scholarly journals PENERAPAN ALGORITMA NAÏVE BAYES PADA PENILAIAN KINERJA PEMERINTAH DESA DALAM PENGELOLAAN DANA DESA

2019 ◽  
Vol 1 (2) ◽  
pp. 15-24
Author(s):  
Muliadi Muliadi
Keyword(s):  
Performance Assessment ◽  
Performance Appraisal ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Government Performance ◽  
Fund Management ◽  
Government Budget ◽  
Bayes Method ◽  
Village Government ◽  
The Village

The purpose of this study is to classify which village government is good and bad in managing village funds in Tolitoli regency to be a reference for local government to control the performance of village government in managing village funds. The method used in this research is naïve bayes classification based on PHP programming computerization is expected to help assess village government performance in village fund management so that it is faster and more accurate in classifying village government performance. Based on the analysis of calculations that have been done, the application of the naïve Bayes method of classification in village government performance appraisal has been done against 2 (two) village with criteria used: budget amount, government budget, development budget, empowerment budget, guidance field budget, unexpected budget and remaining budget so that the final result of village government performance assessment in management village funds namely villages with the name Teluk Jaya village are declared good because they have a good likelihood value of 3.57921E ^ (- 58)> bad likelihood value of 3.39635E ^ (- 60) while the village with the name Salumpaga village is declared bad because it has a good likelihood value of 2.421E ^ (-139) <bad likelihood value 3.20355E ^ (- 83)

scholarly journals Actor Contestation in Village Fund Management

2021 ◽  
Vol 9 (3) ◽  
Author(s):  
Rizky Trisna Putri ◽  
Sofyan Sjaf ◽  
Ekawati Sri Wahyuni
Keyword(s):  
Qualitative Method ◽  
Central Government ◽  
Fund Management ◽  
Government Budget ◽  
Case Study Approach ◽  
Study Approach ◽  
Village Government ◽  
The Village ◽  
Rules Set

Village funds are sourced from the central government budget which is trasferred directly to the village government. This direct transfer takes place after Law No. 6/2014 or also known as The Village Law. This larger village fund can only be accessed by the village government if it follows the rules set by the central government so that the actor in the village will use their assets to accomodate their interests related to village fund management. This study aims to explain the contestation of actors in managing village funds in two villages. This study uses a qualitative method with a case study approach conducted in Suko Village, Probolinggo Regency and Sukadamai Village, Bogor Regency. The results of this study are the village head is the actor who plays the most role in managing village funds using symbolic asset which is the position of the village head. This asset is the strongest because it has legitimacy from the state to be able to make decisions related to the village fund management.

Klasifikasi Tahap Kematangan Pisang Ambon Berdasarkan Warna Menggunakan Naive Bayes

2018 ◽  
Vol 5 (2) ◽  
pp. 60-67 ◽  
Author(s):  
Dwi Yulianto ◽  
Retno Nugroho Whidhiasih ◽  
Maimunah Maimunah
Keyword(s):  
Naive Bayes ◽  
Fruit Production ◽  
Naïve Bayes ◽  
Primary Data ◽  
Banana Fruit ◽  
Bayes Method ◽  
Classification Image ◽  
Average Accuracy ◽  
The Government

ABSTRACT   Banana fruit is a commodity that contributes a great value to both national and international fruit production achievement. The government through the National Standardization Agency establishes standards to maintain the quality of bananas. The purpose of this Project is to classify the stages of maturity of Ambon banana base on the color index using Naïve Bayes method in accordance with the regulations of SNI 7422:2009. Naive Bayes is used as a method in the classification process by comparing the probability values generated from the variable value of each model to determine the stage of Ambon banana maturity. The data used is the primary data image of 105 pieces of Ambon banana. By using 3 models which consists of different variables obtained the same greatest average accuracy by using the 2nd model which has 9 variable values (r, g, b, v, * a, * b, entropy, energy, and homogeneity) and the 3rd model has 7 variable values (r, g, b, v , * a, entropy and homogeneity) that is 90.48%.   Keywords: banana maturity, classification, image processing     ABSTRAK   Buah pisang merupakan komoditas yang memberikan kontribusi besar terhadap angka produksi buah nasional maupun internasional. Pemerintah melalui Badan Standarisasi Nasional menetapkan standar untuk buah pisang, menjaga mutu  buah pisang. Tujuan dari penelitian ini adalah klasifikasi tahapan kematangan dari buah pisang ambon berdasarkan indeks warna menggunakan metode Naïve Bayes  sesuai dengan SNI 7422:2009. Naive bayes digunakan sebagai metode dalam proses pengklasifikasian dengan cara membandingkan nilai probabilitas yang dihasilkan dari nilai variabel penduga setiap model untuk menentukan tahap kematangan pisang ambon. Data yang digunakan adalah data primer citra pisang ambon sebanyak 105. Dengan menggunakan 3 buah model yang terdiri dari variabel penduga yang berbeda didapatkan akurasi rata-rata terbesar yang sama yaitu dengan menggunakan model ke-2 yang mempunyai 9 nilai variabel (r, g, b, v, *a, *b, entropi, energi, dan homogenitas) dan model ke-3 yang mempunyai 7 nilai variabel (r, g, b, v, *a, entropi dan homogenitas) yaitu sebesar 90.48%.   Kata Kunci : kematangan pisang,  klasifikasi, pengolahan citra

scholarly journals PENGEMBANGAN SISTEM CERDAS UNTUK PREDIKSI DAFTAR KEMBALI MAHASISWA BARU DENGAN METODE NAIVE BAYES (STUDI KASUS: UNIVERSITAS PENDIDIKAN GANESHA)

