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All Journal Semesta Teknika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Insect (Informatics and Security) : Jurnal Teknik Informatika ILKOM Jurnal Ilmiah JURIKOM (Jurnal Riset Komputer) Systemic: Information System and Informatics Journal Jurnal Pengabdian Dharma Laksana JURNAL MAHAJANA INFORMASI Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Respati Jurnal Tekinkom (Teknik Informasi dan Komputer) Bubungan Tinggi: Jurnal Pengabdian Masyarakat JITU : Journal Informatic Technology And Communication Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Abdimas: Papua Journal Of Community Service Jurnal Pengabdian Masyarakat Journal of Community Empowerment FRAMEWORK Jurnal Ilmu Komputer dan Informatika Jurnal Keperawatan Sehat Mandiri
Muhammad Rizki Setyawan
Program Studi Teknik Informatika, Universitas Muhammadiyah Sorong
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Nursing Public Health Social Sciences Other

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Journal : jurnal mahajana informasi

 1 
Sistem Pakar Deteksi Penyakit Kambing Menggunakan Certainty Factor Berbasis Android Rizki Setyawan, Muhammad
Jurnal Mahajana Informasi Vol 8 No 1 (2023): JURNAL MAHAJANA INFORMASI
Publisher : Universitas Sari Mutiara Indonesia Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51544/jurnalmi.v8i1.4008

Abstract

Diseases pose a serious threat to the health and well-being of livestock in the livestock industry, especially in goat farming. In addressing this challenge, the use of intelligent technologies such as expert systems is becoming increasingly important. Expert systems are computer programs that can mimic the knowledge and skills of human experts in specific fields. One of the methods used in expert systems is the Certainty Factor method. Certainty Factor is an inference method used in expert systems to measure the level of confidence in a conclusion based on predefined rules. This method takes into account certainty or uncertainty factors in decision-making. In the detection of diseases in goats, the Certainty Factor method considers the symptoms found in goats and calculates the confidence weights for each disease that may be the cause of those symptoms. This research aims to develop an Android-based expert system application using the Certainty Factor method. The results obtained from this research show that the application can assist goat farmers in identifying diseases that affect their livestock, enabling early intervention and reducing losses due to animal deaths.
Perbandingan Tools Forensik Dalam Analisis Bukti Digital Pada Aplikasi Skype Menggunakan Framework NIST Rizki Setyawan, Muhammad
Jurnal Mahajana Informasi Vol 8 No 2 (2023): JURNAL MAHAJANA INFORMASI
Publisher : Universitas Sari Mutiara Indonesia Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51544/jurnalmi.v8i2.4580

Abstract

In the rapidly evolving digital era, human communication has undergone significant changes thanks to instant messaging. Instant messaging enables us to easily and quickly connect with people around the world through mobile devices or computers. However, the use of instant messaging applications can have negative impacts such as fraud, harassment, illegal transactions, and more. Therefore, proper handling of cybercrime cases is crucial, which is why mobile forensics has become significant. Mobile forensics is a branch of digital forensics that aims to collect, analyze, and interpret data from mobile devices. This research aims to evaluate the performance of three forensic tools: Oxygen Forensic Suite, Belkasoft Evidence Center, and MOBILedit Forensic Express. It focuses on finding digital evidence related to activity information in the Skype application using the framework provided by NIST. The research results indicate that Oxygen Forensic Suite achieved the highest index value (98%), followed by Belkasoft Evidence Center (88%) and MOBILedit Forensic Express (84%).
Implementasi Deep Learning Menggunakan Cnn Untuk Klasifikasi Tingkat Kematangan Buah Jeruk Berbasis Android Rahardika Bahari Putra, Fajar; Rizki Setyawan, Muhammad; Soekarta, Rendra; Nabila; Fakhri , La Jupriadi
Jurnal Mahajana Informasi Vol 9 No 2 (2024): JURNAL MAHAJANA INFORMASI
Publisher : Universitas Sari Mutiara Indonesia Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51544/jurnalmi.v9i2.5462

