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All Journal International Journal of Electrical and Computer Engineering Jurnal Informatika JIK Jurnal Ilmu Komputer Jurnal Sistem Komputer BERKALA SAINSTEK Prosiding SNATIKA Vol 01 (2011) Journal of Agromedicine and Medical Sciences INFORMAL: Informatics Journal Jurnal Manajemen Kesehatan Indonesia UNEJ e-Proceeding Proceeding of the Electrical Engineering Computer Science and Informatics Management Analysis Journal JOIV : International Journal on Informatics Visualization International Journal of Artificial Intelligence Research Health Notions Wikrama Parahita : Jurnal Pengabdian Masyarakat Indonesian Journal of Artificial Intelligence and Data Mining CARADDE: Jurnal Pengabdian Kepada Masyarakat SPIRIT Indonesian Journal of Global Health research Journal of Indonesia Road Safety Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences International Journal Of Computer, Network Security and Information System (IJCONSIST) Jurnal Teknik Sumber Daya Air Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Pengabdian Pada Masyarakat JGGAG (Journal of Games, Game Art, and Gamification)
Saiful Bukhori
Lecturer, Faculty Of Computer Science, Universitas Jember
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Social Media Sentiment Analysis to Measure Community Response in the Millennial Road Safety Festival Program Using TF-IDF and Support Vector Machine Saiful Bukhori; Sonya Sulistyono; Antonius Cahya Prihandoko; Januar Adi Putra; Windi Eka Yulia Retnani; Umroh Makhmudah; Muhammad Noor Dwi Eldianto
Journal of Indonesia Road Safety Vol 3 No 2 (2020): Journal of Indonesia Road Safety
Publisher : Traffic Accident Research Center, Indonesia Traffic Police Corps and University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/korlantas-jirs.v3i2.16768

Abstract

This Sentiment Analysis is a combination of data mining and text mining. Sentiment Analysis itself is used to process various opinions that the public or experts have given through a variety of existing media. The argument is given to a product, service, or agency. Sentiment Analysis has three types of opinions: negative opinions, positive opinions, and neutral opinions. Based on the test results, the resulting model achieves the highest accuracy of 83.33% when using 80:20 scenario data, while the lowest accuracy of 80.00% is achieved when using the 60:40 scenario data. The higher the precision that will be obtained, whereas using less training data will be slightly unstable. ABSTRAK Sentiment Analysis merupakan perpaduan dari data mining dan teks mining, dimana Sentiment Analysis sendiri digunakan untuk mengolah berbagai macam opini yang telah diberikan oleh masyarakat atau para pakar melalui berbagai media yang ada, opini tersebut diberikan untuk sebuah produk, jasa maupun sebuah instansi. Pada Sentiment Analysis terdapat 3 jenis opini, yaitu opini negatif, opini positif dan opini netral. Berdasarkan hasil pengujian, model yang dihasilkan mencapai akurasi tertinggi yaitu 83,33% saat menggunakan data skenario 80:20, sedangkan akurasi terendah 80,00% dicapai ketika menggunakan skenario data 60:40 Skenario data dapat memengaruhi tingkat akurasi semakin banyak jumlah data pelatihan yang diberikan, semakin tinggi akurasi yang akan diperoleh, sedangkan jika menggunakan lebih sedikit data pelatihan, hasilnya akan sedikit tidak stabil.
Pengenalan Ekspresi Emosi pada Citra Wajah Menggunakan Extreme Learning Machine Studi Kasus Dataset Publik JAFFE: Emotional Expressions Recognition in Facial Images Using Extreme Machine Learning Case Study of JAFFE Public Dataset Shasha Nur Faadhilah; Saiful Bukhori; Januar Adi Putra
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 2 No. 2 (2022): MALCOM October 2022
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (640.308 KB) | DOI: 10.57152/malcom.v2i2.363

