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All Journal Informatika Jurnal Sistim Informasi dan Teknologi Jurnal Informasi dan Teknologi Jurnal Sistem Informasi dan Sistem Komputer Jurnal Pustaka Data : Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer Jurnal Sistim Informasi dan Teknologi Internet of Things and Artificial Intelligence Journal Bhandar: Harvesting Community Service in Asia
Manurung, Kiki Hariani
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Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering Social Sciences Other

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Simulasi Pengadaan Barang Menggunakan Metode Monte Carlo Manurung, Kiki Hariani; Santony, Julius
Jurnal Sistim Informasi dan Teknologi 2019, Vol. 1, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (431.087 KB) | DOI: 10.35134/jsisfotek.v1i3.3

Abstract

Inventory is a very important aspect for the development of a company. Inventory management is needed to determine the inventory of goods needed within a certain period so that market demand can be fulfilled. The data used in this study are inventory data 2016. Data processing in this study uses the Monte Carlo algorithm to predict procurement data. In accelerating data processing, this research applies a Web-based program with the PHP (Hypertext Processor) programming language. The results of testing this method are to obtain predictions of the supply of goods in a certain period of time with the right level of accuracy. From the test results obtained the level of accuracy in predicting inventory stock by 93% so that it can help companies in making decisions in the future.
Sistim Pakar Konseling Mata Pelajaran Pilihan UNBK Menggunakan Metode Forward Chaining Kiki Hariani Manurung; Julius Santony
Jurnal Sistim Informasi dan Teknologi 2019, Vol. 1, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (529.124 KB) | DOI: 10.37034/jsisfotek.v1i3.2

Abstract

The choice of computer-based national exams is a choice of a student that must be adjusted to his interests and talents, so in this case the selection of majors is very important for the future of a student who will continue his studies to college. But in reality the decisions taken in choosing majors often cause problems, because the majors taken only follow the choice of friends or on the basis of coercion from parents. Causing the large number of students who feel out of line with expectations or abilities and want to change majors. For this reason, an expert system has been made that can make it easy for students to consult early to determine elective subjects for computer-based national examinations. The method used in making this expert system is the Forward Chaining method to determine conclusions. The process of this application is to receive input in the form of types of problems experienced by students. The result of the application is that it can provide early instructions for subjects that match the talents and interests of students. With the application of the forward chaining method that is applied to the system that is governed by the rule type problem. From the accuracy of 89.29%, the system can be said to be good enough to be implemented.
Sistem Pakar Diagnosa Gaya Belajar Mahasiswa Menggunakan Metode Forward Chaining Sapriadi, Sopi; Eko Syaputra, Aldo; Septi Eirlangga, Yofhanda; Manurung, Kiki Hariani; Hayati, Nova
Jurnal Informasi dan Teknologi 2023, Vol. 5, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.v5i3.381

Abstract

Sistem pakar merupakan bagian dari pemanfaatan teknologi sehingga menjadi salah satu upaya dalam mendukung berbagai aktivitas manusia. Salah satu cara di mana sistem pakar dimanfaatkan adalah dlam konteks pendidikan. Gaya belajar adalah kecendrungan individu untuk menambil pendekatan khusus dalam proses pembelajarannya, dengan tujuan memastikan bahwa mereka bertanggung jawab dlam menemukan metode belajar yang cocok baik untuk lingkungan perkuliahan maupun materi kuliah yang harus dipelajari. Terdiri dari tia tipe gaya belajar, yakni visual, auditori, dan kinestetik. Walaupun tiap individu dapat mengunakan ketiga modalitas ini tergantung paa situasi, tetap terdapat kecendrungan yang lebih dominan pada salah satu diantaranya. Sehingga dosen harus membuat pembelajaran seefektif mungkin untuk meningkatkan pembelajaran yang seefesien mungkin. Penelitian ini bertujuan untuk melihat kemampuan mahasiswa dalam pemahaman gaya belajar dan pemahaman mahasiswa dalam proses belajar. Oleh karena itu, penelitian ini juga dapat berkontribusi dalam membatu Universitas Adzkia dalam mengambil keputusan yang sesuai untuk meningkatkan mutu pembelajaran di masa mendatang. . Untuk mengatasi sejumlah tantangan yang telah dijelaskan di atas, diperlukan penerapan sistem pakar yang mampu mengambil keputusan sebagaimana yang dilakukan oleh para ahli. Dalam konteks sistem pakar ini yang digunakan adalah metode forward chaining. Metode ini melibatkan pelacakan ke depan, dimulai dari fakta-fakta yang ada hingga mencapai kesimpulan. Dengan pendekatan ini, tujuan akurasi dapat dicapai. Hasil dari hal ini adalah dapat mendeteksi gaya belajar dengan tingkat kesamaan dikategorikan 90%.
Aplikasi Simulasi Prediksi Pemakaian Obat Kronis Dengan Metode Monte Carlo Rahmad Mulia, Jefri; Afif, Ahmad; Manurung, Kiki Hariani
Jurnal Sistem Informasi dan Sistem Komputer Vol 10 No 1 (2025): Vol 10 No 1 - 2025
Publisher : STIMIK Bina Bangsa Kendari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51717/simkom.v10i1.734

