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All Journal Voice Of Informatics IT (INFORMATIC TECHNIQUE) JOURNAL Innovation in Research of Informatics (INNOVATICS) Informatics and Digital Expert (INDEX) JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Jurnal Pendidikan dan Pembelajaran Indonesia (JPPI) Academic Journal of Computer Science Research (AJCSR) Journal of Artificial Intelligence and Digital Business Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS IPSIKOM PUBLIDIMAS CSRID Jurnal Pengabdian Masyarakat (JURDIMAS) JPPkM: Jurnal Pengabdian dan Pemberdayaan kepada Masyarakat Jurnal Simki Economic
N. Nelis Febriani SM
Universitas Cipasung Tasikmalaya
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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 1 
Analisis Sentimen Pengguna Twitter Terhadap Vaksin Sinovac (Covid-19) Dengan Menggunakan Metode Naïve Bayes Evi Dewi Sri Mulyani; Teuku Mufizar; N. Nelis Febriani SM; Hendri Julian Pramana; Intan Hartiwan
Computer Science Research and Its Development Journal Vol. 15 No. 1: February 2023
Publisher : LPPM Universitas Potensi Utama

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Abstract

In 2020 Indonesia became one of the countries affected by this corona virus. The government has made various efforts to suppress the spread of the corona virus, one of which is by taking vaccinations. The existence of this vaccination, of course, received a response from the community. Many opinions that appear ranging from hopes to worries. One of the forums where the public can express themselves is through the social network Twitter. In the process of processing public opinion data from Twitter social media, a preprocessing process is needed which can then be classified. The method used to analyze public opinion on Covid-19 vaccination is Naive Bayes. The results of the analysis of public sentiment on the Sinovac vaccine using the Naive Bayes method on Twitter showed that of the 1,139 tweet data, 82% were positive and 18% were negative, so it can be concluded that public sentiment tends to be positive. With accuracy or model testing with Confusion Matrix and K Fold Validation, data accuracy is 80%.
SISTEM PAKAR DIAGNOSA PENYAKIT PADA SAPI BERBASIS WEB MENGGUNAKAN METODE FORWARD CHAINING Evi Dewi Sri Mulyani; N Nelis Febriani SM; Teuku Mufizar; Shinta Siti Sundari; Cepi Rahmat Hidayat; Gilang Muhammad Nur Alip; Kurdiman
Computer Science Research and Its Development Journal Vol. 16 No. 1 (2024): February 2024
Publisher : LPPM Universitas Potensi Utama

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Abstract

Beternak sapi merupakan bisnis yang memiliki potensi ekonomi yang sangat menjanjikan, namun tingginya permintaan daging sapi dan air susu sapi tidak disertai dengan laju pertumbuhan ternak. Selain itu, kendala yang sering dialami oleh para peternak adalah proses merawat sapi agar terhindar dari penyakit berbahaya dan menular dengan cepat yang dapat berakibat pada kematian. Untuk mencegah agar sapi tidak sakit, maka pemilik sapi harus senantiasa berkonsultasi dengan dokter hewan agar dapat dilakukan pencegahan dan pengobatan terhadap hewan sapi sedini mungkin, namun terbatasnya pakar dan tingginya biaya konsultasi menjadi kendala utama bagi para peternak. Aplikasi pakar ini dirancang sebagai solusi dari kendala yang dihadapi oleh peternak, agar para peternak dapat melakukan konsultasi mengenai penyakit sapi sehingga peternak dapat melakukan penanganan sedini mungkin dari diagnosis yang dihasilkan. Dengan menggunakan metode Forward Chaining, proses pengumpulan fakta dimulai dari gejala yang ditemukan sampai menghasilkan diagnosis sebagai konklusinya dan dengan metode Certainty Factor, hasil diagnosis tersebut diberi nilai persentase atau tingkat keyakinannya
Analisis Sentimen Pengguna Twitter Terhadap Vaksin Sinovac (Covid-19) Dengan Menggunakan Metode Naïve Bayes Evi Dewi Sri Mulyani; Mufizar, Teuku; SM, N. Nelis Febriani; Pramana, Hendri Julian; Hartiwan, Intan
CSRID (Computer Science Research and Its Development Journal) Vol. 15 No. 1: February 2023
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.15.1.2023.12-21

Abstract

In 2020 Indonesia became one of the countries affected by this corona virus. The government has made various efforts to suppress the spread of the corona virus, one of which is by taking vaccinations. The existence of this vaccination, of course, received a response from the community. Many opinions that appear ranging from hopes to worries. One of the forums where the public can express themselves is through the social network Twitter. In the process of processing public opinion data from Twitter social media, a preprocessing process is needed which can then be classified. The method used to analyze public opinion on Covid-19 vaccination is Naive Bayes. The results of the analysis of public sentiment on the Sinovac vaccine using the Naive Bayes method on Twitter showed that of the 1,139 tweet data, 82% were positive and 18% were negative, so it can be concluded that public sentiment tends to be positive. With accuracy or model testing with Confusion Matrix and K Fold Validation, data accuracy is 80%.
SISTEM PAKAR DIAGNOSA PENYAKIT PADA SAPI BERBASIS WEB MENGGUNAKAN METODE FORWARD CHAINING Evi Dewi Sri Mulyani; N Nelis Febriani SM; Teuku Mufizar; Shinta Siti Sundari; Cepi Rahmat Hidayat; Gilang Muhammad Nur Alip; Kurdiman
CSRID (Computer Science Research and Its Development Journal) Vol. 16 No. 1 (2024): February 2024
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.16.1.2024.35-44

