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APLIKASI PEMODELAN FUZZY PADA INDIKATOR MAKROEKONOMI PROVINSI BALI Sukarsa, I Komang Gde; Kencana, I Putu Eka N.
Prosiding Seminar Nasional MIPA 2015: PROSIDING SEMINAR NASIONAL MIPA UNDIKSHA 2015
Publisher : Prosiding Seminar Nasional MIPA

Show Abstract | Download Original | Original Source | Check in Google Scholar

Sebagian besar data indikator makroekonomi merupakan data deret waktu yang umumnya diprediksi menggunakan model runtun waktu yang dikelompokkan ke dalam kelas pemodelan stokastik atau menggunakan model-model pemulus. Penelitian ini ditujukan untuk melihat kemampuan pemodelan fuzzy yang tergolong ke dalam soft modeling pada kasus data makroekonomi Provinsi Bali pada periode tahun 1990 2013. Indikator makroekonomi yang diprediksi adalah Pendapatan Domestik Regional Bruto (PDRB), Konsumsi, Pembentukan Modal Tetap Domestik Bruto (PMTDB), dan Ekspor Neto Provinsi Bali pada periode tersebut. Kelas pemodelan fuzzy yang digunakan adalah model Fuzzy Time Series (FTS) orde satu dengan fungsi keanggotaan yang dipilih adalah fungsi keanggotaan segitiga fuzzy (fuzzy triangular number). Hasil penelitian menunjukkan model FTS memberikan tingkat keakurasian prediksi yang tinggi, terlihat dari nilai Average Forecasting Error Rate (AFER) yang rendah. Nilai-nilai AFER untuk prediksi out-of-sample dari indikator PDRB, Konsumsi, dan PMTDB masing-masing sebesar 0,20 persen; 2,15 persen; dan 1,08 persen. Komparasi model FTS dalam memprediksi PDRB dengan formula makroekonomi untuk menghitung PDRB menunjukkan model FTS mengungguli formula makroekonomi dengan nilai AFER model FTS sebesar 0,20 persen sedangkan formula makroekonomi memberikan nilai AFER sebesar 4,00 persen.Kata kunci: AFER, fuzzy modelling, fuzzy time series, model makroekonomiAbstractMost of macroeconomic indicators are time series data. In general, time series data were predicted by using time series models which are classified into stochastic model or by applying exponential model. This research aimed to elaborate the performance of fuzzy modeling which is grouped into soft modeling in predicting the macroeconomic indicators for period 1990 2013 of Bali Province. The predicted indicators were Gross Domestic Product (GDP), Consumption, Gross Domestic Investment (GDI) and Net Export of Bali Province for that period. We applied first order Fuzzy Time Series (FTS) with membership function had been chosen is Fuzzy Triangular Number (FTN). The result showed FTS model gave high prediction rate, observed from its Average Forecasting Error Rate (AFER). The values for GDP, Consumption, and GDI were 0.20 percent, 2.15 percent, and 1.08 percent, respectively. In addition, for out-of-sample forecast of GDP, FTS outperformed classical macroeconomic formula for counting it with AFER as much as 0.20 percent while the formula had 4.00 percent.Keywords: AFER, fuzzy modelling, Fuzzy Time Series, macroeconomic model

Tanggapan Pemilih PemulaTerhadap Caleg Perempuan Pada Pemilu Legislatif (PILEG) 2019 Suciptawati, Ni Luh Putu; Sukarsa, I Komang Gde; Kencana, Eka Nila
Jurnal Ilmiah Ilmu Sosial Vol 6, No 2 (2020): Jurnal Ilmiah Ilmu Sosial
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jiis.v6i2.28475

Representasi perempuan dalam legislatif sangatlah penting, keberadaan legislator perempuan diharapkan dapat meningkatkan peran perempuan dalam kebijakan publik seperti pengentasan kemiskinan, kemajuan pendidikan, dan dibidang kesehatan. Penelitian ini bertujuan untuk melihat bagaimana persepsi pemilih pemula terhadap partisipasi perempuan dalam pemilihan legislatif 2019. Data penelitian berupa data primer dengan menyebarkan kuesioner kepada 300 responden pemilih pemula di Denpasar dengan menggunakan purposive sampling. Metode analisis yang digunakan adalah regresi logistic biner. Hasil penelitian menunjukkan bahwa dari 300 responden 235 tidak setuju dengan kandidat perempuan, hanya 65 yang memilih kandidat perempuan. Faktor yang berpengaruh terhadap cara berpikir responden dalam memilih caleg adalah pendidikan dan keaktifan dalam berorganisasi.