Abstract

Era teknologi informasi semakin berkembang dengan cepat dan kompleks, kehandalan sistem mengolah data dengan baik akan menghasilkan informasi yang baik pula. Face Recognition merupakan topik yang ramai dibicarakan dan banyak diteliti, penemuan-penemuan dibidang ini pun banyak menghasilkan temuan yang digunakan sebagai acuan untuk Face Recognition, salah satunya Facial Expression. Sistem pengenalan emosi merupakan salah satu contoh pemrosesan citra yang termasuk pada ranah computer vision. Dalam dunia computer vision, penelitian mengenai ekspresi wajah telah dilakukan sebelumnya oleh Chinese Academy of Sciences Micro-Expression (CASME). Pada kasus micro-expressions wajah, penelitian ini fokus pada satu area yaitu lower face yang dijadikan acuan untuk fitur wajah yang digunakan. Untuk lower face area yang dijadikan ROI khusus diwilayah mulut (lower face). Untuk melakukan ROI pada area tersebut, metode yang digunakan algoritma Viola-Jones pada cascade object detector dengan menentukan wilayah khusus yang dicrop atau batasan area berdasarkan fitur lower face yang bisa disebut sebagai deteksi area mulut (mouth detection). Kemudian dilakukan proses ekstraksi menggunakan Local Binary Pattern. Setelah itu hasil dari proses ekstraksi dijadikan acuan untuk menentukan deteksi ekspresi emosi. Nantinya deteksinya akan memanfaatkan ELM sebagai metode klasifikasi yang dijadikan kelas-kelas ekspresi emosi.
Virtual Assistant for Thesis Technical Guide Using Artificial Neural Network Mohammad Ovi Sanjaya; Saiful Bukhori; Muhammad `Ariful Furqon
Indonesian Journal of Artificial Intelligence and Data Mining Vol 6, No 2 (2023): September 2023
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v6i2.23473

Abstract

This study focuses on finding best practice for Artificial Neural Network (ANN) implementation in the information system for student’s thesis technical instructions. The machine learning model applied sequential model, it means ANN only use 1 input layer, a hidden/dense layer and 1 output layer. The Stochastic Gradient Decent (SGD) method was applied into data training process. The results of this study are chatbot applications, and model testing using the confusion matrix. The result of model evaluation are 99,49% accuracy and 91% in F-1 score.
Analysis of the Effect of the Application of Total Quality Management (TQM) on Performance Improvement through Leadership Dewi Kholifatul Ummah; Saiful Bukhori; Dewi Rokhmah
Management Analysis Journal Vol 12 No 2 (2023): Management Analysis Journal
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/maj.v12i2.58116

Abstract

The results of the study indicate that there is a direct and indirect effect. Total Quality Management (TQM) is a method used by customer satisfaction oriented companies to improve managerial performance. This study aims to determine the direct and indirect effect of TQM on performance through leadership as a moderating variable. The research method is a quantitative research conducted at the Jatibanteng Public Health Center. The number of samples in the study was 73 with a sampling technique using the entire total population. Analysis of the data used is using smartPLS. First, leadership has a direct effect on employee performance with a t statistic of 8,581. Second, TQM has a direct effect on leadership with a t statistic of 54.377. Third, TQM has a direct effect on employee performance with a t statistic of 11.762. Fourth, the results of the analysis of P value < 0.005 means that there is an indirect effect between TQM on employee performance, which can also be interpreted if the intervening variable (leadership) plays a role in mediating the relationship between TQM and employee performance.
Analysis of Hospital Without Wall Service Quality at Dr. Iskak Tulungagung Hospital With Donabedian’s Model Krisnha Dian Ayuningtyas; Saiful Bukhori; FX Ady Soesetijo
Jurnal Manajemen Kesehatan Indonesia Vol 11, No 3 (2023): Desember 2023
Publisher : Magister Kesehatan Masyarakat, Fakultas Kesehatan Masyarakat, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jmki.11.3.2023.307-318

