Article Per Year (5 Year)
p-Index From 2021 - 2026
5.532
P-Index
This Author published in this journals
All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Pendidikan Vokasi Jurnal Sains dan Teknologi Jurnal Sarjana Teknik Informatika Jurnal Teknologi Informasi dan Ilmu Komputer Sistemasi: Jurnal Sistem Informasi Jurnal Pengabdian UntukMu NegeRI Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Penelitian Pendidikan IPA (JPPIPA) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JITK (Jurnal Ilmu Pengetahuan dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING ILKOM Jurnal Ilmiah Compiler KACANEGARA Jurnal Pengabdian pada Masyarakat Martabe : Jurnal Pengabdian Kepada Masyarakat JURTEKSI Jurnal Pemberdayaan: Publikasi Hasil Pengabdian Kepada Masyarakat Jambura Journal of Informatics Building of Informatics, Technology and Science JISKa (Jurnal Informatika Sunan Kalijaga) Mobile and Forensics Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Jurnal Informatika dan Rekayasa Perangkat Lunak International Journal of Advances in Data and Information Systems Jurnal REKSA: Rekayasa Keuangan, Syariah dan Audit Innovation in Research of Informatics (INNOVATICS) Humanism : Jurnal Pengabdian Masyarakat Jurnal Pendidikan dan Teknologi Indonesia Prima Abdika: Jurnal Pengabdian Masyarakat Bulletin of Pedagogical Research Jurnal Pengabdian Pada Masyarakat Jurnal Pengabdian Informatika (JUPITA) Bulletin of Social Informatics Theory and Application Sabangka Abdimas Jurnal Pengabdian Masyarakat Sabangka Mohuyula : Jurnal Pengabdian Kepada Masyarakat Scientific Journal of Informatics
Herman Yuliansyah, Herman
Program Studi Teknik Informatika, Fakultas Teknologi Industri, Universitas Ahmad Dahlan
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

Published : 50 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 50 Documents
Search

 1   2   3   4   5 
Automated Identification of Oil Palm’s 17th Leaf Using YOLOv12 and Spatial Positioning Rahmawan, Jihad; Yuliansyah, Herman; Yudhana, Anton; Irfan, Syahid Al
Innovation in Research of Informatics (Innovatics) Vol 7, No 2 (2025): September 2025
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v7i2.15766

Abstract

This study proposes an artificial intelligence–based approach for automatic identification of the 17th leaf in oil-palm trees (Elaeis guineensis), which serves as a key physiological indicator for nutrient monitoring. The method integrates YOLOv12 object detection with a spatial-positioning algorithm that estimates leaf order through vertical sorting of detected fronds. A total of 1,250 annotated field images were collected from farmer-recorded videos to train and evaluate the system. The proposed model achieved a mean average precision (mAP@0.5) of 92.4% and an average positional error of 10.6 pixels in locating the 17th leaf. Compared with manual identification that requires 3–5 minutes per tree, the automated system performs the entire process in under 15 seconds, providing over 95% time efficiency improvement. This work demonstrates a novel fusion of real-time deep-learning detection and spatial reasoning for nutrient-focused precision agriculture and establishes a practical foundation for scalable, automated leaf indexing in plantation management.
Machine Learning-based Chatbot Model for Healthcare Service: A Bibliometric Analysis Ekawati, Nia; Riadi, Imam; Yuliansyah, Herman
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 7, No 3 (2025): November (Special Issue)
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v7i3.3050

Abstract

While machine learning-based chatbots hold significant potential in healthcare services, a comprehensive synthesis regarding their roles, user demographics, benefits, and limitations remains unavailable, hindering in-depth understanding and future development. This study aims to conduct a bibliometric analysis to identify implementation trends and the research landscape of ML-based chatbot models in healthcare, simultaneously highlighting relevant existing gaps. Analysis of Scopus data using VOSviewer and “Publish or Perish” reveals “machine learning”, “chatbot” and “healthcare” as dominant keywords, indicating intensive research focus areas with stable publication growth. The United States emerges as a central hub for international research collaboration, particularly in AI for malnutrition; however, several outlier countries require further integration. Deep learning algorithms are identified as a crucial methodological trend for future directions. Chatbots possess the potential to revolutionize healthcare by enhancing accessibility and efficiency. Nevertheless, effective implementation necessitates careful consideration of ethical aspects, privacy, and data quality. The identified research gaps underscore the urgency for a holistic synthesis to guide responsible and effective chatbot innovation.
Capacity building for LAZIS administration through Google Applications Training Yuliansyah, Herman; Fahana, Jefree; Prahara, Adhi; Masitha, Alya
KACANEGARA Jurnal Pengabdian pada Masyarakat Vol 8, No 4 (2025): November
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/kacanegara.v8i4.3039