Abstract

Beternak sapi merupakan bisnis yang memiliki potensi ekonomi yang sangat menjanjikan, namun tingginya permintaan daging sapi dan air susu sapi tidak disertai dengan laju pertumbuhan ternak. Selain itu, kendala yang sering dialami oleh para peternak adalah proses merawat sapi agar terhindar dari penyakit berbahaya dan menular dengan cepat yang dapat berakibat pada kematian. Untuk mencegah agar sapi tidak sakit, maka pemilik sapi harus senantiasa berkonsultasi dengan dokter hewan agar dapat dilakukan pencegahan dan pengobatan terhadap hewan sapi sedini mungkin, namun terbatasnya pakar dan tingginya biaya konsultasi menjadi kendala utama bagi para peternak. Aplikasi pakar ini dirancang sebagai solusi dari kendala yang dihadapi oleh peternak, agar para peternak dapat melakukan konsultasi mengenai penyakit sapi sehingga peternak dapat melakukan penanganan sedini mungkin dari diagnosis yang dihasilkan. Dengan menggunakan metode Forward Chaining, proses pengumpulan fakta dimulai dari gejala yang ditemukan sampai menghasilkan diagnosis sebagai konklusinya dan dengan metode Certainty Factor, hasil diagnosis tersebut diberi nilai persentase atau tingkat keyakinannya
Sistem Pakar Deteksi Dini Penyakit Sepsis Neonatal pada Bayi Baru Lahir menggunakan Metode Certainty Factor dan Forward Chaining N Nelis Febriani SM; Dede Rizal Nursamsi; Mutia Maharani; Dwi Junior
CSRID (Computer Science Research and Its Development Journal) Vol. 18 No. 1 (2026): Februari 2026
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.18.1.2026.98-112

Abstract

Neonatal sepsis is a condition caused by bacterial infection in infants during the neonatal period and is one of the leading causes of newborn mortality in many countries around the world, including Indonesia. Indonesia ranks fifth among Southeast Asian countries with the highest neonatal mortality rate. Most of these deaths can essentially be prevented through effective prevention, early diagnosis, and prompt treatment and care. This study aims to develop a web-based expert system application designed to perform early detection of neonatal sepsis, capable of storing and managing knowledge similar to that of a medical expert. The Certainty Factor method is used to calculate and measure the level of confidence in the diagnostic results, while the Forward Chaining method serves as the reasoning mechanism to generate conclusions based on the symptoms selected by the user. The expert system provides comprehensive information on symptoms, treatment steps, care procedures, and medical advice, thereby assisting both healthcare professionals and the public in identifying sepsis risks at an early stage. The testing results show that the expert system can provide a diagnostic confidence level of 94.77%, indicating the system’s accuracy in supporting clinical decision-making and its potential to help reduce neonatal mortality rates.
Co-Authors Aditia Abdurachman Aini Syifa, Raisa Hilia ALAM Alfin Nur Arifah Alfin Anisa Solehah Nurwendah Ardhiansyah Cepi Rahmat Hidayat Cepi Rahmat Hidayat Dani Rohpandi Dede Syahrul Anwar Depelias Setiawan, Dimas Dikdik Muhammad Siddiq Dimas Nurjaman Dwi Junior Evi Dewi Sri Mulyani Fauzan, Riswan Fithri Sri Mulyani Ghurroh Setyoningrum, Nuk Gilang Muhammad Nur Alip Hartiwan, Intan Husna Fauziah, Gita Iin Inayatul Hidayah Ina Nuraeni Intan Hartiwan Isyana Rahayu, Isyana Khairul Anwar Kholiq Mochamad Ramdan Khozizah, Putri Kiki Pitriana NA Kurdiman Kurdiman Listiani, Lina Lodana, Mae B Miftahudin muhamad husnu aminudin muhammad isnen ramdani Muhyiddin, Tazkia Normatiena Mustofa, Pramesti Melyna Mutia Maharani Nugraha, Muhammad Rizky Nuk Ghurroh Setyoningrum Nuk Ghurroh Setyoningrum Nurdin, Arif Muhamad Nursamsi , Dede Rizal Nursamsi, Dede Rizal Pepi Alpiani Pramana, Hendri Julian Putri Khozizah Rahma Putri, Widi Rahmawati, Alvi Riska Raudhatul A'naini Robby Maududy Safitri, Mila Meiliani Sarmidi Shinta Siti Sundari Sintia Yolanda Sohibudin, Roni Sri Sudiarti Tazkia Normatiena Muhyiddin Teuku Mufizar Wijaksana, Ardiansyah Windriyana Yudi Setia Rachmanda