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All Journal Jurnal Sistem Informasi Kaputama (JSIK) JTIK (Jurnal Teknik Informatika Kaputama) Jurnal ICT : Information and Communication Technologies
Ramadhan, Muhammad Hari
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Library & Information Science Mechanical Engineering

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ANALISIS DAN PENERAPAN METODE MULTIFACTOR EVALUATION PROCESS (MFEP) DALAM MENENTUKAN BIBIT TANAMAN BUNCIS YANG LAYAK UNTUK DIBUDIDAYAKAN Ramadhan, Muhammad Hari; Yusfrizal, Yusfrizal
Jurnal Sistem Informasi Kaputama (JSIK) Vol. 3 No. 1 (2019): Volume 3, Nomor 1, Januari 2019
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jsik.v3i1.780

Abstract

In planting plants, especially in beans, it is very necessary to select superior plant seeds. Beans as one type of vegetable that has a fairly complete nutritional content, including among them are sources of carbon and protein. Thus beans are very important to meet the needs of vegetable protein. Beans are one type of leguminous plant that has many uses. As a vegetable ingredient, bean pods can be consumed in a young condition or consumed by seeds. In this case, especially the farmers who are still beginners must be able to choose the seeds that are superior in cultivating the beans. And by utilizing the Decision Making Concept as well as the Application of the Multifactor Evaluation Process (MFEP) Method it is possible to help the novice farmer in determining the Bean Seeds that are Worth Cultivating.
SISTEM PAKAR DIAGNOSA AWAL GANGGUAN ATTENTION DEFICIT HYPERACTIVITY DISORDER PADA ANAK DENGAN METODE CERTAINTY FACTOR Yusfrizal, Yusfrizal; Ramadhan, Muhammad Hari
JTIK (Jurnal Teknik Informatika Kaputama) Vol. 2 No. 2 (2018): Volume 2, Nomor 2, Juli 2018
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jtik.v2i2.655

Abstract

Kurangnya pengetahuan publik tentang perilaku abnormal berakibat perilaku-perilaku abnormal yang ada dan tampak sering dipahami secara keliru, bahkan tidak jarang penyandang perilaku abnormal diperlakukan secara tidak manusiawi. Bukan hanya pada orang dewasa, perilaku abnormal juga dapat dialami oleh anak-anak. Salah satu bentuk perilaku abnormal tersebut adalah Attention Deficit Hyperactivity Disorder atau gangguan pemusatan perhatian pada anak. Tujuan dari penelitian ini adalah membuat suatu aplikasi sistem pakar yang berjalan pada sistem operasi windows yang dapat mendiagnosa gangguan Attention Deficit Hyperactivity Disorder dengan memberi hasil diagnosa berdasarkan tingkat keyakinan terhadap gejala-gejala yang diderita pasien dengan metode Certainty Factor. Penerapan metode Certainty Factor dapat memperkuat diagnosis yang dihasilkan karena sistem mempunyai nilai sehingga tingkat kepastian atau tingkat keyakinan lebih akurat. Dari sistem yang dirancang dan hasil pengujian secara manual diperoleh nilai keakuratan sebesar 0,9676 atau bila dipersentasikan nilainya menjadi 96,76% untuk gejala Combine (Inatentif, Hiperactif / Implusif dan Implusif ).
Multiple Linear Regression Method in Product Stock Prediction at PT. Kartika Mandiri Abadi Armaya, Jhea; Ramadhan, Muhammad Hari
Jurnal ICT : Information and Communication Technologies Vol. 16 No. 2 (2025): October, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v16i2.280

Abstract

Inaccurate inventory management often leads to stock shortages or surpluses, which impact operational efficiency and customer satisfaction in medium-sized distribution companies such as PT. Kartika Mandiri Abadi. This study aims to develop a website-based stock prediction system using the Multiple Linear Regression (MLR) method to produce more accurate stock estimates and support managerial decision-making. The research methods included collecting historical sales and product inventory data, designing a web-based system using the Unified Modeling Language (UML) model, implementing MLR to predict inventory levels based on independent variables such as monthly sales and initial inventory, and testing the functionality and accuracy of the system. The results show that the MLR-based inventory prediction system is capable of producing more stable and consistent estimates compared to manual methods, reducing the risk of stock shortages or surpluses, and facilitating management in inventory planning and distribution scheduling. The implementation of a web-based system provides real-time access, data visualization, and structured reports that support faster and data-driven decision making. These findings emphasize the importance of integrating statistical methods with information technology to improve operational efficiency and inventory planning in distribution companies. This research also opens up opportunities for further development by incorporating external variables or hybrid approaches to improve prediction accuracy in dynamic market conditions.
Co-Authors Armaya, Jhea Pairin, Yusfrizal Bin