Abstract

Rumah Sakit Islam (RSI) Siti Rahmah Padang merupakan rumah sakit swasta yang memberikan pelayanan kesehatan, khususnya dalam pengelolaan penyakit kronis seperti diabetes, hipertensi, dan penyakit jantung. Penyakit kronis memerlukan pengelolaan yang sistematis, terutama dalam penggunaan obat, untuk mencegah komplikasi serius dan memaksimalkan efektivitas terapi. Metode Monte Carlo, sebagai pendekatan probabilistik, menawarkan simulasi berbasis angka acak untuk mengeksplorasi berbagai skenario pengobatan. Dengan mengimplementasikan metode ini dalam aplikasi simulasi, pasien dan tenaga kesehatan dapat memperoleh wawasan yang lebih baik terkait pengelolaan obat kronis, termasuk prediksi efektivitas obat, kepatuhan pasien, serta risiko efek samping. Penelitian ini bertujuan untuk mengembangkan aplikasi simulasi berbasis metode Monte Carlo guna membantu apoteker rumah sakit dalam proses pengolahan data, memperkirakan kebutuhan obat, dan meminimalkan kesalahan persediaan. Hasil simulasi menunjukkan bahwa pendekatan ini mampu memberikan informasi yang akurat dan efisien untuk mendukung pengambilan keputusan berbasis data. Selain itu, simulasi ini juga memungkinkan optimalisasi strategi pengelolaan stok obat.
Integrasi Model Pembelajaran Mesin dalam Game Menggunakan Gerakan Tangan Hendra, Yomei; Sakinah, Putri; Maulana, Fajar; Manurung, Kiki Hariani
Jurnal Informatika Vol 12, No 3: INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i3.6826

Abstract

This study develops a Tetris game controlled through hand gestures using a machine learning model. The primary objective of this research is to create an interactive and responsive gaming experience by utilizing hand gesture detection as the main control mechanism. A hand gesture dataset was collected from videos segmented into individual frames, which were then analyzed using MediaPipe to detect and label gestures. The machine learning model employs a Convolutional Neural Network (CNN) trained to recognize hand gesture patterns and translate them into commands within the game. After implementation, an evaluation was conducted by distributing questionnaires to 18 Informatics students at Adzkia University to assess the system's comfort and responsiveness. The questionnaire results showed a high satisfaction level, with an average score of 84.56, covering evaluations of control ease, gesture detection accuracy, and system responsiveness. The average score for ease of use reached 85, indicating that the majority of users found the gesture-based controls comfortable. This study demonstrates that applying machine learning models in gesture-based control games can provide a more interactive and responsive experience, with potential applications in other interactive technologies.
Rancang Bangun Sistem Informasi Berbasis Web untuk Prediksi Stok Obat Kronis pada Penderita Diabetes Melitus Rahmad Mulia, Jefri; Maulana, Fajar; Afif, Ahmad; Manurung, Kiki Hariani; Wendra, Yumai
Jurnal Pustaka Data (Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer) Vol 5 No 1 (2025): Jurnal Pustaka Data (Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitekt
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakadata.v5i1.1021

