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Audit Tata Kelola Sistem E-Learning Siakad dengan Metode Framework Cobit 5.0 Domain DSS (Deliver, Service, Support) Tusaria Tri Wahyu Ningrum; Purwono Purwono; Imam Ahmad Ashari; Riska Suryani
Seminar Nasional Penelitian dan Pengabdian Kepada Masyarakat 2022: Prosiding Seminar Nasional Penelitian dan Pengabdian Kepada Masyarakat (SNPPKM 2022)
Publisher : Universitas Harapan Bangsa

Teknologi Informasi dalam sebuah instansi sangat berguna jika diterapkan tepat dengan tujuan dan standar perusahaan. Universitas Harapan Bangsa merupakan kampus swasta yang teletak di Purwokerto yang sebagian besar proses operasionalnya sudah menggunakan teknologi informasi. Dalam mencapai tujuan perusahaan maka penerapan Teknologi dan Sistem Informasi yang sudah diterapkan harus tetap dievaluasi agar semakin memudahkan pengguna. Proses evaluasi teknologi informasi tersebut bisa dilakukan dengan adanya audit tata kelola sistem informasi untuk mengidentifikasi seberapa besar tingkat kematangan pada sistem yang sudah diterapkan. Audit dalam penelirian ini memanfaatkan kerangka kerja cobit dengan domain proses dss. Audit ini dilakukan untuk mengidentifikasi sejauh mana level kematakan pada sistem e-learning SIAKAD. Hasil dari penelitian yang telah dilakukan, SIAKAD memiliki tingkat kematangan dengan nilai 4,06 dan berada pada tingkat maturity 4. Hasil ini menunjukan bahwa sistem e-learning SIAKAD telah diimplementasikan dengan konsisten sejalan dengan kebijakan yang sudah ditentukan.

Evaluasi Kinerja Investasi Teknologi Informasi Pada Sistem Informasi Pusat Penerimaan Mahasiswa Baru Menggunakan Framework Val IT 2.0 Siti Rubaeah; Purwono Purwono; Retno Agus Setiawan; Imam Ahmad Ashari
Prosiding Seminar Nasional Unimus Vol 5 (2022): Inovasi Riset dan Pengabdian Masyarakat Guna Menunjang Pencapaian Sustainable Developm
Publisher : Universitas Muhammadiyah Semarang

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Perkembangan teknologi yang begitu pesat membuat banyak perusahaan berlomba-lombamenciptakan teknologi untuk menunjang bisnisnya. Investasi TI adalah salah satu media untukmenunjang kinerja bisnis, namun dengan besarnya biaya yang dikeluarkan untuk investasi TI perludievaluasi manfaat dari kinerja investasi TI. UHB merupakan salah satu universitas yang melakukaninvestasi TI untuk sistem informasi PMB. Investasi TI di UHB perlu dievaluasi untuk dapat mengetahuitingkat kinerjanya. Val IT2.0 merupakan framework yang dapat digunakan untuk mengevaluasiinvestasi TI, tetapi dalam penelitian ini hanya berfokus pada domain Value Governance (VG) untukmengetahui kinerja investasi TI dari sisi management practice. Hasil dari penelitian yang dilakukan,ditemukan bahwa UHB berada pada level 3 (defined) yang artinya pemahaman terkait investasi TIsudah tersampaikan, dilakukannya tata kelola untuk hasil yang lebih efisien serta alokasi sumber dayaTI yang lebih baik. Kata Kunci: Evaluasi, investasi TI, Val IT 2.0.

IMPLEMENTASI APLIKASI KEUANGAN BERBASIS ANDROID UNTUK MEMBANTU KEGIATAN JIMPITAN DI TINGKAT RT DESA SOKARAJA KIDUL BANYUMAS Jatmiko Indriyanto; Imam Ahmad Ashari; Anggit Wirasto
Jurnal Cahaya Mandalika ISSN 2721-4796 (online) Vol. 4 No. 3 (2023)
Publisher : Institut Penelitian Dan Pengambangan Mandalika Indonesia (IP2MI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/jcm.v4i3.1873

Jimpitan is an activity at the RT (neighborhood) level, carried out every day, by collecting money from the houses in the RT 07 RW 01 village of Sokaraja Kidul. In carrying out each jimpitan activity, there are problems encountered, starting with recording errors, people who have paid are thought not to have paid, there are residents who have been registered for jimpitan but have never been withdrawn, every month there is a financial report for jimpitan, that also makes a lot of mistakes. Therefore, we propose an Android-based jimpitan financial application to help solve the problem. After trying to apply for a week, most of the problems can be resolved. Residents and RT administrators were also given questionnaires, to find out their responses to using the Android-based jimpitan financial application, the results were good, and the residents were suitable and had no difficulties.

