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All Journal Telematika : Jurnal Informatika dan Teknologi Informasi Information Management For Educators And Professionals (IMBI) Indonesian Journal of Artificial Intelligence and Data Mining E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi Jurnal Sistem Informasi Akasia: Artikel Ilmiah Sistem Informasi Akuntansi Computer Science (CO-SCIENCE) Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Simpatik: Jurnal sistem Informasi dan Informatika Profitabilitas Nanggroe: Journal of Scholarly Service Jurnal Pengabdian Kepada Masyarakat Kalam
Aryo Tunjung Kusumo
Universitas Bina Sarana Informatika
Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Social Sciences Other

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IMPLEMENTASI FRAMEWORK DENGAN LARAVEL PADA SISTEM AKUNTANSI PENDAPATAN RUMAH MAKAN FAMILY Saputara, Elin Panca; Rismaya, Siska; Kusumo, Aryo Tunjung; Priyono, Priyono; Saryoko, Andi; Dwiantoro, Tino
E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi Vol 12 No 2 (2023): e-Jurnal JUSITI
Publisher : Universitas Dipa Makassar

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

Abstract

Rumah makan family adalah merukan usaha yang bergerak bisnisnya dibidang rumah makan. Menyediakan makanan pokok atau nasi dengan lauk dan minumannya. Tetapi, dalam proses transaksi, pencatatan pendapatannya, penyimpanan data transaksi masih dilakukan secara manual, belum terdapat sistem terkomputerisasi di Rumah makan Family. Hal ini dapat menyebabkan masalah seperti human error, kesalahan dalam penghitungan dan pencatatan pendapatan, kehilangan bukti transaksi karena penyimpanan yang tidak efisien. Dengan berkembangnya teknologi yang semakin pesat, dapat membantu dalam semua bidang, salah satunya perdagangan. Maka untuk memecahkan permasalahan yang ada, penulis membuat sistem yang terkomputerisasi, yaitu rancang bangun sistem informasi akuntansi penapatan pada rumah makan family. Dalam membuat aplikasi web ini penulis melakukan wawancara dan riset. Selain itu, dalam pembuatan aplikasi web ini menggunakan Laravel, Visual Studio-Code, serta Bahasa pemrograman dengan PHP, HTML. Dengan membuat sistem terkomputerisasi, rumah makan tersebut memiliki fasilitas seperti Login, data Customer, daftar menu berikut dengan kategorinya, transaksi pemesanan serta laporan yang dapat diakses oleh user. Dengan rancang bangun yang terbentuknya sistem terkomputerisasi tercapai kegiatan transaksi, penghitungan pendapatan yang lebih efektif serta efisien.
Implementasi Rapid Application Development Pada Pengembangan E-Commerce Persambi Karawang Saepudin, Atang; Tunjung Kusumo, Aryo; Rudianto, Biktra
PROFITABILITAS Vol 3 No 1 (2023): JURNAL PROFITABILITAS
Publisher : Sistem Informasi Akuntansi Kampu Kabupaten Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/profitabilitas.v3i1.1970

Abstract

Advances in computer technology today have moved quickly and massively in various aspects. The computer, which is equipment created to facilitate human work, has changed the way and work system from conventional to computerized. Computerization has now been applied in all fields, including the product sales business. One of them is Pengcab Persambi Karawang which also requires an information system that can support and provide satisfactory service for customers in selling their products. For this reason, researchers built a sales system at the Persambi Karawang Branch Office, which until now has not been computerized. The existing system at Pengcab Persambi Karawang is still done manually, starting from recording customers who buy products, to storing other data related to the sales process to making reports, so that it is possible during the process that errors occur in the recording. The inaccuracy of the reports that are made and the delay in finding the necessary data are the weaknesses of the current system. The design of this information system is the best solution to solve the problems that exist in this company, and with a computerized system an effective and efficient activity can be achieved in supporting the activities of this organization. A computerized system is better than a manual system so that it runs more effectively and efficiently and the current sales system is more conducive than the previous system. The e-commerce system development method is carried out using the Rapid Application Development method approach. This method is a system development method that is carried out quickly and briefly. So it is considered more appropriate in the development of e-commerce systems.
Monitoring Tekanan Udara Berbasis Internet of Things Menggunakan Thingsboard untuk Kontrol Ruangan Saputra, Elin Panca; Ginanjar, Syaiful; Kusumo, Aryo Tunjung; Saryoko, Andi
Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Vol 5, No 04 (2024): Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jrami.v5i4.10973