Tinjauan Dampak Pariwisata di Kawasan Pesisir Pada Dimensi Sosial Budaya Masyarakat Komang Gde Sukarsa; Trisna Darmayanti; Eka N. Kencana
Jurnal Matematika Vol 8 No 1 (2018)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2018.v08.i01.p96

Tourism is a leading sector in developing process of many countries. For Bali, tourism contributes more than 30 percent on the formation of Bali’s Regional Domestic Product. To assure tourism at this island will run in sustainable manner, three aspects have to be considered. This research is aimed to classify the positive as well as the negative effects of socio-cultural dimension arose from tourists activities at coastal area of Badung regency of Bali. A hundred of local community leaders at North Kuta district were selected and their perception regarding effect of tourism on socio-cultural aspect were collected on June – September 2017 and analysed by using factor analysis. Three groups were identified as the positive effects i.e. (a) women empowerment as the economic agents for the family; (b) the increasing of Balinese values; and (c) the raising of community capacity building in developing culture-creative products. Viewed from the burden of cost, we found the potency of increasing the social as well as family conflicts because of different perspectives in viewing tourism.

Indikator Kesejahteraan di Provinsi Bali: Suatu Pendekatan Analisis Biplot I Komang Gde Sukarsa; I G K Gandhiadi
Jurnal Matematika Vol 10 No 1 (2020)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2020.v10.i01.p120

The goal of this reseach is to get the representation of welfare in Bali province based on the indicators represented by People Development Indexs (PDI). PDI is the indexs is a latent variable that can not be measured like measurement variable, so to measure PDI have to be measure by several indicators. In tgeneral, PDI is measured by three indicators that is a long and Healthy life as the Health Indicators, Education Indicators and decent standard of living as Economic Indicators. In Practice, Health Indicators is measured by mean expectation of life. Mean of long school and expectation of long school are measurement of Education Indicators. Whereas Economic Indicators is represented by purchasing power parity. In Staistics methods, to represent or analize multivariate variable there are many methods can be used. One of the methods is Biplot. In Biplot analysis we can represent information about row matrix and coloum matrix simultaneous. In this cases we can get information about object ( 9 districs or city in Bali) and Welfare Indicators represented by PDIsimultanous. The result of biplot analysis in this research is two dimension graphic that represent Euclid distance of object and correlation of indicators so that we can get information of the grouping of object and the characteristic variables of the certain group.

APLIKASI PEMODELAN FUZZY PADA INDIKATOR MAKROEKONOMI PROVINSI BALI I Komang Gde Sukarsa; I Putu Eka N. Kencana
Prosiding Seminar Nasional MIPA 2015: PROSIDING SEMINAR NASIONAL MIPA UNDIKSHA 2015
Publisher : Prosiding Seminar Nasional MIPA

