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All Journal JURNAL DERIVAT: JURNAL MATEMATIKA DAN PENDIDIKAN MATEMATIKA Infotech Journal Jurnal Informatika Upgris Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Progresif: Jurnal Ilmiah Komputer Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat International Journal Software Engineering and Computer Science (IJSECS) COMSERVA: Jurnal Penelitian dan Pengabdian Masyarakat Jurnal Inkofar Duta.com : Jurnal Ilmiah Teknologi Informasi dan Komunikasi Journal of Scientech Research and Development Proceeding of International Conference Health, Science And Technology (ICOHETECH) Prosiding Seminar Nasional Teknologi Informasi dan Bisnis CSRID
Purwanto, Eko
Universitas Duta Bangsa Surakarta
Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation

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Development and Evaluation of an Expert System for the Early Diagnosis of Dental Diseases Eko Purwanto; Devi Pramita Sari; Farahwahida Mohd
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4500

Abstract

Dental diseases, such as caries, periodontitis, and gingivitis, affect public health worldwide, especially in regions where healthcare access remains restricted. The study develops an expert system for early dental disease diagnosis using Forward Chaining and Certainty Factor methods. The system overcomes deficiencies found in previous approaches, such as Naive Bayes and Dempster-Shafer, which demonstrate insufficient accuracy and unclear result interpretation. The developed expert system incorporates a knowledge base containing 7 diseases, 40 symptoms, and 7 diagnostic rules. Forward Chaining enables inference of potential diagnoses from reported symptoms, while the Certainty Factor evaluates diagnostic reliability by calculating confidence levels. System evaluation through Black Box testing achieved 92% diagnostic accuracy, and usability assessments revealed 85% user satisfaction rates, demonstrating that the system proves reliable, accurate, and accessible. Research findings indicate the expert system offers viable solutions for improving dental disease diagnosis in underserved and remote areas, potentially enhancing oral health outcomes through early detection and prompt intervention.
Analisis Perbandingan Metode Yolo Dan Faster R-CNN Dalam Deteksi Objek Manusia Muhammad Ilham Pratama; Nurchim Nurchim; Eko Purwanto
Progresif: Jurnal Ilmiah Komputer Vol 21, No 2 (2025): Agustus
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v21i2.2890

Abstract

Human object detection is an important component in surveillance systems, behavior analysis, and crowd management in public spaces such as stadiums, shopping malls, and terminals. However, the detection process often faces obstacles such as inconsistent lighting, complex backgrounds, and high object density. This study aims to compare the performance of two object detection algorithms, namely YOLOv10 and Faster R-CNN, in detecting humans. The dataset used is uniform and covers a wide range of environmental conditions to ensure fair and objective evaluation. This research involves the stages of data collection, pre-processing, model training, testing, and performance evaluation. The test results show that YOLOv10 has a performance advantage with an mAP50 value of 0.75, higher than that of Faster R-CNN which obtained an AP50 of 0.67. Based on these findings, YOLOv10 is recommended for use in applications that require real-time human detection with a high level of accuracy.Kata kunci: YOLOV10; Faster R-CNN; Object Detection AbstrakDeteksi objek manusia merupakan komponen penting dalam sistem pengawasan, analisis perilaku, dan pengelolaan keramaian di ruang publik seperti stadion, pusat perbelanjaan, dan terminal. Namun, proses deteksi sering menghadapi kendala seperti pencahayaan yang tidak konsisten, latar belakang kompleks, dan kepadatan objek tinggi. Penelitian ini bertujuan buat membandingkan kinerja dua algoritma deteksi objek, yaitu YOLOv10 dan Faster R-CNN, dalam mendeteksi manusia. Dataset yang digunakan bersifat seragam dan mencakup berbagai kondisi lingkungan untuk memastikan evaluasi yang adil dan objektif. Penelitian ini melibatkan tahapan pengumpulan data, pra-pemrosesan, pelatihan model, pengujian, dan evaluasi performa. Hasil pengujian menunjukkan bahwa YOLOv10 memiliki keunggulan performa dengan nilai mAP50 sebesar 0,75, lebih tinggi dibandingkan Faster R-CNN yang memperoleh AP50 sebesar 0,67. Berdasarkan temuan tersebut, YOLOv10 direkomendasikan untuk digunakan dalam aplikasi yang membutuhkan deteksi manusia secara real-time dengan tingkat akurasi tinggi.Kata kunci: YOLOV10; Faster R-CNN; Deteksi Objek 
ANALISIS PENGARUH KUALITAS SISTEM, KUALITAS INFORMASI, DAN KUALITAS LAYANAN PADA SISTEM (ERP) TERHADAP KEPUASAN PENGGUNA DI PT. SRI REJEKI ISMAN TBK Fiqih Dwi Rifai; Eko Purwanto; Nurmalitasari
INFOTECH journal Vol. 10 No. 1 (2024)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/infotech.v10i1.8396

Abstract

ERP adalah suatu sistem integrasi yang mengalami penyederhanaan proses bisnis suatu organisasi agar dapat beroperasi dengan lebih efisien dan efektif. Namun, salah satu hambatan dalam penerapan sistem ERP ini adalah kurangnya pengetahuan beberapa pengguna terkait sistem tersebut. Keberhasilan suatu sistem ERP sangat bergantung pada sejauh mana sistem tersebut bermanfaat dan memberikan kemudahan kepada pengguna, sehingga dapat memberikan kepuasan kepada mereka. Aspek-aspek kualitas seperti kualitas sistem, informasi, dan layanan sangat berpengaruh secara signifikan terhadap tingkat kepuasan pengguna terhadap sistem ERP. Temuan dari penelitian ini didapatkan dari 17% dari total 486 karyawan di PT. Sri Rejeki Isman Tbk, dengan sampel berjumlah 83 karyawan. Metode pengumpulan data yang digunakan adalah kuesioner yang didistribusikan kepada 83 karyawan. Hasil analisis dari pengolahan data penelitian menunjukkan bahwa kualitas sistem, kualitas informasi, dan kualitas layanan dalam sistem ERP secara positif dan signifikan memengaruhi tingkat kepuasan pengguna
Co-Authors Abdullah Sajad Afu Ichsan Pradana Agus Mardiyono Agustina Srirahayu Ajeng Putri Sulistyawati Ali Muhdi Anggit Nurhidayah Ari Zusnan Fahrudin Atina, Vihi Bambang Prasetyo Bangun Pradjadi Cipto Utomo Bangun Prajadi Cipto Utomo Devi Pramita Sari Didik Nugroho Dwi Septieni Ema Sagita Desylawati Ery Permana Yudha Farahwahida Mohd Feny Ramadhani Feri Setiyono Fiqih Dwi Rifai Ilham Fahrul Pratama Indah Nofikasari Indra Hastuti Intan Oktaviani Kris Dayanti Marginingsih Marginingsih Maulindar, Joni Muhammad Ilham Pratama Norma Puspitasari Novita Widyasari Nurchim Nurchim Nurchim Nurchim Nurmalitasari Nurmalitasari Nurmalitasari Otami Amalina Permatasari, Hanifah Pipin Widyaningsih Ratna Puspita Indah Sabar Sularno Shandra Isti Kharisma Auliya Alamsyah Sigit Gunawan Singgih Purnomo Softi Ulin Nuha Sopingi Sri Ningrum Sukma Rahmawati Titin Listiani Velinda Febriana Wiji Lestari Wijiyanto Yusmawan Dwi Suseno