Abstract

The rapid development of information technology has prompted social institutions such as LazisMU to adopt digital administrative systems. However, technical limitations among staff hinder optimal implementation. This community service aimed to enhance the administrative capacity of LazisMU staff through targeted training in Google Applications. The training involved needs assessment, module development, and interactive sessions covering Google Drive, Docs, Sheets, and Forms. Results indicate significant improvement in participants’ understanding and skills, particularly in document management, financial reporting, and data handling. Pre-test and post-test comparisons, along with direct observation, showed over 60% improvement in comprehension scores. These outcomes highlight the positive impact of digital training on operational efficiency. Further training and periodic monitoring are recommended to ensure continued digital competence development.
Enhancing Clustering Accuracy Using K-Means with Seeds Optimization Mahiruna, Adiyah; Ngatimin, Ngatimin; Destriana, Rachmat; Rachmawanto, Eko Hari; Yuliansyah, Herman; Hidayat, Muhammad Taufiq
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10458

Abstract

In this study, the development of the Mean-based method proposed by Goyal and Kumar will be carried out by changing the initial cluster center determination step, which was originally based on the origin point O (0,0), to be replaced with the arithmetic mean. To assess the performance of the proposed method, it will be compared with the Global K-means method and the Mean-based K-means method. In this study, the performance of these methods will be measured using the Davies-Bouldin Index, and the significance of the proposed method will be measured using the Friedman Test. This study proposes a method of Improving K-Means Performance through Initial Center Optimization based on Second Global Average for Clustering Osteoporosis Diagnosis of lifestyle factors. Evaluation of K-Means performance through Initial Center Optimization based on Second Global Average with DBI measurements. The targeted experimental results of this study include improving the performance of K-means optimized through the initial center based on Second Global Average. From the results of nine experiments with the number of clusters [2,3,4,5,6], it can be seen that the method proposed in this study has the same superior performance compared to the Mean Based method and compared to the Global K-means method.
Vulnerability Analysis of Smart Lock Using NIST SP 800-115 Method Aziz, Muhammad Abdul; Sutikno, Tole; Yuliansyah, Herman; Dewi, Ayu Intansari; Rohmadi, Yusuf Eko; Setiawati, Donna
Jurnal Penelitian Pendidikan IPA Vol 11 No 8 (2025): August
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i8.12219

Abstract

Internet of Things (IoT)-based devices, such as smart locks, are becoming increasingly common in home security systems due to the convenience and efficiency they offer. However, without a strong security system, these devices can become potential targets for attacks. This study aims to evaluate and identify potential security vulnerabilities in the Dekkson ELC 9318 smart lock using the NIST SP 800-115 approach. Three authentication methods were tested in this study: PIN code, fingerprint (biometric), and RFID card. The tools used include Nmap for network scanning, Wireshark for traffic analysis, and Proxmark3 for the RFID card cloning process. The results showed several aspects that could still be improved, such as the PIN protection mechanism against brute-force attacks, the vulnerability of MIFARE Classic RFID cards that can still be replicated under certain conditions, and the need to strengthen authentication at the API endpoint to minimize the risk of unauthorized access. Meanwhile, biometric authentication proved to be more resistant to basic spoofing attempts. This research is expected to provide constructive input for the development of security systems in IoT devices, particularly smart locks.
RANCANG BANGUN APLIKASI ANDROID POS (POINT OF SALE) KAFE UNTUK KASIR PORTABLE DAN BLUETOOTH PRINTER Pamungkas, Gilang; Yuliansyah, Herman
JST (Jurnal Sains dan Teknologi) Vol. 6 No. 1 (2017)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (635.996 KB) | DOI: 10.23887/jstundiksha.v6i1.8828

