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All Journal Jurnal Masyarakat Informatika Jurnal Teknologi Informasi dan Ilmu Komputer Jurnas Nasional Teknologi dan Sistem Informasi Matrix : Jurnal Manajemen Teknologi dan Informatika Jurnal AKSI (Akuntansi dan Sistem Informasi) DoubleClick : Journal of Computer and Information Technology SISFO Jurnal Hilirisasi IPTEKS (JHI) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JURNAL AGRI-TEK DIKEMAS (Jurnal Pengabdian Kepada Masyarakat) JEECAE (Journal of Electrical, Electronics, Control, and Automotive Engineering) Journal of Robotics and Control (JRC) Abdimasku : Jurnal Pengabdian Masyarakat Journal of Innovation Information Technology and Application (JINITA) TIERS Information Technology Journal Andalasian International Journal of Applied Science, Engineering, and Technology Prosiding Seminar Nasional Program Pengabdian Masyarakat Jurnal Cakrawala Ilmiah
Ardian Prima Atmaja
Politeknik Negeri Madiun
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Optimasi Aplikasi SIMAK-BMN untuk Inventarisasi Barang Milik Negara Berbasis Aplikasi Mobile Android Atmaja, Ardian Prima; Susanto, Fredy
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 6 No 2: April 2019
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (4905.899 KB) | DOI: 10.25126/jtiik.201962807

Abstract

Dalam sebuah satuan kerja atau institusi pemerintah di Negara Republik Indonesia, terdapat barang-barang yang dibeli atau diperoleh atas beban APBN yang kemudian dapat diidentifikasikan sebagai bagian dari Barang Milik Negara (BMN). BMN tersebut dicatat dalam sebuah aplikasi bernama Sistem Informasi Manajemen dan Akuntansi Barang Milik Negara (SIMAK-BMN). Untuk melakukan monitoring BMN yang telah tercatat di aplikasi tersebut, Kuasa Pengguna Anggaran (KPA) dan tim monitoring seringkali menemui beberapa kesulitan. Hal ini diakibatkan dari keterbatasan aplikasi SIMAK-BMN yang belum sepenuhnya mudah dioperasikan untuk keperluan monitoring. Dengan kondisi seperti itu maka pada makalah ini dibahas pengembangan sistem informasi monitoring BMN terpadu dengan melakukan optimasi terhadap database SIMAK-BMN. Sistem yang dibangun dapat dijalankan oleh tim monitoring BMN secara online menggunakan internet. Selain itu, dikembangkan pula sistem monitoring BMN secara mobile yang dapat diinstall pada perangkat smartphone berbasis Android. Sehingga, dalam pengelolaaanya, petugas tim pencatat dan penginventaris BMN dapat menggunakan smartphone mereka untuk membantu memudahkan pekerjaaan inventarisasi dengan melakukan scanning QR Code dari tiap-tiap BMN. Dengan adanya sistem monitoring BMN yang merupakan optimasi dari database SIMAK-BMN tersebut, diharapkan dapat mempermudah fungsi monitoring BMN dan menjadi kontribusi dalam pengembangan sistem monitoring internal suatu satuan kerja di Republik Indonesia serta mendukung kebijakan-kebijakan pengelolaan BMN. AbstractIn a unit or institution in the government of State of the Republic of Indonesia, there are goods obtained at the expense of the APBN which can be identified as the State Goods (BMN). BMN is recorded in an application called the Management Information System and Accounting for State Goods (SIMAK-BMN). To monitor the BMNs that have been recorded in that application, the Budget User Authority (KPA) and the monitoring team often encounter some difficulties. This is due to the limitations of the SIMAK-BMN application which has not been fully operational for monitoring purposes. With such conditions, this study discusses about the development of integrated BMN monitoring information system by optimizing the SIMAK-BMN database. The built system can be run by the BMN monitoring team using the internet. Moreover, also developed a mobile BMN monitoring system that can be installed on Android-based smartphone devices. Thus, in it’s management, BMN registration team can use their smartphone to scanning QR Code from each item of BMN. With the BMN monitoring system which is the optimization of the SIMAK-BMN database, it is expected to facilitate the BMN monitoring function and become a contribution in developing the internal monitoring system of a work unit in the government of Republic of Indonesia as well as supporting the policies of BMN management.
Machine Learning untuk Prediksi Kegagalan Mesin dalam Predictive Maintenance System Nisa'ul Hafidhoh; Ardian Prima Atmaja; Gus Nanang Syaifuddiin; Ikhwan Baidlowi Sumafta; Salva Mahardhika Pratama; Hafsah Nur Khasanah
Jurnal Masyarakat Informatika Vol 15, No 1 (2024): May 2024
Publisher : Department of Informatics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jmasif.15.1.63641

