Analysis Method Analitycal Hierarchy Process (AHP) in Taking Decisions on Giving Rewards (Bonuses) Based on Employee Performance

This company is a company engaged in the field of umggas farming, which annually provides rewards (bonuses) to employees who have positive personalities such as being diligent, like being responsible, ambitious in working with the aim of making employees more creative and innovative and maintaining employee performance. In general, rewards are divided into two types, namely extrinsic rewards, which are employees who get rewards (bonuses) in the form of external or tangible rewards, for example money, bonuses, facilities, while intrinsic rewards are employees who get rewards (bonuses) in the form of rewards in the form of heart satisfaction, praise. and awards

Decision Support System for Eligibility Determination of Working Contract Extensions in ISS Indonesia using SAW Method (Simple Additive Weighting)

Decision Support System (SPK) to determine the eligibility of a work contract extension at PT. ISS Indonesia is very much needed as a consideration before establishing or extending employment contracts for employees, especially in the Cleaning Service Department. Making this decision support system aims to help PT. ISS Indonesia to determine the feasibility of working contract extensions for its employees, especially in the Cleaning Service Department. The method used in completing this research is SAW (Simple Additive Weighting), which is often known as the weighted addition method. The simple additive weighting method is one of the solutions to problems in decision support systems that require the normalization process of the decision matrix (X) to a scale that is obtained compared to all alternative ratings in the SAW (Simple Additive Weighting) method. There are 6 (six) criteria as a measure for the feasibility of a work contract extension, namely the period of service, initiative, expertise, discipline, cooperation, quality of work, accompanied by the results of the implementation of this simple additive weighting method in the form of ratings against the alternatives used. The method is also implemented into an application that is built using the PHP programming language and MySQL database

Decision Support System in Employee Determination Best Using SAW Method in PT.Tri Mitra Resources

In this era of globalization, computers are needed in almost all aspects of life. Computers are tools to help process a job so that it can be easier and more efficient. A company that has core competencies in the telecommunications field that continuously strives to improve the performance of its employees in achieving its company goals, which has a solid professional team with skills, systems and experience in managing networks. This is due to companies that have not implemented a decision support system in determining the best employees in the company in a good and efficient way. Basically a Decision Support System is a further development of a computerized Management Information System that is designed in such a way as to be interactive with the wearer. Interactive with the aim of facilitating integration between various components in the decision-making process such as procedures, policies, analysis, experience and manager's insights to make better decisions. As is well known so far, companies face more problems related to human resources because managing human resources cannot be equated with machines, materials, and funds which are only technical in nature. This is a problem that is quite complicated, so that companies have difficulty in establishing policies, especially those related to human resources. The Simple Additive Weighting method can be applied in building a decision support system to determine and choose the best ISP alternative, and can help decision makers. This method involves a number of respondents, criteria, alternative choices, and preparation of a certain rating scale into a questionnaire

Decision Support System for HP Android Selection using FMADM Model (Fuzzy Multiple Attribute Decision Making) with Weight Product (WP) Method

The emergence of mobile phones with various brands and quality as well as more competitive price variations, both domestic production and foreign production, resulted in increased interest in people's purchasing power. Often people make purchases only because they are interested in the latest models or appearance and facilities without being adjusted to their needs. This often results in a mismatch between the price of goods, functions and existing facilities. Fuzzy Multiple Attribute Decision Making (FMADM) is a method that can be applied in decision making software which is used to find optimal alternatives from a number of alternatives with certain criteria

Linear Regression Analysis To Predict The Length Of Thesis Completion

Students who carry out knowledge in the undergraduate program will certainly be faced with the preparation of a thesis at the end of their study period. However, every year students still find it takes longer than the time specified in completing their thesis. This is caused by several things, such as students who are working, working hours that do not support the implementation of thesis preparation, students who already have families and other factors. This of course makes universities have to prepare special strategies in order to reduce the number of students who cannot complete their thesis on time in the future, one of which is with a decision support. This can be done by utilizing university big data. Prediction of the length of time for completion of college student thesis can be done by utilizing data mining and a simple linear regression approach. Using 1 independent variable, namely the average inhibiting factor (Working Status, Working Hours, Work Sip, Guidance Media, Status) (X1) and the number of days of thesis completion being the dependent variable (Y). After looking for the regression value of b and constant a, then the simple linear regression equation model is: Y = 280.450 + 1.650 X

Penerapan Metode Teorema Bayes Pada Sistem Pakar Untuk Mendiagnosa Penyakit Lambung

Penyakit lambung dapat dialami oleh siapapun, secara tiba-tiba lambung terasa sakit tidak menentu. Rasa sakit lambung dapat diatasi dengan minum obat. Tidak mudah mengenal sakit yang disebabkan gangguan pada lambung. Terkadang masuk angin yang berlebihan dan terus menerus dapat mengakibatkan gangguan pada lambung. Lambung merupakan organ pencernaan yang berbentuk seperti kantong dan terletak diperut kiri rongga perut di atas diafragma, terdiri dari Kardiak, Fundus, dan Pyorus. Menurut kepakaran penyakit lambung terdiri dari Penyakit Gastritis, Penyakit Dyspepsia, Penyakit GERD (Gastroesophageal Reflux Disease). Untuk diagnosa gejala sakit, melalui seorang pakar lambung akan diterapkan sistem pakar dengan metoda Theorema Bayes. Seseorang yang bukan pakar menggunakan sistem pakar untuk meningkatkan kemampuan pemecahan masalah, sedangkan seorang pakar menggunakan sistem pakar untuk knowledge assistant. Perhitungan metode Bayes dalam mendiagnosa penyakit lambung  pada sistem pakar dirancang berdasarkan algoritma Bayes yaitu perhitungan sesuai dengan gejala-gejala penyakit yang diderita seseorang. Penyakit lambung diberi kode P01, P02, P03 ; gejala penyakit diberi kode G001 s.d G027. Dari perhitungan metode Bayes diperoleh Nilai Probabilitas dengan ada tidaknya penggunaan Theorema Bayes dalam setiap range. Sistem pakar juga memberi advice pengobatan medis berdasarkan diagnosa penyakit. &nbsp