Abstract

Kafe merupakan salah satu jenis usaha di bidang kuliner yang banyak diminati pengunjung. Beberapa permasalahan yang ada adalah sistem transaksi keuangan di kafe belum memanfaatkan kasir digital, hanya berupa mesin drawer. Sehingga terdapat batasan pada perhitungan transaksi. Tujuan dari penelitian menghasilkan aplikasi kasir tablet android untuk membantu proses transaksi penjualan dan dapat merekapitulasi laporan data transaksi di kafe. Selain itu, pada aplikasi ini ditambahkan fitur pencetakan kwitansi untuk pelanggan. Pengujian aplikasi android dilakukan dengan metode unit test dan menunjukkan sudah berjalan dengan lancar dan tidak ada method yang error, sehingga dapat dinyatakan lolos. Selain itu, pengujian black box test dapat disimpulkan bahwa aplikasi berjalan sesuai dengan yang telah dirancang.
Edukasi Pencegahan Demam Berdarah Dengue (Dbd) Untuk Meningkatkan Pengetahuan Jumantik Cilik Di Kelurahan Ambarketawang Handayani, Lina; Sulistyawati, Sulistyawati; Nisa Novianti, Tria; Fitriani, Isah; Jumaedi Nasir, Ardiansyah; Wahyuni Sukesi, Tri; Nafiati, Lu’lu’; Asti Mulasari, Surahma; Yuliansyah, Herman; Tentama, Fatwa
Humanism : Jurnal Pengabdian Masyarakat Vol 6 No 1 (2025): April
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Abstrak Demam Berdarah Dengue (DBD) adalah penyakit yang sulit dideteksi karena dapat tidak menunjukkan gejala sama sekali dan juga bisa menunjukkan gejala yang sangat parah. Di Indonesia, kasus DBD terus meningkat karena mobilitas, kepadatan penduduk, dan perubahan iklim. Kabupaten Sleman, khususnya Kelurahan Ambarketawang, memiliki tingkat kasus DBD yang tinggi pengabdian kepada masyarakat ini bertujuan untuk meningkatkan pengetahuan kader jumantik cilik mengenai pencegahan DBD. Kegiatan ini dilaksanakan melalui metode edukasi kesehatan dan evaluasi. Edukasi kepada 117 kader jumantik cilik dilakukan menggunakan media video animasi dan PowerPoint. Media ini merupakan sebuah pendekatan edukasi yang interaktif dan menarik. Hal ini diharapkan dapat meningkatkan pengetahuan anak-anak tentang DBD dan memotivasi masyarakat untuk menjaga lingkungan agar bebas dari sarang nyamuk. Pengetahuan diukur menggunakan kuesioner pretest dan posttest. Hasil Uji Wilcoxon menunjukkan terdapat peningkatan pengetahuan kader jumantik cilik secara signifikan (p-value 0,000). Edukasi pencegahan DBD dengan media video animasi dan PowerPoint berhasil meningkatkan pengetahuan kader jumantik cilik. Edukasi mengenai pencegahan DBD sejak usia dini akan menciptakan kebiasaan positif yang berkelanjutan, sehingga dapat mengurangi kasus DBD di masa mendatang.
Pencegahan Stunting dengan Inovasi Teknologi berupa Modifikasi Timbangan Digital Terkoneksi Android Sudarsono, Bambang; Sukesi, Tri Wahyuni; Tentama, Fatwa; Mutmainah, Nur Fitri; Yuliansyah, Herman; Mulasari, Surahma Asti; Nafiati, Lu’lu’; Sulistyawati, Sulistyawati; Ghozali, Fanani Arief
Prima Abdika: Jurnal Pengabdian Masyarakat Vol. 3 No. 4 (2023): Volume 3 Nomor 4 Tahun 2023
Publisher : Program Studi Pendidikan Guru Sekolah Dasar Universitas Flores Ende