Abstract

dr. Iskak Tulungagung hospital made a healthcare service innovation during Covid-19 pandemic. This innovation called as hospital without wall to reduce the Covid-19 transmission. This program provides overall health services integrating pre-, intra-, inter-, and post-hospital care services through the Public Safety Center (PSC) platform. Authors examine the implementation of a hospital without walls in post-hospital aspect by using Donabedian's Model to improve service quality. The independent variables are facility and waiting time. The dependent variable is satisfaction. The intervening variable is patient perception. Assessment using a Likert scale questionnaire with a value range of 1-5. Descriptive data analysis used SPSS 25 and multivariate analysis used SMARTPLS 3.0. Our 96 respondents are very satisfied with this service but had to wait for a long time until the nurse arrived at home. Our analysis showed that facility variable affects the waiting time so that is affects patient satisfaction. This program has good structure so it makes a good process and satisfaction. Waiting time significantly associated with facility.
Knowledge Graph Construction for Rice Pests and Diseases Muhammad Ariful Furqon; Saiful Bukhori
International Journal of Artificial Intelligence Research Vol 7, No 1 (2023): June 2023
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i1.1022

Abstract

The agricultural industry in Indonesia confronts the simultaneous task of augmenting food production to satisfy escalating demand while proficiently handling crop losses caused by pests and diseases.  This study introduces a novel approach that leverages knowledge graphs to transform traditional, expert-based knowledge into a dynamic and interconnected system for addressing these agricultural challenges. The study delineates constructing a comprehensive knowledge graph, commencing with data extraction with SPARQL queries, and progressing to ontology design, object property and datatype property specification, and instance generation. The resultant knowledge graph not only serves as an organized archive for pest and disease information but also gives a systematic framework for the integration, analysis, and decision-making of data in agriculture. This knowledge graph adds to the broader junction of data science and agriculture by improving the diagnosis, prevention, and control of rice diseases.
Penguatan Kompetensi Computational Thinking dalam Pembelajaran IPA Melalui Perancangan Pembelajaran Argumentasi Konstruktivis Bukhori, Saiful; Retnani, Windi Eka Yulia; Putra, Januar Adi; Dharmawan, Tio
Wikrama Parahita : Jurnal Pengabdian Masyarakat Vol. 8 No. 1 (2024): Mei 2024
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jpmwp.v8i1.7249

Abstract

Argumentasi merupakan keterampilan kritis yang perlu dibangun pada siswa usia SD, dan perlu dikembangkan pada siswa usia sekolah menengah. Secara teoritis, siswa dengan usia muda seharusnya mampu memahami dan mem­bangun argumen, akan tetapi berdasarkan bukti empiris belum mendukung harapan tersebut. Kondisi ini juga terjadi pada siswa di SD sekitar desa jelbuk. Pada pengabdian kepada masyarakat ini dirancang dan diimplementasikan penguatan kompetensi computational thinking (CT) dalam pembelajaran IPA melalui perancangan pembelajaran argumentasi konstruktivis. Penguatan kompetensi CT pada pengabdian ini dilakukan menggunakan konsep CT-Argumentasi. CT menyediakan proses yang diperlukan untuk merumuskan argumen, sedangkan argumen memanfaatkan dan menerapkan keterampil­an CT melalui penalaran logis. CT yang diberikan kepada siswa dalam peng­abd­ian kepada masyarakat ini mengacu pada 4 tahapan yaitu: decompos­ition, pattern recognition, abstraction, dan algorithm. Hasil dari pengabdian kepada masyarakat ini dapat meningkatkan pemahaman siswa terhadap materi sebesar 40%. Pengabdian ini juga mengenalkan CT kepada siswa dan guru, dan dapat meningkatkan keterampilan menyelesaikan permasalahan dengan CT dibuktikan dengan rata-rata 30% siswa yang hadir angkat tangan dan dapat menjawab dengan benar, ketika diberi pertanyaan dengan permasalahan terbuka yang diambil dari contoh soal di situs web resmi Bebras Indonesia.
Perancangan dan Pembuatan Serious Game Sebagai Simulasi Aktivitas Bisnis dan Akuntansi Menggunakan Pendekatan Agent-Based Modelling Wijaya, Angga Ari; Bukhori, Saiful; Oktavia, Nelly
BERKALA SAINSTEK Vol 5 No 2 (2017)
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/bst.v5i2.5532

