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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Indonesian Journal of Electrical Engineering and Computer Science Community Development Journal: Jurnal Pengabdian Masyarakat PAKAR Pendidikan Journal of Computer Scine and Information Technology Jurnal Ipteks Terapan : research of applied science and education Jurnal Komtekinfo
Sofika Enggari
Universitas Putra Indonesia YPTK Padang
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Journal : Journal of Computer Scine and Information Technology

 1 
Alliance Rules- based Algorithm on Detecting Duplicate Entry Email Arif Hanafi; Sulaiman Harun; Sofika Enggari; Larissa Navia Rani
Journal of Computer Scine and Information Technology Volume 7 Issue 3 (2021): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jcsitech.v7i2.7

Abstract

The way that email has extraordinary significance in present day business communication is certain. Consistently, a bulk of emails is sent from organizations to clients and suppliers, from representatives to their managers and starting with one colleague then onto the next. In this way there is vast of email in data warehouse. Data cleaning is an activity performed on the data sets of data warehouse to upgrade and keep up the quality and consistency of the data. This paper underlines the issues related with dirty data, detection of duplicatein email column. The paper identifies the strategy of data cleaning from adifferent point of view. It provides an algorithm to the discovery of error and duplicates entries in the data sets of existing data warehouse. The paper characterizes the alliance rules based on the concept of mathematical association rules to determine the duplicate entries in email column in data sets.
Implementation of Certainty Factor in an Expert System for Diagnosing Pests and Diseases of Tomato Plants Hafizul Fadli; Sofika Enggari; Sepsa Nur Rahman
Journal of Computer Scine and Information Technology Volume 9 Issue 3 (2023): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jcsitech.v9i3.76

Abstract

Tomatoes are a plant that is currently widely planted by farmers. Environmental factors and stable selling power are the reasons why this plant is popular with Indonesian farmers. However, that doesn't mean tomato plants don't have growth problems. Diseases such as leaf rot, fusarium wilt, bacterial wilt and leaf scorch are still the main factors inhibiting the decline in yield and quality of tomato plants in Indonesia. This is because farmers do not understand the correct diagnosis of tomato diseases. Misdiagnosis of diseases causes the use of pesticides that are not appropriate, resulting in damage or failure of tomato plants. When diagnosing tomato diseases, you need a farm advisor who can accurately diagnose tomato diseases. In this study, an expert system for diagnosing tomato plant diseases was built to determine pest and disease diagnoses and provide solutions and suggestions for existing diseases based on the selected symptoms. The method used in this expert system is certainty factor. This method was chosen because the certainty factor measures the value of a hypothesis's belief in a fact. These values are divided into two parts, namely MB and MD. The results of applying the confidence factor method to an expert system for diagnosing tomato plant diseases with examples of cases of late blight diagnosis by selecting the appropriate symptoms obtained a percentage of 97%, so it can be interpreted that the use of this method has the opportunity to solve problems in tomato plants
Poor Family Classification Decision Support System using the Simple Additive Weighting (SAW) Method Lili Amareza Patriani; Sumijan; Sofika Enggari
Journal of Computer Scine and Information Technology Volume 9 Issue 3 (2023): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jcsitech.v9i3.83

Abstract

Poverty is a problem that continues to be the focus of attention for the government. Poverty has also caused people to be willing to sacrifice anything for their survival. To anticipate this problem, various policies have been adopted by the government to break the chain of poverty. One of them is providing assistance funds to poor families (PKH). This is felt directly by all levels of underprivileged society. One of the efforts of the Koto Ranah Tapan government to eradicate poverty that occurs in Koto Ranah Tapan is to follow the central government program, namely the launch of government financial assistance (PKH). These funds will be distributed to poor residents in Koto Ranah Tapan through the nagari guardian office in Koto Ranah Tapan. However, the distribution of aid funds to poor families is often not on target due to a large level of manual calculation error which makes the aid not on target and also the office of the nagari village of high cliff village has not been able to objectively determine the families who receive the aid. To help determine which families are worthy of receiving poor family assistance funds, a decision support system is needed. With this Decision Support System (DSS), it is hoped that the decision-making process can minimize the occurrence of wrong targets that often arise in the process of selecting poor families who wish to receive aid funds . In this calculation the author uses the Simple Additive Weighting (SAW) method, because this method is suitable for accurate calculations and is very helpful in calculating any data obtained. The results obtained were that Ade Irma Suryani got the highest score with a score of 10.8 and was ranked at the top (Best 1), so she could be considered the best recipient of aid funds.
Co-Authors Agung Ramadhanu Arif Hanafi Hafizul Fadli Halifia Hendri Larissa Navia Rani Lili Amareza Patriani Lita Gusrian Mardison Mardison Muhammad Tajuddin Nabila Frisca Oktavia Rahmatul Husna Arsyah Rani Anggraini Sarjon Defit Sepsa Nur Rahman Silfia Andini Sulaiman Harun Sumijan Sumijan Sumijan Syafri Arlis