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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Teknologi International Journal of Artificial Intelligence Research JURNAL MEDIA INFORMATIKA BUDIDARMA Progresif: Jurnal Ilmiah Komputer Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Generation Journal Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa Dan Inovasi Jurnal Tekinkom (Teknik Informasi dan Komputer) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Sistem Komputer dan Informatika (JSON) Bulletin of Computer Science Research Scientific Student Journal for Information, Technology and Science Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Pengabdian Masyarakat Nasional Jurnal Polimesin Inovasi Gagasan Abdimas & Kuliah Kerja Nyata Jurnal Abdimas Mahakam
Ahmad Fauzi
Universitas Buana Perjuangan Karawang
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Other

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Komparasi Kinerja K-Means dan K-Medoids dalam Klasterisasi Kelompok Keluarga Berisiko Stunting Seluruh Desa di Jawa Barat Wildan Gusty Sakhril Amin; Ahmad Fauzi; Cici Emilia Sukmawati; Ayu Ratna Juwita
Scientific Student Journal for Information, Technology and Science Vol. 7 No. 2 (2026): Scientific Student Journal for Information, Technology and Science
Publisher : Scientific Student Journal for Information, Technology and Science

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

Abstract

Stunting merupakan masalah gizi kronis yang masih menjadi tantangan besar di Indonesia. Provinsi Jawa Barat memiliki prevalensi stunting sebesar 21,7%, sehingga menjadi provinsi dengan prevalensi stunting tertinggi kedua di Pulau Jawa. Untuk mendukung upaya pencegahan stunting, penelitian ini bertujuan mengelompokkan desa-desa di Jawa Barat berdasarkan kelompok keluarga berisiko stunting menggunakan algoritma K-Means dan K-Medoids, serta mengevaluasi performa kedua algoritma tersebut. Penelitian ini menerapkan metodologi Cross-Industry Standard Process for Data Mining (CRISP-DM). Hasil penelitian menunjukkan bahwa algoritma K-Means membentuk tiga klaster, yaitu klaster rendah sebanyak 5.196 desa, klaster sedang sebanyak 106 desa, dan klaster tinggi sebanyak 9 desa. Sementara itu, algoritma K-Medoids juga menghasilkan tiga klaster, yaitu klaster rendah sebanyak 5.196 desa, klaster sedang sebanyak 105 desa, dan klaster tinggi sebanyak 14 desa. Hasil evaluasi menunjukkan bahwa algoritma K-Means memiliki performa yang lebih baik dengan nilai Silhouette Score sebesar 0,9278 dan Davies–Bouldin Index (DBI) sebesar 0,9380 dibandingkan algoritma K-Medoids, yang memperoleh nilai Silhouette Score sebesar 0,9233 dan DBI sebesar 1,0699. Penelitian ini diharapkan dapat membantu pemerintah dalam menentukan prioritas intervensi stunting secara lebih tepat sasaran serta menjadi referensi dalam pengembangan metode klasterisasi menggunakan algoritma K-Means dan K-Medoids.
Assessment Decision Support System Best Teacher By Using Analytical Hierarchy Process (AHP) Method April Lia Hananto; Bayu Priyatna; Fitria Nurapriani; Ahmad Fauzi; Tukino Tukino; Naufal Zubdi Ahnaf
International Journal of Artificial Intelligence Research Vol 6, No 1.1 (2022)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v6i1.1.572

Abstract

Assessment of teachers by the Principal of SMA Negeri 1 Kedungwaringin certainly needs to be done to determine the best teacher, so that teacher performance is in accordance with the specified competencies because the teacher is the most important and influential role in the world of education in the process of teaching and learning activities. The assessment was carried out not only for civil servants (PNS), including honorary teachers who also participated in the assessment process so that there were no limitations in evaluating teachers at SMA Negeri 1 Kedungwaringin. This assessment process uses the Analytical Hierarchy Process (AHP) Algorithm. The method used aims to determine the best teacher at SMA Negeri 1 Kedungwaringin who is in accordance with the assessment criteria prepared. The results of the ranking show that Dian Purwanti, S.Pd obtained the highest score of 0.342 out of 5 other teachers. This application is expected to assist school principals in determining the best teacher based on the criteria and weight of each existing value.
Development of Health Mask Identification Using YOLOv5 Architecture Ahmad Fauzi; Prasetyo Ajie; Anis Fitri Nur Masruriyah; Deden Wahiddin; Hanny Hikmayanti; April Lia Hananto
International Journal of Artificial Intelligence Research Vol 6, No 1.1 (2022)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v6i1.1.573

Abstract

Coronavirus Disease 2019 (COVID-19) causes the state to suffer losses, especially in the health sector. WHO calls for controlling COVID-19 with health protocols that must be obeyed, one of which is wearing a mask. The use of masks can reduce the transmission of COVID-19. But there are still many people who ignore the protocol to use masks properly. So a system was created to detect the use of masks properly using the YOLOv5 architecture. Aiming to help regulate the use of masks in public areas or open places. The process of this research begins with data collection in the form of images. The collected image data will later be used as a dataset and model training will be carried out using the YOLOv5s model. The accuracy results obtained from this study reached 90.37%
Sosialisasi Alur Kerja Sistem Electronic Traffic Law Enforcement (ETLE) Dari Segi Ilmu Komputer Vision Pada Masyarakat Kiki Ahmad Baihaqi; Ahmad Fauzi; Jamaludin Indra
Jurnal Igakerta Vol. 1 No. 3 (2024): Jurnal Igakerta
Publisher : IGAKERTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70234/1km1j504