Abstract

In facing the Industrial Revolution 4.0, technologies such as the Internet of Things, Big Data and Artificial Intelligence are key to industrial modernization. Machine Learning approach as a part of artificial intelligence is used to process high-dimensional multivariable data and extract hidden relationships in complex industrial environments. In this research, Machine Learning is used to classify machine failures in building a Predictive Maintenance System. This research adopts the CRISP-DM (Cross Industry Standard Process for Data Mining) cycle which consists of the business understanding, data understanding, data preparation, modeling, evaluation and deployment stages. The Predictive Maintenance Dataset in the form of synthetic data used in this research reflects real industrial situations consists of 10,000 rows of data with ten features. Types of machine failure are classified into Heat Dissipation Failure, Power Failure, Overstrain Failure, and Tool Wear Failure. Exploratory Data Analysis is carried out to obtain a summary and visualization of data. The machine learning approach uses the Logistic Regression method and the model evaluation results reach an accuracy of 96.87%, in accordance with the data success criteria. The results of the machine learning modelling developed are implemented in a web-based Predictive Maintenance System application to make it easier for users to monitor machine conditions and predict machine failures.
Implementation of a Rule-Based Expert System in the Web-Based SMK Boarding and Semi Boarding Admission System by the Central Java Government Fajar, Muhammad Syaeful; Atmaja, Ardian Prima; Hafidhoh, Nisa'ul; Ismar, MH. Ramdhani; Ivansyah, Maulana Nur
Andalasian International Journal of Applied Science, Engineering and Technology Vol. 6 No. 1 (2026): March 2026
Publisher : LPPM Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/aijaset.v6i1.162

Abstract

The student admission process for boarding and semi-boarding vocational schools involves complex administrative, academic, and socio-economic criteria, which often lead to inefficiencies and inconsistencies when handled manually. This study proposes a web-based student admission system integrating a rule-based expert system to automate multi-stage selection processes in vocational high schools managed by the Central Java Provincial Government. The system was developed using a Research and Development approach with the Agile Scrum methodology. Knowledge representation is implemented through IF–THEN rules derived from officially verified admission guidelines, enabling automated scoring, ranking, and admission decisions. The proposed system was applied across three boarding schools and fifteen semi-boarding schools during the 2024 admission period. The results indicate that the system reduces processing time, improves scoring consistency, and enhances transparency and accountability in decision-making. This study demonstrates that integrating a rule-based expert system with official admission regulations provides an effective and scalable solution for large-scale student selection processes.
Co-Authors Ahmad Kudhori Ahmad Wildan Muammar Aminudin Azis Aulia el hakim Budi Artono Diana Karyawati Dimas Adi Saputra Dinar Nur Izzah Djoko Setyo Martono Dwi Setia, Lutfiyah Fajar, Muhammad Syaeful Fredy Susanto Gus Nanang Syaifuddiin Gus Nanang Syaifuddiin Hafidhoh, Nisa ul Hafidhoh, Nisa'ul Hafsah Nur Khasanah hakim, aulia el Hakim, Aulia El Hendrik Kusbandono Ikhwan Baidlowi Sumafta Ismar, MH. Ramdhani Ivansyah, Maulana Nur Joko Hartadi Karyawati, Diana Kudhori, Ahmad Lestariningsih, Tri Lestariningsih, Tri Lutfiyah Dwi Setia Lutfiyah Dwi Setia MH Ramdhani Ismar Ismar Mochamat Bayu Aji Muhammad Syaeful Fajar Mustofa, Muhammad Imron Abu Nisa'ul Hafidhoh Nisa'ul Hafidhoh Paksi, Angger Binuko Pratama, Lasardi Abdi Priyanto Priyanto Raden Mohamad Herdian Bhakti Salva Mahardhika Pratama Setia, Lutfiyah Dwi Sigit Kariagil Bimonugroho Susilo Veri Yulianto Susilo Veri Yulianto Susilo Veri Yulianto Susilo Veri Yulianto Tri Septianto Wibowo, Ari Purnomo Aji WULANDARI, WIDYA Yulianto, Susilo Veri