Show Abstract | Download Original | Original Source | Check in Google Scholar

Sebagian besar data indikator makroekonomi merupakan data deret waktu yang umumnya diprediksi menggunakan model runtun waktu yang dikelompokkan ke dalam kelas pemodelan stokastik atau menggunakan model-model pemulus. Penelitian ini ditujukan untuk melihat kemampuan pemodelan fuzzy yang tergolong ke dalam soft modeling pada kasus data makroekonomi Provinsi Bali pada periode tahun 1990 2013. Indikator makroekonomi yang diprediksi adalah Pendapatan Domestik Regional Bruto (PDRB), Konsumsi, Pembentukan Modal Tetap Domestik Bruto (PMTDB), dan Ekspor Neto Provinsi Bali pada periode tersebut. Kelas pemodelan fuzzy yang digunakan adalah model Fuzzy Time Series (FTS) orde satu dengan fungsi keanggotaan yang dipilih adalah fungsi keanggotaan segitiga fuzzy (fuzzy triangular number). Hasil penelitian menunjukkan model FTS memberikan tingkat keakurasian prediksi yang tinggi, terlihat dari nilai Average Forecasting Error Rate (AFER) yang rendah. Nilai-nilai AFER untuk prediksi out-of-sample dari indikator PDRB, Konsumsi, dan PMTDB masing-masing sebesar 0,20 persen; 2,15 persen; dan 1,08 persen. Komparasi model FTS dalam memprediksi PDRB dengan formula makroekonomi untuk menghitung PDRB menunjukkan model FTS mengungguli formula makroekonomi dengan nilai AFER model FTS sebesar 0,20 persen sedangkan formula makroekonomi memberikan nilai AFER sebesar 4,00 persen.Kata kunci: AFER, fuzzy modelling, fuzzy time series, model makroekonomiAbstractMost of macroeconomic indicators are time series data. In general, time series data were predicted by using time series models which are classified into stochastic model or by applying exponential model. This research aimed to elaborate the performance of fuzzy modeling which is grouped into soft modeling in predicting the macroeconomic indicators for period 1990 2013 of Bali Province. The predicted indicators were Gross Domestic Product (GDP), Consumption, Gross Domestic Investment (GDI) and Net Export of Bali Province for that period. We applied first order Fuzzy Time Series (FTS) with membership function had been chosen is Fuzzy Triangular Number (FTN). The result showed FTS model gave high prediction rate, observed from its Average Forecasting Error Rate (AFER). The values for GDP, Consumption, and GDI were 0.20 percent, 2.15 percent, and 1.08 percent, respectively. In addition, for out-of-sample forecast of GDP, FTS outperformed classical macroeconomic formula for counting it with AFER as much as 0.20 percent while the formula had 4.00 percent.Keywords: AFER, fuzzy modelling, Fuzzy Time Series, macroeconomic model

Tanggapan Pemilih PemulaTerhadap Caleg Perempuan Pada Pemilu Legislatif (PILEG) 2019 Ni Luh Putu Suciptawati; I Komang Gde Sukarsa; Eka Nila Kencana
Jurnal Ilmiah Ilmu Sosial Vol. 6 No. 2 (2020): Jurnal Ilmiah Ilmu Sosial
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jiis.v6i2.28475

Representasi perempuan dalam legislatif sangatlah penting, keberadaan legislator perempuan diharapkan dapat meningkatkan peran perempuan dalam kebijakan publik seperti pengentasan kemiskinan, kemajuan pendidikan, dan dibidang kesehatan. Penelitian ini bertujuan untuk melihat bagaimana persepsi pemilih pemula terhadap partisipasi perempuan dalam pemilihan legislatif 2019. Data penelitian berupa data primer dengan menyebarkan kuesioner kepada 300 responden pemilih pemula di Denpasar dengan menggunakan purposive sampling. Metode analisis yang digunakan adalah regresi logistic biner. Hasil penelitian menunjukkan bahwa dari 300 responden 235 tidak setuju dengan kandidat perempuan, hanya 65 yang memilih kandidat perempuan. Faktor yang berpengaruh terhadap cara berpikir responden dalam memilih caleg adalah pendidikan dan keaktifan dalam berorganisasi.

Identifikasi dan Kausalitas Dari Faktor Penyebab Perselingkuhan Di Kota Denpasar Ni Made Santiningsih; I Putu Eka Nila Kencana; I Komang Gde Sukarsa
Jurnal Matematika Vol 12 No 1 (2022)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2022.v12.i01.p144

Infidelity can have an impact on married life, some examples of which are less harmonious relationships with partners, and divorce. Infidelity is a sexual and emotional activity carried out by one or both individuals bound by a committed relationship. This study aims to determine the causative factors of infidelity and the causative factors that dominate infidelity. The method used in this research is structural equation modeling partial least square (SEM-PLS). The place where this research was conducted is in Denpasar City with a research period of October to November 2021. Data were obtained based on a questionnaire in the form of responses from married residents to the factors causing infidelity. The questionnaires were distributed as many as 130 questionnaires. This study obtained the results that the factors that cause infidelity are sexual factors, emotional factors, love factors, and social factors. Infidelity occurs dominated by emotional factors, namely the lack of attention from partners.