2020 ◽  
Vol 3 (1) ◽  
pp. 22-34
Author(s):  
Komang Aditya Pratama ◽  
Gede Aditra Pradnyana ◽  
I Ketut Resika Arthana
Keyword(s):  
Naive Bayes ◽  
Intelligent System ◽  
Naïve Bayes ◽  
The State ◽  
State University ◽  
Bayes Method ◽  
New Students ◽  
Computer Based ◽  
Entrance Test ◽  
Naive Bayes Method

Ganesha University of Education or Undiksha is one of the state universities in Bali, precisely in the city of Singaraja. In the admission of new students, Undiksha applies 3 admissions paths, as follows the State University National Admission Selection (SNMPTN), State University Joint Entrance Test (SBMPTN), and Independent Entrance Test (SMBJM) consisting of 2 parts namely Computer Based Test (CBT) and Interests and Talents. Each year the committees are busy with the re-registration of prospective students. In determining the number of students quota for re-registration, they are still using the manual method in form of an excel file, so they want to use a system to do the process. These problems can be overcome by using “Intelligent System for Re-Registration of New Students Prediction using the Naive Bayes Method (Case Study: Ganesha University of Education)”. The Naive Bayes method is used to determine the re-register probability of the new students so that the number of students who re-register can be determining the new students quota. In developing the system, the researcher use the CRISP-DM methodology as a standard of data mining process as well as a research method. The results of this prediction system research show that the system can predict well with the average predictive system accuracy value of 75.56%.

scholarly journals Analisis Metode K-Nearest Neighbors (K-NN) Dan Naive Bayes Dalam Memprediksi Kelulusan Mahasiswa

2021 ◽  
Vol 3 (2) ◽  
pp. 107-113
Author(s):  
Kartarina Kartarina ◽  
Ni Ketut Sriwinarti ◽  
Ni luh Putu Juniarti
Keyword(s):  
Naive Bayes ◽  
Naïve Bayes ◽  
Entry And Exit ◽  
Accuracy Rate ◽  
Bayes Method ◽  
K Nearest Neighbors ◽  
Bayes Methods ◽  
Accuracy Test ◽  
Student Graduation ◽  
Selection Of

In this research the author aims to apply the K-NN and Naive Bayes algorithms for predicting student graduation rates at Sekolah Tinggi Pariwisata (STP) Mataram, The comparison of these two methods was carried out because based on several previous studies it was found that K-NN and Naive Bayes are well-known classification methods with a good level of accuracy. But which one has a better accuracy rate than the two algorithms, that's what researchers are trying to do. The output of this application is in the form of information on the prediction of student graduation, whether to graduate on time or not on time. The selection of STP as the research location was carried out because of the imbalance between the entry and exit of students who had completed their studies. Students who enter have a large number, but students who graduate on time according to the provisions are far very small, resulting in accumulation of the high number of students in each period of graduation, so it takes the initial predictions to quickly overcome these problems. Based on the results of designing, implementing, testing, and testing the Student Graduation Prediction Application program using the K-NN and Naive Bayes Methods with the Cross Validation method, the result is an accuracy for the K-NN method of 96.18% and for the Naive Bayes method an accuracy of 91.94% with using the RapideMiner accuracy test. So based on the results of the two tests between the K-NN and Naive Bayes methods which produce the highest accuracy, namely the K-NN method with an accuracy of 96.18%. So it can be concluded that the K-NN method is more feasible to use to predict student graduation

scholarly journals ARTIKEL REKRUTMEN APARATUR DESA TERHADAP PENINGKATAN KINERJA PEMERINTAH DI DESA ANALUTUR, KECAMATAN BABAT TIMUR KABUPATEN MALUKU BARAT DAYA

2021 ◽  
Author(s):  
Yulius Luturmas
Keyword(s):  
Statistical Analysis ◽  
Confidence Level ◽  
Coefficient Of Determination ◽  
Government Performance ◽  
Structured Interviews ◽  
Literature Study ◽  
And Performance ◽  
Village Government ◽  
The Village ◽  
Recruitment Performance