Pendekatan Transfer Learning dan SMOTE untuk Klasifikasi Kanker Kulit pada Imbalanced Dataset Lutviana, Lutviana; Purwono, Purwono; Imam Ahmad Ashari
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 2 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

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Skin cancer is one of the most commonly diagnosed cancers worldwide, with the incidence increasing every year. While early detection is a key factor in reducing skin cancer mortality, conventional methods such as biopsy have limitations in terms of cost and invasiveness. This research applies a deep learning based approach for skin cancer classification with Convolutional Neural Networks (CNN) model using transfer learning method. 3 CNN architectures namely MobileNetV2, EfficientNetB0, and DenseNet121 are used to evaluate the performance of the model in detecting skin cancer. One of the main challenges in this research is the imbalanced dataset, which can cause bias in classification. The Synthetic Minority Over-Sampling Technique (SMOTE) was applied to improve the representation of minority classes. The dataset used comes from Kaggle and consists of 2,357 images classified into 9 skin cancer categories. The results show that the transfer learning method combined with SMOTE can significantly improve the accuracy of the model, especially in detecting classes with a smaller number of samples. The evaluation was conducted using accuracy, precision, recall, and f1-score metrics. This research is expected to contribute to the development of an artificial intelligence-based skin cancer detection system that is more accurate, efficient, and can be used as a tool for medical personnel in early diagnosis of skin cancer.

Implementasi dan Evaluasi Kinerja Sistem IoT Multi-Sensor Berbasis ESP32 untuk Pemantauan dan Peringatan Dini Lingkungan secara Real-Time Arif Setia Sandi Ariyanto; Deny Nugroho Triwibowo; Imam Ahmad Ashari; Rito Cipta Sigitta Haryono
JSAI (Journal Scientific and Applied Informatics) Vol 9 No 1 (2026): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v9i1.9861

Real-time environmental monitoring has become increasingly important due to growing urban and industrial activities that affect air quality, noise levels, and physical environmental stability. However, many existing monitoring systems remain relatively expensive, lack portability, and are limited to passive monitoring functions without clear performance evaluation. This study aims to implement and evaluate the performance of an Internet of Things (IoT)-based multi-sensor environmental monitoring system integrated with a mobile application and real-time early warning features. The system is developed using an ESP32 microcontroller connected to DHT22, MQ135, SW-420, and KY-037 sensors to monitor temperature, humidity, air quality, vibration, and noise levels. Sensor data are transmitted to a server via a RESTful API, stored in a MySQL database, and visualized in real time through a Flutter-based mobile application. The research adopts a Research and Development (R&D) approach, encompassing requirement analysis, system design, implementation, integration, and functional testing. The experimental results indicate that the system can transmit multi-sensor data reliably with low response time, present environmental information in real time, and consistently deliver early warning notifications when environmental parameters exceed the defined threshold values. This study contributes by providing a practical and replicable performance evaluation of an IoT-based multi-sensor system suitable for small-scale environmental monitoring.

Pendekatan Transfer Learning dan SMOTE untuk Klasifikasi Kanker Kulit pada Imbalanced Dataset Lutviana, Lutviana; Purwono, Purwono; Imam Ahmad Ashari
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 2 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No2.pp323-331

Skin cancer is one of the most commonly diagnosed cancers worldwide, with the incidence increasing every year. While early detection is a key factor in reducing skin cancer mortality, conventional methods such as biopsy have limitations in terms of cost and invasiveness. This research applies a deep learning based approach for skin cancer classification with Convolutional Neural Networks (CNN) model using transfer learning method. 3 CNN architectures namely MobileNetV2, EfficientNetB0, and DenseNet121 are used to evaluate the performance of the model in detecting skin cancer. One of the main challenges in this research is the imbalanced dataset, which can cause bias in classification. The Synthetic Minority Over-Sampling Technique (SMOTE) was applied to improve the representation of minority classes. The dataset used comes from Kaggle and consists of 2,357 images classified into 9 skin cancer categories. The results show that the transfer learning method combined with SMOTE can significantly improve the accuracy of the model, especially in detecting classes with a smaller number of samples. The evaluation was conducted using accuracy, precision, recall, and f1-score metrics. This research is expected to contribute to the development of an artificial intelligence-based skin cancer detection system that is more accurate, efficient, and can be used as a tool for medical personnel in early diagnosis of skin cancer.

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