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Jurnal Litbang Edusaintech
Published by Lembaga LitbangMu Jawa Tengah
ISSN : 27463478     EISSN : 2746346X     DOI : https://doi.org/10.51402/jle.v1i1
Core Subject : Science, Agriculture, Engineering,
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Industrial & Manufacturing Engineering
The Jurnal Litbang Edusaintech (JLE) is an open access and peer-reviewed journal, published by LitbangMu Jawa Tengah, which is a dissemination medium for research result from scientists and engineers in many fields of Education, Science and Technology. JLE is a biannual journal. The editors welcome submissions of papers describing recent theoretical and experimental research related to: (1) Theoretical articles; (2) Empirical studies; (3) Practice-oriented papers; (4) Case studies; (5) Review of papers, books, and resources; (6) Community service and development.
Arjuna Subject : Umum - Umum
Articles 47 Documents
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PEMODELAN JUMLAH KASUS PENYAKIT KUSTA DI PROVINSI SULAWESI TENGGARA MENGGUNAKAN METODE REGRESI POISSON INVERSE GAUSSIAN : PEMODELAN JUMLAH KASUS PENYAKIT KUSTA DI PROVINSI SULAWESI TENGGARA MENGGUNAKAN METODE REGRESI POISSON INVERSE GAUSSIAN Moh Yamin Darsyah; M Nurul Ramadhan
Jurnal Litbang Edusaintech Vol. 3 No. 1 (2022): Volume 3 No 1 2022
Publisher : Litbang PWM Jawa Tengah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51402/jle.v3i1.9

Abstract

Leprosy data is census data so in its modeling, it can use Poisson regression. Leprosy data also has the potential to experience overdispersion so that in overcoming the case of overdispersion, several models are formed which are a combination of the Poisson distribution with several distributions both discrete and continuous (mixed Poisson distribution). One of them is the distribution of Poisson Inverse Gaussian (PIG) which is a mixed Poisson distribution with random effects that have the Gaussian inverse distribution. In the application of a Poisson Inverse Gaussian regression method, factors are affecting the occurrence of leprosy in Southeast Sulawesi. As for the factors namely the population density, the residents who experience health complaints and ever ambulatory care, the use of clean water, the Clean and Healthy Behavior (PHBS) Households, the health facilities, the health workers, and the economic growth from the BPS website and the Profile of the Health Office of Southeast Sulawesi Province in the PDF appendix. The results of data analysis and discussion, the Poisson Inverse Gaussian regression model are obtained with a significant variable to the model that is the percentage of population density and the percentage of clean water use. With the addition of 1 ratio to the percentage of population density will be proportional to the increase in the average number of leprosy in Southeast Sulawesi Province by 1.00177. And with the addition of 1 ratio on the percentage of the use of clean water, it would be comparable to the average increase in the number of leprosy in southeast Sulawesi province by 1.01205
PRINCIPAL COMPONENT ANALYSIS BIPLOT GLOBAL COMPETITIVENESS INDEX ASEAN COUNTRIES Pardomuan Robinson Sihombing; Lisna Sari
Jurnal Litbang Edusaintech Vol. 3 No. 1 (2022): Volume 3 No 1 2022
Publisher : Litbang PWM Jawa Tengah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51402/jle.v3i1.26

Abstract

ASEAN's global competitiveness requires institutional and ASEAN countries appear to be a formidable economic actors in protecting the economic interests and at the same time having an open economic system that indicates the readiness of ASEAN to compete with the economic strength of the entire region in the world. In this case the measurement of global competitiveness factors become important aspects of state enterprises in the face of global competition. This study was conducted to determine how competitive the ASEAN countries with Biplot method of Principal Component Analysis. Results obtained from this study is the ASEAN countries have different advantages in each of the variables related to the global competitiveness index. In addition, the diversity of which can be explained more than 70% which is 90.69% which means that Principal Component Analysis Biplot describes well the overall total.
Perbandingan Metode Naïve Bayes, Support Vector Machine Dan Decision Tree Dalam Klasifikasi Konsumsi Obat Chindy Aulia Sari; Annisa Sukmawati; Rishani Putri Aprilli; Prais Sarah Kayaningtias; Novanto Yudistira
Jurnal Litbang Edusaintech Vol. 3 No. 1 (2022): Volume 3 No 1 2022
Publisher : Litbang PWM Jawa Tengah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51402/jle.v3i1.47