Abstract

Sistem deteksi kendaraan bermotor yang digunakan pada sistem E-TLE bukan hal baru, dikarenakan sistem tersebut sudah banyak diteliti dan diimplementasikan dinegara maju. Deteksi yang dimaksud adalah mendeteksi nomor polisi yang ada pada suatu kendaraan kemudian dikonversi menjadi laporan dan dikategorikan dalam bentuk pelanggaran seperti apa sesuai perundang-undangan. Namu, tidak banyak Masyarakat yang paham akan alur proses deteksi dan akurasi dari sistem tersebut. Sehingga dibutuhkan sosialisasi kepada Masyarakat lebih lanjut dan mendalam. Sosialisasi dilakukan pada kegiatan pengabdian kepada masyakarat yang dilakukan ditingkat desa yang berada dibagian luar Kabupaten Karawang. Masyarakat yang mengikuti adalah perangkat desa setingkat RT dikarenakan nanti akan disosialisasikan kembali oleh aparatur desa kepada Masyarakat. Peserta berjumlah 30 orang yang dibagi menjadi 2 termin pagi dan sore, dikarenakan kapasitas ruangan dan faktor efektifitas penjelasan agar kondusif. Hasilnya 50%  yaitu berjumlah 15 orang tidak mengetahui perihal sistem seperti ini bisa akurat dan mengidentifikasikan nomor kendaraan serta pelaggarannya
Analisis Perbandingan Algortima Support Vector Machine, Random Forest dan Naive Bayes Untuk Prediksi Penyakit Kanker Paru-Paru Rendy Alfa Rizky; Ahmad Fauzi; Dwi Sulistya Kusumaningrum; Hilda Yulia Novita
Journal of Information System Research (JOSH) Vol 7 No 3 (2026): April 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i3.9611

Abstract

The lungs are one of the vital organs responsible for the processes of respiration and blood circulation, with smoking habits being the primary factor contributing to the development of lung cancer. In Indonesia, the prevalence of this disease continues to increase, placing it eighth in the Southeast Asian region. Globally, lung cancer accounts for approximately 11.6% of all cancer cases and 18% of total cancer-related deaths.This study aims to analyze and compare the performance of Support Vector Machine (SVM), Random Forest, and Naïve Bayes algorithms in predicting lung cancer, as well as to determine the best-performing algorithm based on accuracy, precision, and recall metrics. The study utilizes the Lung Cancer Prediction dataset obtained from Kaggle, consisting of 309 instances and 16 attributes. The approach involves the implementation of three machine learning algorithms, namely Support Vector Machine (SVM), Random Forest, and Naïve Bayes. The research process includes data collection, preprocessing, data transformation, feature selection, model development, and evaluation using a confusion matrix. The experimental results show that both SVM and Naïve Bayes achieve the same accuracy of 91.07%, while Random Forest obtains an accuracy of 89.28%. In terms of evaluation metrics, SVM demonstrates more consistent performance with a precision of 95% and recall of 93%, whereas Naïve Bayes shows a higher recall of 95% with a precision of 93%. On the other hand, Random Forest exhibits limitations in identifying non-cancer cases. Based on the overall results, SVM is considered the most optimal method as it provides a better balance of performance. This study indicates that machine learning has significant potential as a supporting tool for early detection of lung cancer in a more accurate and efficient manner.
Co-Authors Ade Suhara Adi Rizky Pratama Adie Putra Afif Hakim Agung Rahmat Ahmad Rahman Amelia Pratiwi Amri Abdulah Ananda Faizah Anggie Wiyani Putri Anis Fitri Nur Masruriyah Anis Fitri Nurmasruriyah Anwar Ilmar Ramadhan April Hananto April Lia Hananto Ardi Apriansyah Arphilia Nur Rani Aviv Yuniar Rahman Ayu Ratna Juwita Ayu Sri Rahayu Baihaqi, Kiki Ahmad Bambang Sukowo Bayu Kerta Sukma Gandara Candra Zonyfar Deden Wahiddin Dedi Mulyadi Destanto Muhamad Yusuf Dodi Mulyadi Dwi Kusumaningrum Dwi Sulistya Kusumaningrum Dwi Sulistya Kusumaningrum Dwi Tian Tonara Euis Nurlaelasari Farhan Muhammad Fadillah Firmansyah Maulana Fitria Nurapriani Hananto, Agustia Hanny Hikmayanti Handayani Hilda Yulia Novita Hilda Yulia Novita Ilham Dwi Ischan Indra, Jamaludin Indri Rahmawati Intan Murni Pratiwi Irfan Irma Putri Rahayu Khoirudin Khoirudin Khoirudin Lestari, Santi Arum Puspita Maharina Maharina Mohamad Rizkiyanto Mudzakir, Tohirin Al Murtalim Nana Rahdiana Naufal Zubdi Ahnaf Novalia, Elfina Nunung Nurjanah Prasetyo Ajie Priyatna, Bayu Rahmat Rahmat Randy Kurniadi Rendy Alfa Rizky Ricko Valderama Ridwan Maulana Rini Beatrix Laurentzia Saruni Dwiasnati Siregar, Amril Mutoi Sony Hartono Wijaya Sriyanto Sriyanto Sukarman Sukarman Sukmawati, Cici Emilia Sumanto Sutan Faisal Sutan Faisal Sutan Faisal Tjong Wan Sen Toif Muhayat Tukino Tukino Tukino Wildan Gusty Sakhril Amin Yana Cahyana Yana Cahyana Yudo Devianto Yusuf Eka Wicaksana Yusuf Khoiruddin