Abstract

Teknologi dibuat untuk membantu manusia dalam menyelesaikan berbagai pekerjaan. Teknologi yang begitu populer pada saat ini adalah Internet of Things. Penerapan pada teknologi Internet of Things banyak digunakan dalam berbagai bidang pada saat ini. Salah satunya dimanfaatkan untuk melakukan monitoring tekanan udara. Penelitian ini bertujuan untuk membuat suatu perangkat yang dapat mengirimkan kondisi tekanan udara dalam tangki melalui Internet of Things dengan protocol Message Queuing Telemetry Transport (MQTT) dan terintegrasi dengan Thingsboard sebagai platform pemantauan dan pengelolaan data IoT yang kuat dan fleksibel. Kami mengintegrasikan sensor tekanan dengan mikrokontroler Raspberry Pi yang terhubung ke jaringan internet, memungkinkan pengiriman data tekanan udara ke server Thingsboard secara berkala. Data tersebut kemudian diolah dan disajikan dalam bentuk grafik yang interaktif dan mudah dimengerti melalui antarmuka pengguna Thingsboard. Hasil penelitian ini, mikrokontroller Raspberry Pi memiliki spesifikasi hardware yang lebih optimal dibandingkan Arduino sebagai media perantara antara data yang dibaca oleh sensor yang kemudian disimpan pada aplikasi Thingsboard untuk kebutuhan industri jangka panjang.
Prediction of Heart Disease Using K-Nearest Neighbor and Particle Swarm Optimization Algorithm Saputra, Elin Panca; Saryoko, Andi; Kusumo, Aryo Tunjung; Priyono, Priyono
Indonesian Journal of Artificial Intelligence and Data Mining Vol 8, No 1 (2025): March 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v8i1.33373

Abstract

One of the leading causes of death nowadays is heart disease, so more has to be done to avoid it, such as by making prediction models work better. Among the machine learning algorithms is K-Nearest Neighbor (K-NN) is among the best methods for predicting heart disease based on several risk factors, including smoking, high blood pressure, diabetes, age, and so on. To get accurate values and attribute selection features, we tested them with K-NN, and to improve the results of our research predictions, we combined them using the Particle Swarm Optimization (PSO) algorithm. The results are very interesting after we do the calculations, the algorithm that uses PSO-based K-NN gets a higher weight compared to using only the K-NN algorithm. The predicted value of the weight resulting from the PSO-based K-NN is 97.67%. while the results only use K-NN of 64.92%. The advantages of PSO can also select attributes that can affect it, namely age, diabetes, and ejection fraction. So gathering information through data mining. The PSO-Based K-NN method, which is the primary machine learning technique used in this computation, yields the greatest results in terms of accuracy for heart disease when applied to the data assets. Using the K-NN - PSO algorithm can provide promising results for predicting symptoms that cause heart disease with very good accuracy. PSO is Used to choose features and optimize k values on the K-NN dataset, after which the accuracy is output on the K-NN.
Co-Authors Andi Saryoko Atang Saepudin Desty Anggraeni Dwiantoro, Tino Euis Widanengsih, Euis Fajar Agustini Ginanjar, Syaiful Henny Destiana iman, Fadlul Ishak Komarudin Panca Saputra, Elin Priyono Priyono Rismaya, Siska Rudianto, Biktra Saputara, Elin Panca Saputro, Achmat Yulyadi sismadi, sismadi Taufik Rahman Vito Triantori