Abstract

Permainan memiliki efek positif dalam mendukung kemampuan motorik seseorang untuk berkembang. Salah satu bahasan menarik dalam permainan adalah simulasi bisnis yang memiliki kategori serious game untuk dijadikan alternatif media pembelajaran dalam memahami konsep dasar bisnis dan aktivitas akuntansi. Gameplay dibuat dengan menciptakan artificial bisnis level UKM yang melakukan aktivitas jual beli, dimana di dalamnya terdapat game world, pelanggan dan toko yang berinteraksi untuk menghasilkan fenomena sebuah pasar. Aktivitas jual beli menjadi dasar siklus akuntansi untuk pemain belajar dan memahami kejadian finansial. Setiap agent diberi attribute yang digunakan sebagai parameter untuk membentuk personality-trait dan pengambilan keputusan pembelian serta aktivitas yang membentuk tingkah laku sehari - hari melalui State Machine dan Rule Based System (RBS). Simulasi perilaku konsumen dalam pasar virtual digunakan sebagai trigger aktivitas utama bisnis yaitu transaksi penjualan. Kejadian finansial yang terjadi dari proses simulasi menghasilkan proses jurnal untuk memberikan pemain pengalaman dalam memproses transaksi dengan contoh sumber aktivitas buatan.Kata Kunci: Serious Game, Perilaku Konsumen, Agent-based Model, A Star, Stack Finite State Machine, Rule-Based System.
The Development of Stacking Techniques in Machine Learning for Breast Cancer Detection Van FC, Lucky Lhaura; Anam, M. Khairul; Bukhori, Saiful; Mahamad, Abd Kadir; Saon, Sharifah; Nyoto, Rebecca La Volla
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.416

Abstract

This study addresses the challenges of accurately detecting breast cancer using machine learning (ML) models, particularly when handling imbalanced datasets that often cause model bias toward the majority class. To tackle this, the Synthetic Minority Over-sampling Technique (SMOTE) was applied not only to balance the class distribution but also to improve the model's sensitivity in detecting malignant tumors, which are underrepresented in the dataset. SMOTE was effective in generating synthetic samples for the minority class without introducing overfitting, enhancing the model's generalization on unseen data. Additionally, AdaBoost was employed as the meta model in the stacking framework, chosen for its ability to focus on misclassified instances during training, thereby boosting the overall performance of the combined base models. The study evaluates several models and combinations, with K-Nearest Neighbors (KNN) + SMOTE achieving an accuracy of 97%, precision, recall, and F1-score of 97%. Similarly, C4.5 + Hyperparameter Tuning + SMOTE reached 95% in all metrics. The stacking model with Logistic Regression (LR) as the meta model and SMOTE achieved a strong performance with 97% accuracy, precision, recall, and F1-score all at 97%. The best result was obtained using the combination of Stacking AdaBoost + Hyperparameter Tuning + SMOTE, reaching an accuracy of 98%. These findings highlight the effectiveness of combining SMOTE with stacking techniques to develop robust predictive models for medical applications. The novelty of this study lies in the integration of SMOTE and advanced stacking methods, particularly using AdaBoost and Logistic Regression, to address the issue of class imbalance in medical datasets. Future work will explore deploying this model in clinical settings for accurate and timely breast cancer detection.
Pelatihan Penggunaan Platform Canva untuk Optimalisasi Desain Grafis bagi Pengrajin Papan Bunga Akrilik Bukhori, Saiful; Bukhori, Hilmi Aziz; Dharmawan, Tio; Prasetyo, Beny; R., Windi Eka Y.
Jurnal Pengabdian Pada Masyarakat Vol 10 No 1 (2025): Jurnal Pengabdian Pada Masyarakat
Publisher : Universitas Mathla'ul Anwar Banten

