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All Journal JOIV : International Journal on Informatics Visualization Indonesian Journal of Electrical Engineering and Computer Science Journal of Applied Data Sciences Journal of Computer Scine and Information Technology
Enggari, Sofika
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology

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Journal : Journal of Computer Scine and Information Technology

 1 
Evaluation of New Employee Selection using the Multi Factor Evaluation Process Method Marissa, Dian; Enggari, Sofika; Guswandi, Dodi
Journal of Computer Scine and Information Technology Volume 10 Issue 1 (2024): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jcsitech.v10i1.96

Abstract

The process of accepting and selecting prospective employees is the earliest process for a company to get quality employees that the company or agency needs. Companies must have criteria for the employees they want. On CV. Adtuil Photocopying in recruiting employees is still less efficient, namely prospective employees still send application files to the company or via expedition delivery. So HRD will have difficulty in selecting prospective employees because they have to record and double-check incoming application files as well as the process of determining the right criteria . Solutions used to overcome problems on CV. Adtuil uses a decision support system for selecting new employees, using the Multi Factor Evaluation Process (MFEP) method. This method is quantitative which uses a weighting system in decision making. Application design using the Vb programming language. Net and MySQL databases that can manage data quickly and accurately. The results of this research show that there were 3 employees who received 10 alternative data, namely A1, A5, A9 with scores > 75. After using this decision support system it can help CV. Adtuil Photocopy in determining employee acceptance precisely, quickly and accurately
Implementation of the Topsis and AHP Methods in the Decision Support System for Determining the Best Employees Putri, Yolan Ananda; Sumijan; Enggari, Sofika
Journal of Computer Scine and Information Technology Volume 10 Issue 2 (2024): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jcsitech.v10i2.103

Abstract

Every company or agency needs Human Resources (HR) in the form of employees who have competence and good performance. Employees are one of the most important assets owned by a company. The West Sumatra Province Transportation Service is the organizer of government affairs in the field of transportation or transportation policy for the West Sumatra Province region where the selection of the best employees is still not optimal using Microsoft Excel. The aim of designing a new system at the Provincial Transportation Service is to create optimization in the assessment of each employee to facilitate the recapitulation of employee data. The data is analyzed and processed according to the research framework, namely using a Decision Support System, especially the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Analytic Hierarchy Process (AHP) methods. In this research, 10 alternative employees were taken to be assessed. Based on formula calculations using the AHP method, it is used to determine the weighted value of each existing criterion, then the resulting values from the weighting are used to carry out rankings using the TOPSIS method. After carrying out calculations using these 2 methods, the result was that the best employee was alternative 9 in the name of Rusdi with a value of 0.9995. So with this calculation the results can show which employees have the right to be the best employees in that agency
Implementation of Certainty Factor in an Expert System for Diagnosing Pests and Diseases of Tomato Plants Fadli, Hafizul; Enggari, Sofika; Rahman, Sepsa Nur
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 Patriani, Lili Amareza; Sumijan; Enggari, Sofika
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 Devita, Retno Dodi Guswandi Fadli, Hafizul Febri Hadi Halifia Hendri Hanna Pratiwi, Hanna Hendri, Hallifia Majid, Mazlina Abdul Marissa, Dian Patriani, Lili Amareza Putri, Yolan Ananda Rahman, Sepsa Nur Ramadhanu, Agung Ramadhanu, Agung Rani, Larissa Navia Rianti, Eva Silfia Andini, Silfia Skylab, Deny Sumijan