Abstract

Obat adalah suatu bahan yang berisi zat-zat yang berguna untuk mencegah atau menyembuhkan suatu penyakit pada makhluk hidup sehingga terjadi perubahan secara fisiologis atau psikologis selain itu obat psikoaktif merupakan obat yang mempengaruhi mental tetapi kebanyakan obat psikoaktif disalahgunakan untuk hal-hal yang tidak penting bahkan membahayakan. Terdapat banyak jenis obat psikoaktif, diantaranya ada 18 jenis obat-obatan legal maupun ilegal yaitu alcohol, amphetamines, amyl nitrite, benzodiazepine, cannabis, chocolate, cocaine, caffeine, crack, ecstasy, heroin, ketamine, legal highs, LSD, methadone, mushrooms, nicotine and volatile substance abuse consumption. Metode penelitian yang digunakan adalah metode Algoritma Naive Bayes, SVM, dan Decision Tree yaitu untuk memprediksi kecocokan data tersebut dilihat dari hasil akurasi yang didapatkan. Semakin besar akurasi yang dihasilkan maka semakin cocok data tersebut, dan semakin kecil akurasi yang dihasilkan maka semakin tidak cocok data tersebut. Peneliti menggunakan dataset Drug Consumption dalam bentuk format file .csv. Dataset ini diambil dari UCI Data Repository. Dataset Drug Consumption mengelompokkan tipe konsumen narkoba menurut pengukuran kepribadian. Berdasarkan penelitian yang telah dilakukan, maka hasil yang didapatkan dari membandingkan algoritma naive bayes, SVM (Support Vector Machine) dan Decision Tree adalah SVM (Support Vector Machine) merupakan algoritma yang paling baik. Sehingga kesimpulan yang didapat dari penelitian ini adalah sebelum memilih algoritma sebaiknya peneliti menganalisis data yang digunakan terlebih dahulu, dan SVM (Support Vector Machine) merupakan algoritma yang paling baik diantara algoritma Naïve Bayes, dan Decision Tree pada data Drug Consumption.
Analisis Keterampilan Membaca Dongeng Siswa Sekolah Dasar serta Relevansinya dengan Pembelajaran Membaca Arum Ratnaningsih; Joko Purwanto; Maksum Akhmad Maksum
Jurnal Litbang Edusaintech Vol. 3 No. 1 (2022): Volume 3 No 1 2022
Publisher : Litbang PWM Jawa Tengah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51402/jle.v3i1.65