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30653/jppm.v10i1.1105

Abstract

Pengrajin papan bunga akrilik, terutama yang membuat papan bunga beserta tulisan ucapan selamat pada momen spesial dengan desain khusus sering menghadapi beberapa permasalahan dalam desain tulisannya antara lain adalah: kualitas tulisan dan keterbacaan, keterampilan teknikal terutama dalam menentukan jenis dan ukuran tulisan, kreativitas dan desain sesuai dengan permintaan klien, efisiensi waktu pembuatan, serta estetika dan fungsi. Permasalahan ini disebabkan karena belum memiliki pengetahuan tentang cara mengelola tulisan ucapan selamat pada momen spesial dan masih menggunakan cara manual. Pengabdian kepada masyarakat ini bertujuan untuk memberikan keterampilan pada pengrajin papan bunga akrilik di Malang selaku peserta pelatihan dalam mengelola tulisan ucapan momen spesial pada papan bunga akrilik dengan menggunakan platform desain grafis online canva. Berdasarkan hasil evaluasi pengabdian kepada masyarakat yang kemudian dianalisis secara sistematis menunjukkan adanya peningkatan pengetahuan pengrajin papan bunga akrilik di Malang dalam hal manajemen desain tulisan pada papan bunga akrilik sekaligus mempengaruhi produk desain papan bunga secara keseluruhan sebelum dan sesudah dilaksanakan pelatihan. Acrylic flower board craftsmen, especially those who make flower boards with congratulatory writings on special moments with special designs often face several problems in their writing designs, including: writing quality and readability, technical skills especially in determining the type and size of writing, creativity and design according to client requests, efficiency of production time, and aesthetics and function. This problem is caused by not having knowledge about how to manage congratulatory writings on special moments and still using manual methods. This community service aims to provide skills to acrylic flower board craftsmen in Malang as training participants in managing special greeting writings on acrylic flower boards using the canva online graphic design platform. Based on the results of the community Service evaluation which were then analyzed systematically, it showed an increase in the knowledge of acrylic flower board craftsmen in Malang in terms of writing design management on acrylic flower boards as well as influencing the overall flower board design product before and after the training was carried out.
Co-Authors Ahmad Fauzal Adifia Ahmad Firdaus Ababil Ahmad Firdaus Ababil Al Munawir Anam, M Khairul Ancah Caesarina Novi Marchianti Antonius Cahya Prihandoko Basbeth, Faishal Bayhaqqi Bayhaqqi Bukhori, Hilmi Aziz Dewi Kholifatul Ummah Dewi Rokhmah Dharmawan, Tio Diah Adistia Diah Adistia A Diah Ayu Retnani Wulandari Fahruddin Arrasyid Alfansuri Faishal Basbeth Feby Indriana Yusuf Feby Sabilhul Hanafi Firman Firman Furqon, Muhammad Ariful FX Ady Soesetijo Gayatri Dwi Santika Gusfan Halik Hairul Anam Hanesya, Arini Farihatul Haryanto, Kurniawan Wahyu Hastungkara, Duhita Husnul Hotimatus s Husnul Hotimatus Sahroh I Ketut Eddy Purnama januar adi putra, januar adi Krisnha Dian Ayuningtyas Lucky Lhaura Van FC, Lucky Lhaura Luh Putu Ratna Sundari Mahamad, Abd Kadir Malik Qilsi, Fatkhur Ruli Markus Apriono Maulia Azizah Maulina Azizah Mauridhi Heri Purnomo Mochamad Hariadi Mohammad Ovi Sanjaya Mohammad Zarkasi Muhammad Bagus Rizqi Alvian Muhammad Noor Dwi Eldianto Mustika Rahmasuci Mustika Rahmasuci Nafolion Nur Rahmat, Nafolion Nur Negoro, Wahyu Saptha Nur Kholis Mansur Nuryadi Nuryadi Oktalia Juwita Oktavia, Nelly Puspitarini, Niken Wahyu Putra, Januar Adi PUTRI WULANDARI R., Windi Eka Y. Rebecca La Volla Nyoto Saon, Sharifah Sari, Meylita Shasha Nur Faadhilah Sonya Sulistyono Sri Hartatik Sri Hernawati Sri Wahyuni Sumijan Sumijan Surmayanti, Surmayanti Syaiful Anam Tio Dharmawan Umroh Makhmudah Vivi Sefrinta Izza Afkarina Wijaya, Angga Ari Wiji Utami Windi Eka Yulia Retnani Yudha Alif Aulia Yudha Alif Auliya Yudhi Tri Gunawan Yunarni, Wiwik