan mancanegara. Namun, SMKN 5 Mataram belum konsisten dalam menawarkan produknya secara lingkup nasional dan mancanegar disebabkan karena keterbatasan mereka dalam mempromosikan dan mengenalkan produk yang dihasilkan dapat diakses dari luar daerah bahkan internasional. Ditambah kurangnya kemampuan sumber daya manusianya dalam membuat dan mengelola website dan sosial media atau marketplace, minimnya kemampuan pengambilan foto/video untuk mengisi website galeri usaha yang dihasilkan. Untuk itu diperlukannya upaya untuk meningkatkan kemampuan siswa dan juga sekolah.  Salah satunya yakni melalui implementasi teknologi digital pada usaha ekonomi kretif. Tujuannya agar siswa atau sekolah dapat memaksimalkan pemamfaatan teknologi terhadap pemasaran dan e-niaga sebagai media untuk memperluas jangkauan pasarnya. Hal ini sejalan dengan keinginan Menteri Pendidikan dan Kebudayaan Nadiem Makarim untuk mengimplementasikan teknologi dan digital dalam kurikulum 5.0. Dalam pelaksanaannya pelaksanaan kegiatan ini akan dibagi menjadi tiga tahap dan dilaksanakan dalam waktu tiga pertemuan dengan pendekatan persuasif dan interaktif (timbal balik). Hasil kegiatan pelatihan ini mampu memberikan wawasan lebih banyak mengenai bagaimana melakukan ekspor barang, peningkatan kualitas konten dan pemanfaatan teknologi digital berupa pengelolaan media sosial dan website khususnya.Abstract:  SMKN 5 Mataram is one of the vocational schools in Mataram City that produce cultural products with the potential to reach national and international markets. However, the school has not been consistent in offering its products nationally and internationally due to its limitations in promoting and introducing products that can be accessed from outside the region and even internationally. The institution's capacity to create and manage websites, social media, and marketplaces is deficient, as is its capability to produce visual content, such as photographs and videos, to populate the business gallery website.To address these limitations, there is an imperative for enhancing the competencies of students and schools.A proposed solution involves the integration of digital technology into creative economic initiatives. The objective is to empower students and schools to leverage technology for marketing and e-commerce purposes, thereby expanding their market reach. This objective is consistent with the Minister of Education and Culture, Nadiem Makarim's vision for the integration of technology and digital elements into the 5.0 curriculum.The implementation of this activity will be meticulously structured into three phases, spanning three meetings, employing a persuasive and interactive approach. The training activity is expected to yield several key outcomes, including a deeper understanding of strategies for enhancing the quality of exported goods and leveraging digital technologies for effective management of social media and websites.
DETECTION OF CHILDREN'S NUTRITIONAL STATUS USING MACHINE LEARNING WITH LOGISTIC REGRESSION ALGORITHM Yuliana, Yuliana; Paradise, Paradise; Qulub, Mudawil
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 10 No. 2 (2024): Maret 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i2.2973