Abstract

Pembelajaran di sekolah dasar merupakan fondasi fundamental untuk menyampaikan penanaman materi dengan benar kepada siswa. Pembelajaran Bahasa Indonesia di sekolah dasar mengharapkan supaya siswa memiliki banyak keterampilan dalam berbahasa. Salah satunya keterampilan membaca dongeng. Tujuan dari penelitian ini adalah (1) mendeskripsikan keterampilan membaca dongeng siswa (2) mendeskripsikan relevansi keterampilan membaca dongeng siswa dengan pembelajaran membaca. Metodologi penelitian ini adalah penelitian deskriptif kualitatif. Subjek dari penelitian ini siswa kelas III SD Negeri 2 Baledono. Sedangkan objeknya adalah keterampilan membaca dongeng siswa dan relevansinya dengan pembelajaran membaca. Teknik pengumpulan data yang digunakan pada penelitian ini yaitu kuesioner, wawancara, teknik simak catat, dan studi dokumen. Teknik analisis data menggunakan model Miles and Huberman meliputi koleksi data, reduksi data, penyajian data, dan penarikan kesimpulan atau verifikasi. Hasil penelitian ini yaitu kategori baik sekali (7,4%), kategori baik (48,1%), kategori cukup (40,7%), serta kategori perlu bimbingan (3,8%). Temuan penting dalam penelitian yaitu faktor motivasi dalam diri siswa yang berpengaruh terhadap semangat belajar membaca dongeng sekolah dasar. Selain itu adalah materi pelajaran membaca dongeng dianggap masih cukup sulit dikuasai oleh siswa
Peramalan Produksi Bawang Merah Kabupaten Brebes Menggunakan Autoregressive Integrated Moving Average (ARIMA) Septi Winda Utami; Rizma Novinda Puteri; Tiani Wahyu Utami; Fatkhurokhman Fauzi
Jurnal Litbang Edusaintech Vol. 3 No. 1 (2022): Volume 3 No 1 2022
Publisher : Litbang PWM Jawa Tengah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51402/jle.v3i1.76

Abstract

Kabupaten Brebes merupakan kabupaten terluas ke-2 di Jawa Tengah. Kabupaten Brebes mempunyai sumber daya manusia (SDM) yang mampu mengembangkan potensi komoditas unggulan di Kabupaten Brebes, terutama sektor pertanian yang menjadikan bawang merah sebagai komoditas utama dan ciri khas karena menjadi sektor penyumbang pendapatan terbesar daerah di Kabupaten Brebes. Pemerintah perlu membuat target produksi untuk merumuskan kebijakan pemerintah terkait pangan dan perekonomian, salah satunya dengan melakukan peramalan. Penelitian ini menggunakan metode Autoregressive Integrated Moving Average (ARIMA) karena bersifat fleksibel (mengikuti pola data), tingkat akurasi peramalan cukup tinggi dan cocok digunakan untuk memprediksi dengan cepat, sederhana, akurat, dan murah untuk meramalkan produksi bawang merah di Kabupaten Brebes pada Tahun 2021. Hasil Penelitian ini diperoleh model ARIMA terbaik yang mampu meramalkan produksi bawang merah di Kabupaten Brebes yaitu ARIMA (0,1,1) karena memiliki nilai AIC terkecil yaitu 904,52 dengan hasil peramalan produksi bawang merah di Kabupaten Brebes pada Tahun 2021 sebesar 3.031.561 kuintal.
PERAMALAN INDEKS HARGA KONSUMEN KABUPATEN BANYUMAS DENGAN METODE SARIMA Arini Rizky Wahyuningtyas; Wahyu Putri Pratiwii; Rochdi Wasono; Tiani Wahyu Utami
Jurnal Litbang Edusaintech Vol. 3 No. 1 (2022): Volume 3 No 1 2022
Publisher : Litbang PWM Jawa Tengah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51402/jle.v3i1.77

Abstract

The CPI is used as an indicator to determine the inflation rate that can describe economic developments in a region. Uncontrolled inflation will have a direct impact on economic conditions. Therefore, it is necessary to have a method to predict the CPI so that the government can determine the right policy so that the economic condition of the community becomes more stable and improves. In this study, CPI forecasting in Banyumas Regency will be carried out using the SARIMA method. The purpose of this study is to predict the CPI in the future. This study uses CPI data from Banyumas Regency from January 2014 to August 2021 with 92 data. The results show that the SARIMA (1,1,1)(0,1,1)12 model is the right model for forecasting the CPI in Banyumass Regency. Forecasting the CPI for Banyumas Regency for the next 12 months using the SARIMA (1,1,1)(0,1,1)12 method shows a trend pattern that tends to increase or inflation will not be so high.
PENGARUH PEMBERIAN VITAMIN C DOSIS TINGGI TERHADAP KADAR TUMOR NEKROSIS FAKTOR ALFA PADA AKTIVITAS FISIK BERAT Angga Pria Sundawa; Reza Adityas
Jurnal Litbang Edusaintech Vol. 3 No. 1 (2022): Volume 3 No 1 2022
Publisher : Litbang PWM Jawa Tengah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51402/jle.v3i1.89