Penerapan Metode K-means Pada Klasterisasi Provinsi di Indonesia Berdasarkan Indikator Indeks Kebahagiaan Damayanthi, Ni Wayan Rita; Suciptawati, Ni Luh Putu; Jayanegara, Ketut; Sukarsa, I Komang Gde; Kencana, Eka N.; Wijayakusuma, I Gusti Ngurah Lanang
Jurnal Matematika Vol 14 No 1 (2024)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2024.v14.i01.p172

The happiness index is a measure that reflects individual well-being, thus playing an important role in the development of a region. The level of happiness in Indonesia is still significantly lower compared to other ASEAN countries. In relation to efforts to improve the happiness index in Indonesia, this study applies the K-means method to cluster the 34 provinces of Indonesia based on the indicators of the happiness index for the year 2021. The data used is sourced from publications by the Indonesian Central Bureau of Statistics with seven happiness index indicators and employing the Minkowski distance. The clustering results of the 34 provinces using the K-means method obtained four clusters with a cluster accuracy value of 71 percent. Cluster 1 consists of seven provinces with a fairly high average of seven attributes, cluster 2 consists of seven provinces is a cluster with a low average level of internal and external satisfaction, cluster 3 consists of four provinces with a high average of seven attributes, and cluster 4 consists of 16 provinces is a cluster with provinces with a fairly high average level of external satisfaction, but a low level of internal satisfaction.

PENDUGAAN PROPORSI RUMAH TANGGA MISKIN TINGKAT DESA DI PROVINSI BALI DENGAN METODE EMPIRICAL BEST LINEAR UNBIASED PREDICTION DAN BAYESIAN Sukarsa, I Komang Gde; Gandhiadi, I. G. K
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 15 No 2 (2021): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Kebijakan pengentasan kemiskinan pada pemerintahan presiden Ir. H. Joko Widodo dilakukan melalui empat strategi kunci yang salah satunya adalah pemberdayaan kelompok masyarakat miskin. Ketersediaan informasi mengenai kemiskinan sangatlah minim padahal untuk menerapkan strategi kebijakan tersebut seharusnya dimulai pada kelompok masyarakat terkecil yakni masyarakat desa. Guna memperoleh informasi kemiskinan pada tingkat desa, penelitian ini menerapkan metode pendugaan area kecil sebagai akibat kurang efektifnya pendugaan langsung pada area kecil. Metode pendugaan area kecil yang umum digunakan yakni metode empirical best linear unbiased prediction (EBLUP), empirical Bayes (EB), dan metode hierarchical Bayes (HB). Hasil yang diperoleh pada pendugaan area kecil pada tingkat desa di Provinsi Bali menujukkan bahwa dugaan proporsi rumah tangga miskin di tingkat desa di Provinsi Bali berada di antara 0,00423 dan 0,03910 serta nilai mean square error yang berada di antara 0,0013 dan 0,1291 diperoleh melalui metode hierarchical Bayes, kemudian untuk metode empirical Bayes diperoleh dugaan proporsi rumah tangga miskin di antara 0,00423 dan 0,03909 serta nilai mean square error di antara 0,0011 dan 0,1288 dan metode empirical best linear unbiased prediction diperoleh dugaan proporsi rumah tangga miskin berada di antara 0,00425 dan 0,03910 serta nilai mean square error di antara 0,00010 dan 0,1291. Secara umum nilai mean square error berada di kisaran yang sama. Sehingga ketiga metode pendugaan tidak dapat disimpulkan yang lebih baik satu dengan yang lainnya.

UNEMPLOYMENT RATE ESTIMATION IN BALI PROVINCE: A SMALL AREA ESTIMATION APPROACH Sukarsa, I Komang Gde; Gandhiadi, G. K.; Kencana, I Putu Eka Nila
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 1 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Good development and economic growth increase the opportunities for people in the related areas to become more prosperous so that they can become a benchmark for the country's economy. One way that can be used to measure the level of development and economic growth is through microeconomic indicators such as the unemployment rate. Detailed information on the unemployment rate will certainly be a good consideration in the formation of economic policy. The development of estimation methods up to a very small area is very well used to estimate a parameter in a small area where there is not an adequate sample for use in direct estimation. This study discusses the unemployment rate at the sub-district level in Bali Province in 2020 with the result that estimating a small area using the empirical best linear unbiased prediction method gives a smaller mean square error value than the direct estimation method. The results obtained are that East Denpasar District has the largest unemployment rate of 8.49%.

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