Abstract

Abstract: Children's nutritional issues are an important concern for parents to pay attention to growth and development, especially health and well-being. According to the results of the Ministry of Health's Indonesian Nutrition Status Survey (SSGI), there are 4 nutritional problems for children in Indonesia, namely stunting, wasting, underweight and everweight. In this research, how to predict signs of symptoms of a decline in a child's nutritional status using a machine learning algorithm, a prediction model was designed using logistic regression in Python IDE to predict whether a child is indicated by a decline in nutrition or not. Dataset from Bengkayang Community Health Center data consisting of 657 pediatric patient data. The dataset is divided into 7 features (independent variables) and 1 predictor (dependent variable). Test results show perfect performance with precision, recall, F1-score, accuracy values of 100%. Then the visualization results on the ROC (Receiver Operating Characteristic) curve to depict the TP (True Positive) value on the Y axis against the FP (false Positive) value on the become overfit. It is recommended that in preparing the training dataset, measure the training data and reduce the features, after carrying out feature selection to increase the accuracy of the model.            Keywords: child nutritional status; growth and development logistic regression; machine learning Abstract: Masalah Gizi anak menjadi perhatian penting bagi orangtua untuk memperhatikan tumbuh kembang, terutama kesehatan dan kejahteraan. Menurut hasil survei status Gizi Indonesia (SSGI) Kemenkes memperlihatkan 4 permasalahan gizi anak di Indonesia yaitu stunting, wasting, underweight, dan everweight. Dalam penelitian ini, bagaimana memprediksi tanda gejala penurunan status gizi anak menggunakan  algoritma  machine  learning dirancang model prediksi menggunakan logistic regression pada Python IDE dengan  memprediksi anak  terindikasi  penurunan gizi  atau tidak. Dataset dari data Puskesmas Bengkayang  yang terdiri 657 data pasien anak. Dataset dibagi menjadi 7 feature (variabel independen) dan 1 predictor (variabel dependen). Hasil Pengujian memperlihatkan kinerja yang sempurna dengan nilai presisi, recall,  F1-score, akurasi, sebesar 100%. Kemudian hasil Visualisasi pada kurva ROC (Receiver Operating Characteristic) untuk menggambarkan nilai TP (True Positif) di sumbu Y terhadap nilai FP (false Positif) di sumbu X juga menunjukkan nilai yang sangat tinggi dan sudah mendekati angka 1 ini pertanda bahwa model ini menjadi overfit. Sebaiknya dalam persiapan training dataset diukur dengan data training dan mengurangi feature, setelah melakukan feature Selection untuk meningkatkan akurasi model. Keywords: logistic regression; machine learning; status gizi anak; tumbuh kembang
Peningkatan Kompetensi Guru SMAN 7 Mataram dalam Melaksanakan Pembelajaran dengan Pendekatan Deep Learning Azwar, Muhamad; Hariyadi, I Putu; Azhar, Raisul; Priyanto, Dadang; Adil, Ahmat; Santoso, Heroe; Syahrir, Moch.; Augustin, Kartarina; Zulkipli, Zulkipli; Darma, I Made Yadi; Asroni, Ondi; Qulub, Mudawil; Azhar, Lalu Zazuli; Widyawati, Lilik; Anas, Andi Sofyan
Bakti Sekawan : Jurnal Pengabdian Masyarakat Vol. 5 No. 2 (2025): Desember
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/bakwan.v5i2.852

Abstract

The capability of educators to respond to the dynamics of 21st-century education is a primary determinant in establishing a high-quality learning environment. Based on initial findings at SMAN 7 Mataram, a disparity was identified between the urgency of applying varied learning models and the reality in the field, which still relies heavily on conventional, teacher-centered approaches. This situation implies minimal active student participation and suboptimal stimulation of critical thinking skills or Higher Order Thinking Skills (HOTS). This community service program was initiated to escalate teacher capacity at SMAN 7 Mataram, specifically in designing Deep Learning-based schemes. The implementation approach adopted the Participatory Action Research (PAR) method, involving the full attention of 70 teachers through a series of phases, ranging from preparation and implementation to evaluation and mentoring. Key interventions included training on compiling Deep Learning-oriented Lesson Plans and teaching simulations. Program effectiveness was measured through questionnaires, lesson plan document reviews, and observations. Evaluation data showed a substantial positive impact, marked by an increase in conceptual understanding of Deep Learning indicators (40%), 6C principles (40%), the teacher's function as a facilitator (32%), and the application of authentic assessment (40%). In terms of implementation, the quality of lesson plans accommodating student-centered activities surged significantly from 30% in the pre-activity phase to 100% after the activity. It can be concluded that this program effectively boosts teachers' pedagogical competence comprehensively and encourages the transformation of teaching practices in the classroom to become more dynamic.
Co-Authors Ahmat Adil Alfia, Kharunia Andi Sofyan Anas Augustin, Kartarina Azhar, Lalu Zazuli Azhar, Raisul Budiarta, Meiza Ariya Darma, I Made Yadi Hammad, Rifqi Hariyadi, I Putu Lilik Widyawati Muhamad Azwar, Muhamad Ondi Asroni Pahrul Irfan Paradise, Paradise Santoso, Heroe Syahrir, Moch. Widyati, Baiq Dinna Yuliana Yuliana Zahrah, Zahrah Zulkipli Zulkipli