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All Journal Semantik Seminar Nasional Informatika (SEMNASIF) JURNAL MEDIA INFORMATIKA BUDIDARMA Syntax Literate: Jurnal Ilmiah Indonesia JITK (Jurnal Ilmu Pengetahuan dan Komputer) Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Teknik Informatika (JUTIF)
Fikri Budiman
Departemen Teknik Informatika, Fakultas Ilmu Komputer, Universitas Dian Nuswantoro, Indonesia
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Journal : Jurnal Teknik Informatika (JUTIF)

 1 
HYBRIDIZATION OF THE NAIVE BAYES CLASSIFICATION METHOD IN THE FRESHWATER FISH SEED SELLER CLASSIFICATION MODEL M Hafidz Ariansyah; Esmi Nur Fitri; Sri Winarno; Asih Rohmani; Fikri Budiman; Junta Zeniarja; Edi Sugiarto
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 2 (2023): JUTIF Volume 4, Number 2, April 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.2.715

Abstract

Freshwater fish seed sellers play several roles in the supply chain process in the freshwater fish farming business. The role of the seller of freshwater fish seeds in this process is to distribute fish seeds which are one of the upstream sources in the supply chain process. Freshwater fish cultivators must select competent freshwater fish seed sellers so the supply chain process can run well. A large number of freshwater fish seed sellers in the market remind freshwater fish cultivators to choose the quality of the freshwater fish seed seller in terms of seed quality, low prices, shipping that can reach many areas, ergonomic packaging, and others. This study proposes Hybrid Naïve Bayes Classifiers (HNBCs) as a machine learning method for classification. This study aimed to compare the seed seller classification method in which the appropriate pattern of seed seller was identified by hybridization of Naïve Bayes Classifiers (NBCs), and then the researchers conducted performance appraisal and evaluation. The results are beneficial for freshwater fish cultivators and researchers which will enable them to formulate their plans according to the predicted results. The proposed method has produced significant results by achieving a training data accuracy of 82.61% and the testing data accuracy of 73.91%.
DECISION TREE SIMPLIFICATION THROUGH FEATURE SELECTION APPROACH IN SELECTING FISH FEED SELLERS Esmi Nur Fitri; Sri Winarno; Fikri Budiman; Asih Rohmani; Junta Zeniarja; Edi Sugiarto
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 2 (2023): JUTIF Volume 4, Number 2, April 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.2.747

Abstract

Feed is a crucial variable because it can determine the success of fish farming. Breeders can use two types of artificial feed, namely alternative feed and pellets. Many cultivators need pellets as the main consumption for the fish they are cultivating because the pellets contain a composition that has been adjusted to their needs based on the type and age of the fish. However, currently, cultivators are facing a problem, namely the high price of fish pellets on the market. Therefore, an analysis of the classification of the selection of fish feed sellers is needed that is adjusted to several criteria like the number of types of feed, price, order, delivery, and availability of discounts. This study conducted a classification analysis of simplification of characteristics in selecting fish feed sellers in Kendal Regency that would then be compared with a model without feature selection by utilizing the Decision Tree C4.5 method. The results of this study are the decision tree with the best performance where C4.5 with the application of the selected feature has an accuracy value of 92%, while C4.5 without the selection feature has an accuracy of 86.8%. The results of this study indicate that the C4.5 method with the application of selection features is better than C4.5 without selection features so that it can be applied to the selection of freshwater fish feed sellers in Kendal Regency.
Co-Authors Ahmad Zainul Fanani Ajib Susanto Ari Yahya A Arry Maulana Syarif Asih Rohmani Asih Rohmani Asih Rohmani Defri Kurniawan Edi Sugiarto Edi Sugiarto Edi Sugiarto Edi Sugiarto Elkaf Rahmawan Pramudya Esmi Nur Fitri Esmi Nur Fitri Junta Zeniarja Khafiidz Hastuti Linda Marlinda M Hafidz Ariansyah Moch Arief Soeleman Muhammad Rafi Haqqi Ramadhan Muslih Muslih Ruri Suko Basuki S Nurhendratno Slamet Sudaryanto N Sri Winarno Widyatmoko Karis Yosiko Aditya Pratama