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37478/abdika.v3i4.3176

Abstract

Stunting is a problem that has a negative impact on society and can last for a long time. This community service program aims to increase the knowledge and skills of partner communities in preventing stunting by using innovative technology called the "Tas Stunting Kit." This activity involves creating appropriate technology, training health cadres, and evaluating technological innovation. The digital scale is modified to connect to an Android tablet via Bluetooth and is packaged in a bag. This community service program was attended by 29 participants, all of whom were health cadres, with the implementing team consisting of the chief proposer, additional proposers, and a second team consisting of lecturers and students. This technological innovation was evaluated with the Software Usability Scale (SUS) as a series of modifications to digital scales and Android applications, with the results having an acceptable acceptability range. The subsequent follow-up is developing a more integrated data collection system as a basis for the village government to make data-based decisions.
Aspect-Based Sentiment Analysis of User Reviews on the Game “Honkai: Star Rail” Using Naïve Bayes Classifier Agus Setiawan, Hisyam; Yuliansyah, Herman
Sistemasi: Jurnal Sistem Informasi Vol 13, No 5 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i5.4343

Abstract

Game is a form of entertainment that is often used to refresh the mind from the fatigue of daily activities and routines. Honkai: Star Rail is a popular turn-based game from Hoyoverse available on Google Play Store. Several studies have proposed Sentiment Analysis with Naïve Bayes classification method. However, not many have identified the reviews of a game to the extent of identifying on its aspects. In aspect-based sentiment analysis, text is analyzed to identify various attributes or components, then the relevant sentiment (positive, negative, or neutral) for each of these attributes is determined. This research aims to analyze aspect-based sentiment using the Naïve Bayes Classifier method, as well as categorize sentiment into positive and negative, and classify reviews into certain aspects. The results obtained after 5-fold iteration obtained the best average accuracy of 79%, The evaluation results show that it is necessary to tune the model using Grid Search Hyperparameter Tuning. Optimization of smoothing parameters with alpha = 0.1 proved effective in improving model performance with the highest weighted average accuracy of 93%. The evaluation results show that Grid Search Hyperparameter Tuning optimization gives better performance to the Naive Bayes algorithm model in multi-label classification.
PREDICTING LOAN ELIGIBILITY WITH SUPPORT VECTOR MACHINE: A MACHINE LEARNING APPROACH Rajunaidi, Rajunaidi; Yuliansyah, Herman; Sunardi, Sunardi; Murinto, Murinto
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 3 (2025): Juni 2025
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.v11i3.3876