ABSTRACTThe Village Government apparatus of Analutur, Southwest Maluku Regency is not excellent, and one of the influencing factors is that the Village Apparatus Recruitment is not carried out properly. By using associative research methods that link recruitment and performance. Data were collected by conducting structured interviews, observations, literature study, and distributing a list of questions to 50 respondents. then analyzed quantitatively (Product Moment Correlation Statistical Analysis). The results show that the correlation between apparatus recruitment and government performance in Analutur Village, Southwest Maluku Regency is 0.857. Based on the coefficient of determination, it is proven that recruitment contributes to performance by 62.2% and the remaining 37.8% is determined by other variables which are constant. Furthermore, a significant test was carried out using t-count at a confidence level of 0.05%. And the result is t-count of 8.888&gt; t-table 1.68, which means that the hypothesis is accepted. Keywords: Apparatus Recruitment, Performance and Village Improvement

scholarly journals OPTIMASI METODE NAIVE BAYES DENGAN FEATURE SELECTION INFORMATION GAIN UNTUK PREDIKSI KETERLAMBATAN PEMBAYARAN SPP SEKOLAH

2019 ◽  
Vol 17 (1) ◽  
pp. 1
Author(s):  
Muqorobin Muqorobin ◽  
Kusrini Kusrini ◽  
Emha Taufiq Luthfi
Keyword(s):  
Feature Selection ◽  
Naive Bayes ◽  
Information Gain ◽  
Confusion Matrix ◽  
Education Institution ◽  
Naïve Bayes ◽  
Bayes Method ◽  
Education Development ◽  
Main Requirement ◽  
Naive Bayes Method

The cost of education is one component of input that is very important in implementing education. Because costs are the main requirement in an effort to achieve educational goals. SMK Al-Islam Surakarta is a private education institution that requires students to pay school fees in the form of Education Development Donations. Educational Development Donation is a routine school fee that is conducted every month. Based on last year's TU report, many students were late in paying Education Development Donations, around 60%. This is a big problem. The purpose of this study is that researchers will build a predictive system using the Naïve Bayes method. Because the method can classify the class right or late, in the payment of school fees. Data processing was taken from the dapodik data of schools in 2017/2018 with the test dataset taking 30 records. To find out the level of accuracy, this research was conducted with the Naive Bayes Method and the Information Gain Method for feature selection. Accuracy testing is done by the Confusion Matrix method. The results showed that the highest accuracy was obtained by combining the Naive Bayes Method with the Information Gain Method obtained by 90% accuracy. 

scholarly journals SISTEM PAKAR DIAGNOSA PENYAKIT DAN HAMA PADA TANAMAN JAGUNG MENGGUNAKAN METODE NAIVE BAYES

2021 ◽  
Vol 2 (3) ◽  
pp. 390-398
Author(s):  
Bayu Bastiyan Suherman
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Preventive Measures ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Agricultural Commodities ◽  
Bayes Method ◽  
Mathematical Basis ◽  
Lack Of Information ◽  
Corn Plants

Corn is one of the leading agricultural commodities that can be used as a staple plant other than rice. Constraints faced by corn farmers include the lack of information about diseases that attack the corn plants, which causes less productivity. In this study a system was developed that can automatically detect disease that attacks corn plants so that preventive measures can be taken to prevent corn plants from dying. Expert systems are designed to solve certain problems by imitating the work of experts. In addition, this expert system also helps farmers who are experiencing problems regarding diseases and pests and their solutions without relying on an expert. The method used is the Naive Bayes method, Naive Bayes is a method used to predict probabilities and has several characteristics that are istitively in accordance with the way of thinking of an expert and accompanied by a strong mathematical basis. From the tests carried out with diagnoses obtained from the comparison between the results of expert diagnoses and the diagnosis of the system to diagnose diseases and pests in corn plants is 90%.

scholarly journals PENGELOLAAN DANA DESA BERDASARKAN PERATURAN MENTERI DALAM NEGERI NOMOR 113 TAHUN 2014 (STUDI KASUS PADA NAGORI KAHEAN KECAMATAN DOLOK BATU NANGGAR KABUPATEN SIMALUNGUN

2019 ◽  
Vol 7 (1) ◽  
pp. 79-91
Author(s):  
Helwin Effendi ◽  
Jubi Jubi ◽  
Elly Susanti ◽  
Musa Fernando Silaen
Keyword(s):  
Community Participation ◽  
Sense Of Community ◽  
Good Governance ◽  
Fund Management ◽  
Management Planning ◽  
Village Governance ◽  
Village Government ◽  
The Village ◽  
Transparency And Accountability

The results of this research can be concluaded that: 1. Lack of community participation to participate in village fund management planning, this is due to the lack of motivation of the community to participate in the deliberations. Then there was a delay in submitting a draft village regulation that had been agreed to be evaluated. 2. In the implementation, administration, reporting and accountability of village fund management in accordance with PERMENDAGRI Number 113 of 2014, it shows that the principles of participation in management, orderly and disciplined principles, principles of transparency and accountability principles have been carried out properly.The suggestion from this research is that the village government should develop a participatory concept and foster a sense of community motivation by providing education seminars on managing village funds and leading to the implementation of village governance. Then the village government should pay more attention to the applicable regulations in managing village finances in order to realize Good Governance.

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