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All Journal Sistemasi: Jurnal Sistem Informasi Techno Nusa Mandiri : Journal of Computing and Information Technology Informasi Interaktif
Heri Sismoro
Universitas AMIKOM Yogyakarta
Computer Science & IT Electrical & Electronics Engineering

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PERBANDINGAN TINGKAT USABILITY GOOGLE CLASSROOM BERDASARKAN PERSPEKTIF TEACHERS PADA PERGURUAN TINGGI Lilis Dwi Farida; Heri Sismoro
Sistemasi: Jurnal Sistem Informasi Vol 9, No 1 (2020): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (792.113 KB) | DOI: 10.32520/stmsi.v9i1.575

Abstract

E-Learning merupakan aplikasi teknologi informasi yang berbasis elektronik melalui jaringan internet yang dirancang untuk keperluan pembelajaran. Saat ini hampir semua sekolah tinggi telah memanfaatkan e-Learning dalam proses pembelajaran. Google merupakan perusahaan besar yang menawarkan fasilitas Google for Education, dengan salah satu produknya adalah google classroom. Google classroom dapat membantu students dan teachers untuk mengorganisasi penugasan, mendukung kolaborasi, dan membantu komunikasi yang lebih baik. Ketersediaan google classroom pada sisi students dan teachers belum sepenuhnya membuat aplikasi digunakan. Penerimaan students dianggap tidak memiliki pengaruh yang signifikan. Sementara itu, performa memiliki pengaruh terhadap tingkat penerimaan. Penelitian ini bertujuan untuk mengukur tingkat usability penggunaan google classroom di lingkungan Perguruan Tinggi melalui perspektif teacher pada Universitas XYZ. Penggunaan google classroom diimplementasikan melalui website desktop dan aplikasi mobile. Hasil pengukuran menunjukkan bahwa google classroom yang diakses melalui website desktop mendapatkan nilai 86, yang berarti acceptable, adjective range dinilai excellent, grade scale berada pada level B. Sementara yang diakses melalui aplikasi mobile mendapatkan nilai 76, dengan penerimaan acceptable, nilai adjective range adalah good, dan grade score pada level C.Kata Kunci: e-Learning, google classroom, usability.
SENTIMEN ANALISIS REVIEW PENGGUNA MARKETPLACE ONLINE MENGGUNAKAN NAÏVE BAYES CLASSIFIER Siti Rahayu; Kusrini Kusrini; Heri Sismoro
Informasi Interaktif Vol 3, No 3 (2018): Jurnal Informasi Interaktif
Publisher : Universitas Janabadra

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (323.949 KB)

Abstract

The presence of social media allows users to freely review, comment on works, public figures, products, and companies. This is why then social media now is become a great source of data, which can be collected for some analysis , according to information needed. One of them is , Social media data can be used to evaluate the fast-growing market-place website in Indonesia. This can be done by analyzing the sentiments of the users review in social media sites especially twitter. The object of this research is marketplace Online Shoope. The activity of analyzing and processing user review data can also be referred to as Sentiment analysis / opinion mining. One method of text mining that can be used to solve the problem mining issue is Naïve Bayes Classifier (NBC). NBC can be used to classify opinions into positive and negative opinions. The level of accuracy of sentiment analysis system of user review of Marketplace Online shopee by using Naïve Bayes Classifier is 78,3% , with 47 tweets are classified accurately from the total number of testing tweet as much as 60 tweets, with the amount of training data are 300 tweets.Keywords: Naïve Bayes Classifier, Sentiment Analysis, Marketplace Online
DIAGNOSE OF MENTAL ILLNESS USING FORWARD CHAINING AND CERTAINTY FACTOR Marcheilla Trecya Anindita; Yoga Pristyanto; Heri Sismoro; Atik Nurmasani; Anggit Ferdita Nugraha
Jurnal Techno Nusa Mandiri Vol 20 No 2 (2023): TECHNO Period of September 2023
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v20i2.4330

Abstract

The prevalence of mental disorders in Indonesia is increasingly significant, as seen from the 2018 Riskesdas data. Riskesdas records mental, emotional health problems (depression and anxiety) as much as 9.8%. This shows an increase when compared to the 2013 Riskesdas data of 6%. Based on these data, it can be said that many people still suffer from mental disorders. Meanwhile, the number of medical personnel, medicines and public treatment facilities for people with mental disorders is still limited. In addition, the lack of public awareness, concern and knowledge about mental health causes a lack of public interest in consulting a psychologist, so people tend to self-diagnose. One solution for self-diagnosis is to use an expert system. This study developed an expert system using the forward chaining method and certainty factor. Based on the research conducted, the results are as follows. First, the expert-based system that has been developed can help provide the results of a diagnosis that is carried out before there are complaints and will be detected early by efforts to increase awareness of the prevention of mental illness and reduce the tendency to self-diagnose. Second, applying the forward chaining method and certainty factor to this expert system can produce an accuracy rate of 95.918%. An expert has also validated these results; in this study, the expert was a psychologist at a hospital in Yogyakarta.
Co-Authors Atik Nurmasani Kusrini Kusrini LILIS DWI FARIDA Marcheilla Trecya Anindita Nugraha, Anggit Ferdita Siti Rahayu Yoga Pristyanto