Article Per Year (5 Year)
p-Index From 2021 - 2026
5.35
P-Index
This Author published in this journals
All Journal Voteteknika (Vocational Teknik Elektronika dan Informatika) Syntax Jurnal Informatika POSITIF INFORMAL: Informatics Journal Format : Jurnal Imiah Teknik Informatika Faktor Exacta PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Jurnal ULTIMA InfoSys Jurnal Teknologi Jurnal TAMBORA CCIT (Creative Communication and Innovative Technology) Journal Building of Informatics, Technology and Science Jurnal Manajemen Informatika dan Sistem Informasi Jurnal Mnemonic JISA (Jurnal Informatika dan Sains) Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Ilmu dan Teknologi Peternakan Terpadu (JITPU) CSRID Pekayunan Journal of Applied Informatics Science
Herfandi Herfandi
Universitas Teknologi Sumbawa
Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Immunology & microbiology Industrial & Manufacturing Engineering

Published : 34 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 34 Documents
Search

 1   2   3   4 
Application of Information Gain to Select Attributes in Improving Naïve Bayes Accuracy in Predicting Customer's Payment Capability Herfandi, Herfandi; Zaen, Mohammad Taufan Asri; Yuliadi, Yuliadi; Julkarnain, M.; Hamdani, Fahri
JISA(Jurnal Informatika dan Sains) Vol 4, No 2 (2021): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v4i2.1044

Abstract

The customer is the main factor in the running of PT. XYZ. A good understanding of customers is very important for predicting the capability of customers to pay. The implementation of credit collectibility is used to determine the quality of customer credit, one of which is the customer's capability to pay interest and principal on time. While manually, it is very difficult to accurately predict the capability of customer credit payments. Data mining techniques with the Naïve Bayes algorithm were chosen to classify customers to be able to find patterns, analyze and predict, because they have good performance, are efficient, and simple. The Naïve Bayes algorithm has a weakness in terms of sensitivity to many attributes, so the accuracy is low. Based on the problem stated, his study will apply the Information Gain method to select the most influential attribute on the label in order to increase the accuracy of the Naïve Bayes algorithm. This research produces a new dataset with seven attributes: TENOR, SALARY, DOWN PAYMENT, INSTALLMENT, APPROVAL, OTR CLASS, AGE with Labels: Status and Id: Id number based on the Information Gain method. The dataset comparison process with 995 data records showed an increase in accuracy, precision, and AUC using the new dataset compared to the old dataset, but in the t-Test test with an alpha value = 0.05 there is a difference but not significant. In the evaluation process, performance experienced a significant increase in the use of new datasets with the following percentages of performance improvement: accuracy = 8%, precision = 18.42%, recall = 17.65% and AUC= 0.057%. The results of this study obtained AUC of 0.876, accuracy of 87.88%, precision of 61.90%, and recall of 76.47%, and classified into good classification. 
SMART ACADEMIC BERBASIS WEB RESPONSIF DI SMK KREATIF DOMPU Dody Priamitra; Herfandi; Yunanri.W; Dinola; Fahri Hamdani; Yuliadi; Herliana Rosika
Jurnal Manajemen Informatika dan Sistem Informasi Vol. 9 No. 2 (2026): MISI Juni 2026
Publisher : LPPM STMIK Lombok

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

Abstract

Efisiensi pengelolaan administrasi akademik merupakan salah satu faktor penting dalam meningkatkan kualitas layanan pendidikan. SMK Kreatif Dompu masih menghadapi berbagai kendala dalam pengelolaan data akademik yang dilakukan secara konvensional menyebabkan duplikasi data, keterlambatan penyampaian informasi, serta tingginya risiko kehilangan data. Penelitian ini bertujuan merancang dan mengimplementasikan aplikasi Smart Academic berbasis web responsif sebagai sarana berbasis teknologi pengelolaan data akademik di SMK Kreatif Dompu. Metode pengembangan perangkat lunak yang digunakan adalah Agile Programming dengan tahapan yang dilakukan secara iteratif pada setiap sprint. Sistem dikembangkan menggunakan konsep Responsive Web Design (RWD) sehingga dapat diakses melalui komputer maupun perangkat bergerak (smartphone). Pengujian sistem menggunakan metode Black-Box Testing terhadap 25 skenario pengujian yang mencakup fungsi login, manajemen data guru, data siswa, jadwal pelajaran, e-rapor, dan pengelolaan pengumuman. Hasil pengujian menunjukkan 100% skenario berhasil dijalankan sesuai dengan kebutuhan fungsional, tanpa ditemukan kegagalan fungsi pada fitur utama. Implementasi sistem berhasil mengintegrasikan seluruh proses administrasi akademik, mempercepat proses pengolahan data, mempermudah guru dalam pengisian nilai secara real-time. Dengan demikian, aplikasi Smart Academic berbasis web responsif terbukti mampu meningkatkan pengelolaan administrasi akademik dan mutu layanan pendidikan di SMK Kreatif Dompu.
CornLeafNet: Disease-Area-Based Corn Leaf Disease Classification Using Convolutional Neural Networks Herfandi Herfandi; Eri Sasmita Susanto; Fahri Hamdani; Jonathan Afriliansyah
Journal of Applied Informatics Science Volume 2 Issue 2 (2026)
Publisher : GWS Tech Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65897/jais.v2.i2.96

