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All Journal JUITA : Jurnal Informatika Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data) Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Sains dan Informatika : Research of Science and Informatic JURTEKSI JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Teknologi Informasi dan Pendidikan Jurnal Agrium Jurnal Informasi dan Teknologi Indonesian Journal of Electrical Engineering and Computer Science Journal of Computer Scine and Information Technology Jurnal Sains Informatika Terapan (JSIT) Jurnal Komtekinfo Jurnal Teknologi Jurnal Teknik dan teknologi tepat guna
Eva Rianti
Universitas Putra Indonesia YPTK Padang
Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Social Sciences

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Design of Expert System for Identification of Learning Modalities and Multiple Intelligences in Students with Fuzzy Logic Method Nova Fatmasari; Eva Rianti; Hari Marfalino
Journal of Computer Scine and Information Technology Volume 10 Issue 4 (2024): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jcsitech.v10i4.110

Abstract

Multiple intelligences and learning modalities possessed by each student need to be considered by teachers. Because to maximize the learning process, both of these things are needed. However, this is often ignored by teachers. The learning process that is carried out only focuses on single intelligence and learning methods that focus on paying attention to the teacher explaining the material. This method certainly causes the learning process to be less than optimal. therefore , an expert system is needed that can help teachers and students know this. The expert system that will be processed takes knowledge from the Guidance and Counseling teacher of SMAN 15 Padang using the Fuzzy Logic Tsukamoto method. This expert system is processed using the Visual Basic.Net programming language, this expert system can identify 4 types of multiple intelligences, namely linguistics, mathematical logic, music and intrapersonal and also the learning modalities possessed by each student with predetermined rules. The results of the expert system can help teachers and students in improving the learning process. With this system, it can help schools, especially Guidance and Counseling teachers, in identifying the types of learning and multiple intelligences possessed by each student. So that it can develop and provide solutions for developing student abilities.
Implementasi Computer Vision Dalam Deteksi Dan Klasifikasi Sampah Otomatis Pada Sistem Pengolahan Limbah Perkotaan Akbar Lusman; Retno Devita; Ondra Eka Putra; Eva Rianti; Fajrul Islami
Jurnal Sains Informatika Terapan Vol. 5 No. 1 (2026): Jurnal Sains Informatika Terapan (Februari, 2026)
Publisher : Riset Sinergi Indonesia (RISINDO)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62357/jsit.v5i1.956

Abstract

Waste is a very serious environmental problem commonly faced by Indonesians. According to data from the National Waste Management Information System (SIPSN), Indonesia's waste volume reached 20.02 million tons in 2022. In Indonesia, the amount of waste generated reached 65 million tons per day in 2016 and increased to 66.5 million tons in 2018. The amount of waste in Indonesia continues to increase annually. In large cities, waste management is an increasingly pressing challenge, given the negative impacts caused by improper management, such as waste accumulation in landfills (TPA), water and air pollution, and public health issues. This study aims to design and implement an automatic waste classification system based on Computer Vision technologies as a solution for urban waste management. The system utilizes an Arduino Mega 2560, camera, ultrasonic sensor, servo motor, and conveyor to detect and classify five main types of waste: plastic, paper, glass, metal, and organic materials in real time. The camera captures images of waste, which are then analyzed using a Computer Vision model, while sensors and actuators control the flow and physical sorting process. This research seeks to improve waste processing efficiency by reducing human involvement in hazardous tasks and to promote the application of intelligent technologies in supporting sustainable recycling systems and reducing the burden on final disposal sites (landfills). The system created can detect and classify waste types well.
Monte Carlo Simulation to increase the efficiency of Gas Distribution in Padang City Zulfitri Yani; Nurmaliana Pohan; Devi Gusmita; Eva Rianti
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 6 No. 2 (2023): Jurnal Teknologi dan Open Source, December 2023
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v6i2.3378

Abstract

PT. Cahaya Hermes Indo Abadi is one of the largest non-subsidized gas distributors in the city of Padang. Gas is a necessity in society. It is necessary to pay attention to the availability of gas to meet consumer needs, the state of gas stocks can affect the level of sales revenue. Sales relate to consumer desires for goods and services that they want to fulfill. Increasing the amount of gas demand can generate a large income. In predicting gas needs, a method is needed that is able to overcome society's gas needs. One of the methods used in this research is the Monte Carlo Method. This method is able to overcome further gas needs so data is needed to overcome this problem. The data used is 12 Kg non-subsidized gas sales data for three years, namely Gas Sales Data for 2021, 2022, and Gas Sales Data for 2023. The level of prediction accuracy in 2022 is 86.9% and in 2023 the accuracy is 86.6%. Based on the gas distribution simulation that has been carried out, the average is 86.75%. By obtaining a greater level of accuracy, this method is suitable for use and implementation in predicting future gas demand, making it easier for companies to make decisions in the future.
Analisis Kepuasan Pelayanan Publik Menggunakan Metode Naïve Bayes Pada Dinas Kependudukan Dan Pencatatan Sipil Kabupaten Agam Irzal Arief Wisky; Eva Rianti; Afika Syahira
Jurnal Sains Informatika Terapan Vol. 4 No. 3 (2025): Jurnal Sains Informatika Terapan (Oktober, 2025)
Publisher : Riset Sinergi Indonesia (RISINDO)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62357/jsit.v4i3.784

Abstract

This study aims to analyze public satisfaction with services provided by the Department of Population and Civil Registration (Disdukcapil) of Agam Regency using the Naïve Bayes method. The research data were collected from 252 respondents through a public satisfaction survey covering nine service indicators based on the Ministry of Administrative Reform Regulation No.16 of 2014. The Naïve Bayes algorithm was applied to classify satisfaction levels into four categories: very dissatisfied, dissatisfied, satisfied, and very satisfied. The results indicate that the developed web-based system can accurately predict public satisfaction levels, with the highest probability value of 0.1127 falling under the “very satisfied” category. These findings demonstrate that the service quality at Disdukcapil Agam Regency has been well implemented, and the application of the Naïve Bayes method is effective in supporting the evaluation and continuous improvement of public service performance.
Co-Authors Abdullah Abdullah Afika Syahira Aggy Pramana Gusman Agung Ramadhanu Akbar Lusman Bhaidawi Bhaidawi Bhaidawi, Bhaidawi Devi Gusmita Devi Gusmita Dian Maulida Dwi Febrina Barel Eka Praja Wiyata Mandala Enggari, Sofika Fajrul Islami Ferry Juliandri Pane Firna Yenila Graceae, Marsaa Noverdi Gusmita, Devi Halifia Hendri Intan Savilla Irzal Arif Wisky J, Shafa Adillah Khairul, Khairul Zaman Kurnia, Hezy Marfalino, Hari Maulida, Dian Mayang Sajida melanie, Vanesaputri Melda Agharina Muhammad Gafa Akbar Awidani Mutiana Pratiwi Nitami, Dian Nova Fatmasari Nugraha, Fariz Haris Ondra Eka Putra Pohan, Nurmaliana Pradana, Taufan Pratama, Robby Noval Purwoko, Agus Rahman, Sepsa Nur Resvi Ansiska Retno Devita Rizky, Syafrika Deni Romi Hardianto Rozizah Dwi Gusni Sarjon Defit Silfia Andini Suci Wahyuni Wifra Safitri Yesri Elva Yuhandri Yuhandri, Yuhandri Zulfitri Yani