How to deal wiith inconsistency in AHP R

[xiaoni]

Hi. I am using AHP library of R.

I have the following inconsistencies. How can I make the inconsistencies 0.

Below is my .yaml file.

Version: 2.0
Alternatives: &alternatives
  Coins.ph Wallet:
    Functional_Suitability Bug Count: 726
    Functional_Suitability Customer Satisfaction Rate: 0.15
    Reliability Bug Count: 100
    Reliability Customer Satisfaction Rate: 0.56
  GCash - Buy Load, Pay Bills, Send Money:
    Functional_Suitability Bug Count: 2777
    Functional_Suitability Customer Satisfaction Rate: 0.11
    Reliability Bug Count: 374
    Reliability Customer Satisfaction Rate: 0.45
  PayMaya - Shop online, pay bills, buy load & more!:
    Functional_Suitability Bug Count: 1162
    Functional_Suitability Customer Satisfaction Rate: 0.14
    Reliability Bug Count: 187
    Reliability Customer Satisfaction Rate: 0.49

Goal:
  name: Select App
  author: unknown
  preferences:
    pairwise:
    - [Functional_Suitability, Reliability, 1]
  children:
    Functional_Suitability:
      preferences:
        pairwise:
        - [Functional_Suitability Bug Count, Functional_Suitability Customer Satisfaction Rate, 1]
      children:
        Functional_Suitability Bug Count:
          preferences:
            pairwiseFunction: >
              BugCountPreference <- function(a1, a2) {
                if (a1$`Functional_Suitability Bug Count` > a2$`Functional_Suitability Bug Count`) return (1/BugCountPreference(a2,a1))
                if (a2$`Functional_Suitability Bug Count` == 0) return (1/9)
                else if (a1$`Functional_Suitability Bug Count` == 0) return (9)
                else return(a1$`Functional_Suitability Bug Count`/a2$`Functional_Suitability Bug Count`)
              }
          children: *alternatives
        Functional_Suitability Customer Satisfaction Rate:
          preferences:
            pairwiseFunction: >
              CSRatePreference <- function(a1, a2) {
                if (a1$`Functional_Suitability Customer Satisfaction Rate` > a2$`Functional_Suitability Customer Satisfaction Rate`) return (CSRatePreference(a2, a1))
                ratio <- a2$`Functional_Suitability Customer Satisfaction Rate`
                if (ratio <= 0) return (1/9)
                return (ratio)
              }
          children: *alternatives
    Reliability:
      preferences:
        pairwise:
        - [Reliability Bug Count, Reliability Customer Satisfaction Rate, 1]
      children:
        Reliability Bug Count:
          preferences:
            pairwiseFunction: >
              BugCountPreference <- function(a1, a2) {
                if (a1$`Reliability Bug Count` > a2$`Reliability Bug Count`) return (1/BugCountPreference(a2,a1))
                if (a2$`Reliability Bug Count` == 0) return (1/9)
                else if (a1$`Reliability Bug Count` == 0) return (9)
                else return(a1$`Reliability Bug Count`/a2$`Reliability Bug Count`)
              }
          children: *alternatives
        Reliability Customer Satisfaction Rate:
          preferences:
            pairwiseFunction: >
              CSRatePreference <- function(a1, a2) {
                if (a1$`Reliability Customer Satisfaction Rate` > a2$`Reliability Customer Satisfaction Rate`) return (CSRatePreference(a2, a1))
                ratio <- a2$`Reliability Customer Satisfaction Rate`
                if (ratio <= 0) return (1/9)
                return (ratio)
              }
          children: *alternatives

library (yaml)
library (ahp)
appAhp <- Load(in_filename)
Calculate(appAhp)
AnalyzeTable(appAhp)

The following are the results of AnalyzeTable(appAhp):