Abstract

Abstract: Non-performing loans remain one of the main challenges faced by cooperatives, particularly when the loan eligibility assessment process is still conducted manually. This traditional approach tends to be time consuming, subjective, and prone to inaccurate decisions. This study aims to develop a predictive model for borrower eligibility using the Support Vector Machine (SVM) algorithm as a more efficient and objective machine learning-based solution. A total of 1,000 loan history records were processed using RapidMiner software, taking into account variables such as salary, years of employment, loan amount, monthly installment, employment status, monthly expenses, number of dependents, housing status, age, and collateral value. The model’s performance was evaluated using a confusion matrix and classification metrics including accuracy, precision, recall, and kappa. The results indicate that the SVM model achieved an accuracy of 90.05%, precision of 90.13%, recall of 90.05%, and f1 score of 90,08%, reflecting a strong performance in classifying borrower eligibility. The application of this method makes a significant contribution to the development of data driven decision support systems within cooperative environments. This finding expands the scientific understanding in the field of microfinance and supports the implementation of artificial intelligence technologies in making decisions that are more precise, rapid, and accurate.Keywords: cooperative; eligibility prediction; machine learning; non-performing loan; SVMAbstrak: Kredit macet merupakan salah satu permasalahan utama yang dihadapi koperasi, terutama ketika proses penilaian kelayakan peminjam masih dilakukan secara manual. Pendekatan ini cenderung lambat, subjektif, dan berisiko menghasilkan keputusan yang kurang akurat. Penelitian ini bertujuan untuk membangun model prediksi kelayakan peminjam menggunakan algoritma Support Vector Machine (SVM) sebagai solusi berbasis machine learning yang lebih efisien dan objektif. Sebanyak 1.000 data riwayat pinjaman diolah menggunakan tools RapidMiner dengan mempertimbangkan variabel: gaji, lama bekerja, besar pinjaman, angsuran per bulan, status pegawai, pengeluaran bulanan, jumlah tanggungan, status rumah, umur, dan nilai jaminan. Evaluasi model dilakukan menggunakan confusion matrix dan metrik klasifikasi seperti akurasi, presisi, recall, dan kappa. Hasil menunjukkan bahwa model SVM mencapai akurasi  90,05%, presisi 90,13%, recall 90,05%, dan f1 score 90,08%, yang mencerminkan performa model yang sangat baik dalam mengklasifikasikan kelayakan peminjam. Penerapan metode ini memberikan kontribusi penting dalam pengembangan sistem pendukung keputusan berbasis data di lingkungan koperasi. Temuan ini memperluas wawasan keilmuan di bidang keuangan mikro dan mendukung penerapan teknologi kecerdasan buatan dalam pengambilan keputusan yang lebih tepat, cepat, dan akurat.Kata Kunci: koperasi; kredit macet; machine learning; prediksi kelayakan; SVM  
Co-Authors Abdul Fadlil Adhi Prahara, Adhi Agus Setiawan, Hisyam ALYA MASITHA Anton Yudhana Apriliani, Evinda Ardiansyah, Ricy Arief Ghozali, Fanani Asti Mulasari, Surahma Ayu Laksmi Pandhita, Ayu Laksmi Bambang Sudarsono Bella Okta Sari Miranda Bidinnika, Muhammad Kunta Darmanto Darmanto Destriana, Rachmat Dewi Soyusiawaty Dewi, Ayu Intansari Donna Setiawati Eko Hari Rachmawanto Fatwa Tentama Febiyan, Rifal Firdaus, Muhammad Khysam Fitriani Mutmainah, Nur Fitriani, Isah Ghozali, Fanani Arief Habie, Khairul Fathan Hafin, Aqid Fahri Hazar, Siti Herman Herminarto Sofyan Hidayat, Muhammad Taufiq Hildayanti, Ica Kurnia Hildayanti, Ica Kurnia Ika Arfiani Imam Riadi Irfan, Syahid Al Jayawarsa, A.A. Ketut Jefree Fahana Jumaedi Nasir, Ardiansyah Khoirul Anam Dahlan Khoirunnisa, Itsnaini Irvina Kintung Prayitno, Kintung Lifa, Lifa Lina Handayani Listyaningrum, Prabandari Mahiruna, Adiyah Muhammad Abdul Aziz Muhammad Dzikrullah Suratin, Muhammad Dzikrullah Muhammad Fahmi Mubarok Nahdli Muhammad Kunta Biddinika Muhammad Ridwan Murinto Murinto Murinto Mutmainah, Nur Fitri Nafiati, Lu'lu' Nafiati, Lu’lu’ NGATIMIN, NGATIMIN Nia Ekawati, Nia Nisa Novianti, Tria Novitasari, Isda Desy Nur Rochmah Dyah Pujiastuti Pamungkas, Gilang Pamungkas, Gilang Pratama, Ridho Haikal Pratama, Wegig Putro, Aldibangun Pidekso R. Hafid Hardyanto, Settings Rachmaliany, Nur Rahmawan, Jihad Rahmawati, Rahmawati Raihan, Habib Aulia Rajunaidi, Rajunaidi Razak, Farhan Radhiansyah Rohmadi, Yusuf Eko Rusydi Umar Salji, Rinday Zildjiani Sri Winiarti Subardjo Subardjo, Subardjo Sukesi , Tri Wahyuni Sulistyawati , Sulistyawati Sulistyawati Sulistyawati Sunardi Sunardi Sunardi Surahma Asti Mulasari Tole Sutikno Tri Wahyuni Sukesi Ulumiyah, Iftitah Dwi Wahyuni Sukesi, Tri Wala, Jihan Wan Ali, Wan Nur Syamilah Yohanni Syahra Yulianto, Dinan Yulisasih, Baiq Nikum