Abstract

Pengelolaan persediaan obat yang efektif merupakan aspek penting dalam pelayanan kesehatan, terutama untuk penyakit kronis seperti Diabetes Melitus yang membutuhkan ketersediaan obat secara berkelanjutan. Penelitian ini bertujuan untuk merancang sistem informasi berbasis web yang dapat memprediksi kebutuhan stok obat kronis bagi penderita Diabetes Melitus dengan menggunakan metode simulasi Monte Carlo. Sistem ini dikembangkan untuk membantu pihak manajemen rumah sakit dalam melakukan perencanaan pengadaan obat secara lebih efisien dan akurat. Metode penelitian meliputi analisis kebutuhan sistem, pemodelan dengan Unified Modeling Language (UML), dan pembangunan prototipe sistem berbasis web. Data pemakaian obat tahun 2021 hingga 2023 digunakan sebagai dasar perhitungan distribusi probabilitas dan simulasi Monte Carlo.Hasil dari penelitian ini berupa prototipe sistem yang mampu menghitung estimasi kebutuhan obat kronis untuk periode tertentu. Sistem ini tidak hanya meningkatkan efisiensi pengelolaan logistik farmasi, tetapi juga mendukung pengembangan infrastruktur e-health di Indonesia. Sistem dapat dikembangkan lebih lanjut untuk digunakan pada jenis penyakit kronis lainnya.
Decision Support System For Student Activity Unit Selection Using Certainty Factor Method Manurung, Kiki Hariani; Hayati, Nova; Shofia, Alima; Syaputra, Aldo Eko
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 3 (2024): Volume 4 Issue 3, 2024 [August]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i3.794

Abstract

In various fields, including the selection of Student Activity Units on campus, Decision Support Systems (DSS) have become an important tool to assist the decision-making process. SPK provides information and analysis that is structured and easy to understand, thereby helping decision-makers to choose SMEs that best suit their interests, talents, and goals. Choosing the right Student Activity Units for students can contribute to the development of their personal qualities and help develop a variety of social and professional skills. Using the Certainty Factor method in creating a Decision Support System to assist students in choosing Student Activity Units that are most relevant to their desired interests and talents. The Certainty Factor method is an artificial intelligence technique that can overcome uncertainty in data and provide a level of confidence in every decision. Based on trials carried out on several interest and talent characteristics using the Certainty Factor method, percentage results were obtained with a confidence level of 80.26%. Based on the test results, it can be concluded that the expert system created can make it easier to determine talent interests that match student desires.
OPTIMIZING LEARNING WITH TECHNOLOGY: ONLINE ATTENDANCE, AI, AND GESCHOOL AT MAN 2 PAYAKUMBUH THROUGH THE LOVE-BASED CURRICULUM (KBC) APPROACH Yulastri, Weni; Zulfa, Zulfa; Hidayat, Hafiz; Hayati, Nova; Manurung, Kiki Hariani; Erlina, Erlina; Kaksim, Kaksim
Bhandar: Harvesting Community Service in Asia Vol 2, No 1 (2025): Bhandar: Harvesting Community Service in Asia
Publisher : Bhandar: Harvesting Community Service in Asia

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

Abstract

Educational transformation in the digital era demands the integration of technology into the teaching and learning process. This article describes a community service activity at MAN 2 Payakumbuh, which implemented three technological components—online attendance, artificial intelligence (AI), and the Geschool learning platform—using the Love-Based Curriculum (KBC) approach. This activity aimed to improve the effectiveness, efficiency, and humanization of the learning process. The Community Service method used was a participatory and collaborative approach with the school for two months. These activities included: a. Teacher workshops on the use of online attendance applications and Geschool. b. Training on AI Education Tools such as ChatGPT, Canva AI, and AI for creating teaching materials. c. Introduction and mentoring for the implementation of KBC, through character development based on the values of love, empathy, and spirituality in learning. An evaluation of this activity was also conducted. The results showed that the synergy between technology and the values of compassion in education had a positive impact on student learning motivation, teacher engagement, and improved classroom management.
Co-Authors Ahmad Afif Aldo Eko Syaputra Alima Shofia Erlina Erlina Hafiz Hidayat Hayati, Nova Hendra, Yomei Jefri Rahmad Mulia Julius Santony Julius Santony Kaksim Maulana, Fajar Rahmad Mulia, Jefri SAKINAH, PUTRI Sopi Sapriadi Wendra, Yumai Weni Yulastri Yofhanda Septi Eirlangga Zulfa Zulfa