Abstract

Corn leaf diseases can reduce crop productivity by disrupting photosynthesis and plant growth. Manual identification in large-scale fields remains limited due to its dependence on observer expertise, visual similarity among disease symptoms, and variations in field conditions. This study proposes CornLeafNet, a Custom Convolutional Neural Network model for disease-area-based corn leaf disease classification. The dataset consists of XML-annotated corn leaf images, from which disease-affected regions were extracted through annotation parsing and bounding box-based cropping to focus the model on symptomatic leaf areas. CornLeafNet was developed to classify three disease categories: Grey Leaf Spot, Corn Rust, and Leaf Blight. The model achieved a validation accuracy of 97.66% and a testing accuracy of 98.60%, with precision, recall, and F1-score values of 0.9860, respectively. The best-performing model was converted into ONNX format and deployed in a web-based prototype for image- and video-based classification. The testing results showed that all core system functions operated as expected, indicating that CornLeafNet has potential as an automatic and practical support model for early corn leaf disease identification.
WORKSHOP ARTIFICIAL INTELLIGENCE, MEDIA PEMBELAJARAN INTERAKTIF, DAN STRATEGI OSN BAGI GURU SDN SEBASANG UNTER M. Julkarnain M Julkarnain; I Made Widiarta; Herfandi; Rodianto; Yunanri.W; Juniardi Akhir Putra; Dinola; Farida Idifitriani
Jurnal Pekayunan Vol. 2 No. 1 (2026): PEKAYUNAN Maret - Juli 2026
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/xgf33b84

Abstract

Implementasi Kurikulum Merdeka menuntut guru sekolah dasar untuk lebih kreatif dan adaptif dalam menciptakan pembelajaran berpusat pada siswa. Namun, beban kerja administratif yang tinggi serta kendala adaptasi teknologi membuat waktu guru untuk merancang media inovatif menjadi sangat terbatas. Padahal, teknologi Artificial Intelligence (AI) berpotensi besar mereduksi beban kerja tersebut. Kegiatan pengabdian ini bertujuan untuk meningkatkan literasi teknologi terapan dan keterampilan praktis guru sekolah dasar dalam mengoperasikan serta mengoptimalkan AI secara aman, efektif, dan efisien. Metode pelaksanaan kegiatan mengombinasikan ceramah dan demonstrasi praktik interaktif yang dibagi ke dalam tiga tahapan, yaitu persiapan, pelaksanaan demonstrasi, dan tindak lanjut. Kegiatan dilaksanakan di SDN Sebasang Unter dengan melibatkan 10 orang peserta yang terdiri dari kepala sekolah dan guru. Hasil kegiatan menunjukkan adanya perubahan positif berupa peningkatan kompetensi peserta dalam menyusun media pembelajaran digital seperti Wordwall dan Kahoot. Selain itu, peserta berhasil mempraktikkan teknik prompt engineering terstruktur untuk otomatisasi materi ajar dan berkas administrasi. Guru juga memperoleh pengayaan strategi pembinaan intensif untuk mempersiapkan siswa menghadapi Olimpiade Sains Nasional (OSN). Keberhasilan kegiatan ini dilihat dari peningkatan kompetensi peserta yang signifikan yaitu rata-rata dari 43,9 menjadi 86,3. Kesimpulannya, kegiatan workshop ini berhasil meningkatkan kompetensi profesional dan pedagogik guru dalam memanfaatkan teknologi AI demi mendukung produktivitas kerja dan efisiensi pembelajaran serta kesiapan sekolah dalam membina siswa berbakat secara berkelanjutan.
Co-Authors Aditya Agus Wisanto Agung Susilo Yuda Irawan Ahmad Fauzul Kabir Ahmad Muchlis Ali Kafabillah Assegaf , Ridwan Anggi Fitria Ari Syahwatullah Arman Diansyah Baihaqi, Kiki Ahmad Deri Afriliyansa Dinola Dody Priamitra Eko Purwirawansyah Elga Ramdani Eri Sasmita Susanto Fahri Hamdani Fahri Hamdani Farida Idifitriani Fifit Alfiah Gilang Ginanta Haris Yusuf Bakhtiar Herliana Rosika I Made Widiarta Idham Amdin Jonathan Afriliansyah Julkarnain, M. Juniardi Akhir Putra Kamal Prihandani Kevin Noanda Aditya Rudy Yanto Lokesworo M Julkarnain M. Julkarnain M. Julkarnain M. Julkarnain M Julkarnain Moch Wahyu Firmansyah Mohammad Taufan Asri Zaen Muhammad Hanif muhammad rizky, muhammad Mujahidin Patti Peiloh Mulyanto, Yudi Nurul Maulida Solihat Randi Candra Kirana Reza Avrizal Reza Maulana Rodianto, Rodianto Safira, Azzahrah Maulya Saruni Dwiasnati Suarantalla, Ryan Sukarna, Royan Habibie Sultan Naufal Abdillah Syarifuddin Syarifuddin Ulfatus Soleha Yuliadi Yuliadi Yuliadi Yuliadi Yulian Ansori Yunanri.W