Forecasting the Number of Students in Multiple Linear Regressions

The most important element of higher education was students, therefore every university must continue to improve services in the future, and one of them was by using decision support. This case could be done by utilizing the University of Big Data. Predicting the number of prospective students in higher education was done by utilizing data mining and multiple linear regression approaches. By using 2 independent variables, namely administration costs (X1), accreditation score (X2), and the number of students who was registered each year as dependent variable (Y). For the test data, it used database for the last 13 years. By using multiple linear regression, the intercept value was sought and the coefficient of determination until the regression coefficient was obtained with the equation Y = 45.28 + -0.02.X1 + 121.58.X2, noted that if X2 was constant, the increasing of one unit was in X1 would have the effect of increasing -0.02 units on Y. Secondly, if X1 was constant, the increasing of one unit was in X2, would have the effect of increasing 121.58 units in Y. Thirdly, if X1 and X2 were equal to zero, the magnitude of Y was 45.28 units. Therefore, the proposed approach could be provided the acceptable predictive results

Implementasi Metode K-Means Clustering Dalam Pengelompokan Bibit Tanaman Kopi Arabika

The emergence of various information on good coffee seeds to be planted has prompted the Agriculture and Plantation Service to group the seeds to be recommended in coffee planting centers in the working area of Sarimunthe Village, Kec. Munte Karo District. Data mining is used to extract valuable information from a dataset and then present it in a format that is easily understood by humans with the aim of making a decision. In this study, data processing for Arabica Coffee seedlings consisted of 30 items, in the Karo Regency Agriculture sector, in preparing the seeds to be distributed to the public, the assessment was divided into 3 phases, namely coffee seeds that did not produce (Phase 0-1 Year), immature (Phase 1-2 years) and produce (Phase 2 years and above). The final result of the grouping of Arabica coffee seedlings is that there are 10 recommended items suitable for plantin

Ekplorasi Timeline : Waktu Respon Pesan Terbaik WhatSapp Group “Gurauan kita STMIK Amik”

WhatsApp merupakan salah satu aplikasi pesan instan yang banyak di gunakan saat ini. WhatsApp memungkinkan pengguna membuat grup. Sering pesan pada grup tidak terbaca dan terabaikan oleh anggota grup. Perlu dilakukan analisa waktu yang tepat sebuah pesan direspon anggota grup dengan cepat sehingga informasi dapat disampaikan dengan baik pada semua anggota. Penelitian ini melakukan explorasi WhatSapp Group “Gurauan kita STMIK Amik” untuk menentukan waktu terbaik menyampaikan pesan dengan metode timeline serta menganalisis anggota yg berjumlah 32 orang, emoji dan sentimen. Pada Analisis sentimen dari 1095 total pesan, sentimen positif 35.53% dan sentimen negatif 64.47%. Respon emoji dari anggota sebanyak 46% menggunakan pesan emoji diatas 50% dan 34% anggota menggunakan emoji dibawah 50% sedangkan 18 % anggota tidak pernah menggunakan emoji. Dalam penelitian ini dari proses timeline dapat disimpulkan waktu terbaik untuk mengirimkan pesan pada hari selasa dan jum’at pada jam 10, 13 sampai 15 siang dan jam 20 pada malam hari

Sistem Pakar untuk Identifikasi Kandungan Formalin dan Boraks pada Makanan dengan Menggunakan Metode Certainty Factor

Tujuan dari penelitian ini adalah untuk mengetahui identifikasi kandungan zat pengawet berbahaya boraks dan formalin pada makanan. Metode yang digunakan untuk mengidentifikasi kandungan zat berbahaya pada makanan dengan menggunakan Certainty Factor dengan teknik pemberian bobot pada setiap premis (gejala) hingga memperoleh persentase keyakinan untuk mengidentifikasi makanan yang mengandung formalin dan boraks. Hasil penelitian ini adalah Kandungan boraks pada makanan, dari 4 sampel makanan (100%) yaitu 4 sampel atau seluruh sampel tidak mengandung boraks dengan persentase sebesar 100%. Kandungan formalin pada makanan, dari 4 sampel makanan (100%) yaitu ada 2 sampel makanan positif mengandung formalin dengan persentase sebesar 50% dan ada 2 makanan negative mengandung formalin dengan persentase sebesar 50%. Dari hasil pemeriksaan menggunakan spektrofoto meter UV-VIS kadar formalin yang terendah terdapat pada sampel (Ikan Segar) dengan nilai 0,6631 mg/l. Kadar formalin yang tertinggi terdapat pada sampel C (Mi Bakso) dengan nilai 1,7140 mg/l