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All Journal Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) Ittishal Educational Research Journal Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Pengabdian Masyarakat Teknologi dan Pendidikan (MANTAP) Journal of Information Technology, Computer Engineering and Artificial Intelligence (ITCEA)
Remawati, Dwi
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Religion Arts Humanities Automotive Engineering Computer Science & IT Economics, Econometrics & Finance Education Health Professions Languange, Linguistic, Communication & Media Mechanical Engineering Public Health Other

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Metode Naïve Bayes Untuk Prediksi Waktu Produksi Mebel di UD. Wali Barokah Kartasura Sukoharjo Jawa Tengah Abdul Dhohir Surya Kusuma, RM; Remawati, Dwi; Sandradewi, Kumaratih
Journal of Information Technology, Computer Engineering and Artificial Intelligence (ITCEA) Vol. 1 No. 1 (2024): Journal of Information Technology, Computer Engineering and Artificial Intellig
Publisher : Redtech Putra Benua

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Abstract

Wali Barokah is one of the industrial furniture craftsmen (furniture) with the main material using teak wood. The development of the times has made many furniture entrepreneurs appear, making the competition between furniture craftsmen increasingly tight. One way for customers not to be disappointed is that business voters must serve customers according to the specified time when transacting. The attributes that will be used in classifying the production time are the name of the item, the number of orders, the difficulty, the equipment, the number of workers. The method that will be used is the the method Naïve Bayes Classifier. Based on the results of the confusion matrix test on the nave Bayes method of the dataset that has been taken on the object of research, an accuracy rate of 80% is obtained or is included in the category Good. Meanwhile, Precision is 83% and Recall is 88%.
METODE K-MEANS CLUSTERING UUNTUK PEMETAAN GEDUNG OLAHRAGA RAGA BADMINTON DI SOLORAYA Prasetyo, Danar Aji; Remawati, Dwi; Nugroho, Didik
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 11, No 1 (2023): Jurnal TIKomSiN, Vol. 11, No. 1, April 2023
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v11i1.730

Abstract

There are many Badminton Sports Buildings in the Soloraya area, including Sukoharjo Regency, Boyolali Regency, Klaten Regency, Wonogiri Regency, Karanganyar Regency, Sragen and Solo. Each Badminton Gymnasium has different conditions, starting from varying rental prices, as well as the various facilities offered by each Badminton Sports Hall. The purpose of this research is to help people in Soloraya find suitable badminton sports halls, an information system is needed that can explain the mapping of badminton sports halls in Soloraya. This study uses the K-Means and GIS methods to solve the problem of grouping badminton sports halls based on their categories. The result of this research is a geographic mapping information system to make it easier for people to find badminton courts that match the criteria of people in Soloraya.
SISTEM PAKAR DIAGNOSA PENYAKIT JAMUR (CRAYFISH PLAGUE) PADA LOBSTER AIR TAWAR MENGGUNAKAN METODE CERTAINTY FACTOR BERBASIS WEB Pratiwi, Vivi Dian; Nugroho, Didik; Fitriasih, Sri Hariyati; Remawati, Dwi
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 13, No 2 (2025): Jurnal Tikomsin, Vol 13, No.2, Oktober 2025
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v13i2.1018

Abstract

Crayfish plague, caused by the oomycete Aphanomyces astaci, is a deadly disease in crayfish/freshwater lobsters and poses a threat to lobster cultivation and sustainability. This study designed a web-based expert system to diagnose fungal disease (crayfish plague) in freshwater lobsters using the Certainty Factor (CF) method. Knowledge was gathered from observations at lobster farms and expert interviews. Seven symptoms were used and compiled as a rule base. The system was implemented using PHP and MySQL. The inference mechanism used a combination of expert and user CF, along with functional (black-box) and validity testing. The results showed a combined CF value for fungal diagnosis reached 0.9369 for the observed symptom combination. Seven scenarios tested yielded a 6/7 (85.7%) agreement. The expert system using the CF method is suitable for use as an early diagnosis tool for fungal diseases in freshwater lobsters, especially in local cultivation.
Co-Authors Abdul Dhohir Surya Kusuma, RM Ady Prabowo, Iwan Ahyar, Khoirul Didik Nugroho, Didik Effendi, Rohmat Irvan Febrianto, R Arie Fitriani, Putri Asiska Nur Haqiqi, Arif Naofal Kustanto, Kustanto Lestari, Zannuba Anugrah Indah Mujirahayu Meyliana, Nirma paulus harsadi Prasetyo, Danar Aji Pratiwi, Vivi Dian Putri Pertiwi, Ina Raharja, Bayu Dwi Restu Utami, Widya Retno Tri Vulandari Retno Wahyu Utami, Yustina Sandradewi, Kumaratih Septiana, Anisa Dwi Sri Hariyati Fitriasih, Sri Hariyati Tri Irawati, Tri Widada, Bebas Widianto, Septian Cahyo Wijayanto, Hendro Yustina Retno Wahyu Utami