Abstract

Indonesia is a country that heavily relies on the agricultural sector, including various types of horticultural commodities, especially fruits. One example is oranges, which have many benefits and a sweet, refreshing taste. To obtain the best flavor and freshness, fully ripe oranges are the preferred choice. However, the process of recognizing the ripeness of oranges still faces many challenges. With advances in computer technology, particularly through smartphones, many human tasks can now be performed more efficiently and practically. One useful technology is computer vision, which can be used to automatically identify and determine the ripeness of oranges. This research aims to implement Convolutional Neural Networks (CNN) to measure the model's performance and ensure its capability in classifying the ripeness of oranges. The results of the research show that classification using CNN with the VGG-16 architecture achieved a training accuracy of 96% and a validation accuracy of 97%.
RANCANG BANGUN APLIKASI SISTEM PAKAR UNTUK MENDIAGNOSA PENYAKIT PADA BALITA MENGGUNAKAN METODE DEMPSTER SHAFER DENGAN PENELUSURAN FORWARD CHAINING BERBASIS ANDROID Muhammad Surahmanto; Bahari Putra, Fajar Rahardika; Muhammad Rizki Setyawan; Ahmad Ilham
Jurnal Mahajana Informasi Vol 10 No 1 (2025): JURNAL MAHAJANA INFORMASI
Publisher : Universitas Sari Mutiara Indonesia Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51544/jurnalmi.v10i1.6079

Abstract

Penelitian ini bertujuan untuk merancang dan membangun aplikasi sistem pakar berbasis Android guna mendiagnosis penyakit pada balita menggunakan metode Dempster-Shafer dan penelusuran Forward Chaining. Aplikasi ini dikembangkan sebagai solusi terhadap pentingnya deteksi dini penyakit pada balita, mengingat masa usia dini merupakan fase pertumbuhan yang sangat krusial. Dengan memanfaatkan metode Dempster-Shafer, sistem mampu mengolah ketidakpastian data gejala dan menghasilkan diagnosis yang akurat, sementara Forward Chaining berperan dalam menelusuri aturan berbasis fakta yang tersedia. Hasil yang di dapat yakni 98% pilek berdasarkan deteksi penyakit dan pengujian dengan metode black box menunjukkan bahwa aplikasi berjalan sesuai fungsinya dan hasil diagnosis konsisten dengan perhitungan manual. Penelitian ini menunjukkan potensi penerapan kecerdasan buatan dalam mendukung pelayanan kesehatan anak, serta membuka peluang pengembangan sistem pakar berbasis Android yang lebih luas di masa mendatang. Saran kedepan agar lebih di perdalam lagi dalam proses mengidentifikasi penyakit balita dengan metode lainnya.
Co-Authors Abdul Fadlil Abdul Fadlil Ahistasari, Asih Ahmad Ilham Amri, Irman Anton Yudhana Aronggear, Karim Paul Bahari Putra, Fajar Rahardika Bekti Wiji Lestari Dewi Astria Faroek Elisabeth Serlina Elensia Bupu Ermin Ermin Ermin, E Fajar, Fajar Rahardika Bahari Putra Fakhri , La Jupriadi Fitriyani Tella Haris Haris, Haris Hermansa Hermansa Hilda Histiarini, Aprisa Rian Ilham, Ahmad Kahar, Muhammad Syahrul Kayatun, Siti Nur La Jupriadi Fakhri Marlinda Indah Eka Budiarti, Marlinda Indah Eka Mirga Maulana Rachmadhani Mohammad Arief Nur Wahyudien Mohammad Arief Nur Wahyudien Muh. Fadli Hasa Muhammad Jundullah Muzakkir Pangri Nabila Novita Sari Nurul Widya Har Putra, Fajar Rahardika Bahari Rachmadanur Rachmadanur Rahardika Bahari Putra, Fajar Rahmatullah Bin Arsyad Ramadhani, Ardhina Rawi, Rais Dera Pua Reflita Reflita Rinanda Tri Setiawan Sangadji, Zulkarnain Simori, Pascalina Magrice Slameto, Andika Agus Soekarta, Rendra Soleha Rahayu Muklis Hayu Sundari Sundari Surahmanto Suseno, Dimas Adi Tasman Tasman Teguh Hidayat Iskandar Alam Tella, Fitriyani tivani nurizqi Umar Rusli Marasabessy Verra Widhi Astuti Wattimena, Mikhael Yudhana , Anton