Abstract

Front Matters: Front Cover, Editorial Team & Table of Contents Editorial Board
Jurnal Litbang Edusaintech Vol. 3 No. 1 (2022): Volume 3 No 1 2022
Publisher : Litbang PWM Jawa Tengah

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

Abstract

PEMODELAN GEOGRAPHICALLY WEIGHTED NEGATIVE BINOMIAL REGRESSION (GWNBR) PADA KASUS MALARIA DI INDONESIA Moh Yamin Darsyah
Jurnal Litbang Edusaintech Vol. 2 No. 2 (2021): Volume 2 No 2 2021
Publisher : Litbang PWM Jawa Tengah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51402/jle.v2i2.100

Abstract

Geographically Weighted Negative Binomial Regression Modeling by Comparing Adaptive Gaussian Weighting and Adaptive Tricube in Cases of Malaria in Indonesia. Malaria was an infectious disease caused by the bite of female malaria mosquitoes (Anopheles) caused by the Plasmodium parasite that breeds in human red blood cells. Malaria is one of the biggest causes of death in Indonesia, so it needs special handling in preventing the number of Indonesian malaria cases. The spread of malaria cases was caused by population density, the households with clean and healthy living behaviors (PHBS), the sufferers receiving ACT programs, and the households living in slums. Indonesia is a unitary state that has a large area and certainly has different environmental characteristics. So that spatial regression analysis is the right solution for the case of Malaria in Indonesia. The spatial regression analysis used is Geographically Weighted Negative Binomial Regression (GWNBR) is one of the models on spatial points. The purpose of this study is to determine the best modeling using GWNBR with malaria cases in Indonesia and the factors that influence it from a regional perspective by comparing the Adaptive Gaussian weighting matrix and Adaptive Tricube weighting matrix. The results showed that the best modeling with the smallest AIC value of 695,2341962 was Geographically Weighted Negative Binomial Regression (GWNBR) with Adaptive Tricube weighting. Significant variable are population density, provision of ACT treatment and slums by taking samples from Papua Province as the province with the highest number of malaria cases.
Implementasi E-Learning Di Masa Pandemi Sebuah Tantangan Bagi Lembaga Pendidikan Suriadi Samsuri; Mursidin Mursidin; Wahidah Wahidah
Jurnal Litbang Edusaintech Vol. 3 No. 2 (2022): Volume 3 No 2 2022
Publisher : Litbang PWM Jawa Tengah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51402/jle.v3i2.20

Abstract

Dampak pandemi corona virus 19 ternyata telah membawa sebuah perubahan yang besar dan mendesak pada berbagai sektor, satu diantaranya adalah pada lembaga pendidikan mulai dari tingkat dasar hingga Perguruan Tinggi. Hal tersebut mempengaruhi perubahan-perubahan dan pembaharuan kebijakan untuk diterapkan. Artikel ini membahas tentang Implementasi E-Learning di Masa Pandemi Sebuah Tantangan Bagi Lembaga Pendidikan. Penelitian ini dilakukan berdasarkan pengamatan pada beberapa sekolah di lembaga pendidikan sekolah dasar di Sambas-Indoensia. Penelitian ini menggunakan jenis penelitian kepustakaan. Hasil analisis dari kajian ini menyimpulkan bahwa tantangan bidang teknologi, tantangan di bidang ekonomi, tantangan dibidang kebudayaan, tantangan dibidang sosial kemasyarakatan, tantangan dibidang sistem nilai, dan tantangan dibidang politik.

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