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Herry Wahyono
Universitas Krisnadwipayana
Aerospace Engineering 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 Dentistry Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Transportation Veterinary

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Journal : Teknokris

 1 
PERANCANGAN APLIKASI PENILAIAN RUMAH TIDAK LAYAK HUNI MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING PADA KEGIATAN KEMENTERIAN PUPR Faisal Ruswanto; Herry Wahyono; Ali Khumaidi
TEKNOKRIS Vol 26 No 1 (2023): Jurnal Teknokris Edisi Juni
Publisher : Fakultas Teknik Unkris Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61488/teknokris.v26i1.244

Abstract

Determination of recipients of uninhabitable housing assistance (RTLH) is one of the problems that is of concern to the Directorate of Self-Help Housing of the Ministry of Public Works and Public Housing of the Republic of Indonesia, because the large number of data on incoming aid proposals makes it difficult to determine which beneficiaries deserve due to the limited budget. One way to determine beneficiaries is to use a decision system using the Simple Additive Weighting (SAW) method. This method will provide the value of the selected alternative preference as an indicator to determine the recipient of assistance as it can help the data processing team, stakeholders and leaders in the Directorate of Self-Help as the government which has a policy in determining the prospective recipients of the house renovation assistance objectively not subjectively. The data used was taken from data collection conducted by the field team in the Serang City area of Banten Province where the data obtained were 935 residents
ANALISIS SENTIMEN TERHADAP PILPRES 2024 BERDASARKAN OPINI DARI TWITTER MENGGUNAKAN NAÏVE BAYES DAN SVM Tamara Rosyida; Harjono Padmono putro; Herry Wahyono
TEKNOKRIS Vol 26 No 1 (2023): Jurnal Teknokris Edisi Juni
Publisher : Fakultas Teknik Unkris Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61488/teknokris.v26i1.245

Abstract

Ahead of the Presidential Election, although it will run for about two years in the future, the large number of public opinion tweets about the 2024 Presidential Election on Twitter has caused positive and negative, from the data collection can be used as material for analysis. Naïve Bayes algorithm and the Support Vector Machine aims to determine the accuracy, precision, and recall values of the classification of positive or negative tweets. The method used is a qualitative method, the data taken amounted to 1606 datasets during April and May 2022. Result of RapidMiner 9.10 Tools, SVM Algorithm gets higher results by having an accuracy value of 98.43%, precision 97.15%, and recall 99.71%, Naïve Bayes algorithm has an accuracy value of 96.63%, precision 94.30%, and recall 98.90%. Based on the results of tweets that have elements of rejection of the 2024 Presidential Election, it is hoped that the public will not be able to happen
IMPLEMENTASI SISTEM PAKAR UNTUK MENDIAGNOSA PENYAKIT GIGI MENGGUNAKAN METODE TEOREMA BAYES Fadhila Anggraini; Nur Hikmah; herry wahyono
TEKNOKRIS Vol 25 No 2 (2022): Jurnal Teknokris Edisi Desember
Publisher : Fakultas Teknik Unkris Jakarta

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Abstract

Teeth are one of the most vital organs of the human body, therefore maintaining dental health is very important. The reason why people only do dental check-ups when their teeth are sick and the lack of public awareness of themselves about dental health and the long queues that cause crowds at the dental clinic are the reasons why people are reluctant to come to the dental clinic during the pandemic which is still in existence in Indonesia. Therefore we need a system to facilitate both the handling and prevention of early symptoms of dental disease that can be done online. The method used in this study is the Bayes theorem method, where this method can calculate how often the symptoms appear. The results of the research on the implementation of an expert system for diagnosing dental disease is a website-based application that can help identify dental diseases with a percentage of 80%
ANALISIS PERBANDINGAN ALGORITMA C4.5 DAN ID3 UNTUK FAKTOR KEPUASAN KONSUMEN WARUNG ICHA STEAK & SEAFOOD Muhammad Farhan Arief; Herry wahyono; Nuke Chusna
TEKNOKRIS Vol 25 No 2 (2022): Jurnal Teknokris Edisi Desember
Publisher : Fakultas Teknik Unkris Jakarta

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Abstract

Warung Icha Steak & Seafood is an MSME type food stall business that focuses on the culinary field that sells food in the form of steak and processed food from the sea. Efforts to retain consumers are certainly not an easy thing, especially the thing that is now being faced by Icha Steak & Seafood stalls is declining the number of consumers and customers. This is a threat that is being faced by the msme because it will have an impact on revenue turnover. The purpose of this study is to find out what factors need to be improved to achieve consumer satisfaction of Warung Icha Steak & Seafood. Apply the Classification method with C4.5 and ID3 algorithms to group the most influential factors for consumer satisfaction. Perform a Comparison of both C4.5 and ID3 algorithms with the Cross Validation method. Itwas concluded that the problem of determining the consumer satisfaction factor of Warung Icha Steak & Seafood can be solved using data mining techniques, namely with the C4.5 and ID3 algorithms, resulting in the same decision tree and 6 rules and the most dominant factor is Service Friendliness (C8) with a gain value of 0.41370089. Testing the ID3 algorithm has a high level of accuracy of 98.50%, a Precision value of 98.77% and a Recall value of 99.38%
Co-Authors Ali Khumaidi Chusna, Nuke L Fadhila Anggraini Faisal Ruswanto Harjono Padmono Putro M.Ageng Laksono Mega Wahyu Rhamadani Muhammad Farhan Arief Mulyana Adi Saputra Ninuk Wiliani Nuke Chusna Nur Hikmah Tamara Rosyida