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Suwanto Raharjo
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JNANALOKA
Published by Lentera Dua Indonesia
ISSN : 27227332     EISSN : 27222896     DOI : https://doi.org/10.36802/jnanaloka.2020.v1-no1
Core Subject : Science, Education, Social, Engineering,
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences Transportation Other
JNANALOKA merupakan jurnal ilmiah berbasis blind peer review dan open access terbit mulai tahun 2020 dipublikasikan oleh Lentera Dua Indonesia. Jurnal terbit sebanyak 2 (dua) kali dalam setahun yakni bulan Maret dan September. Redaksi Jurnal JNANALOKA menerima artikel ilmiah orisinil lintas bidang ilmu yang memiliki fokus namun tidak terbatas pada bidang sains dan teknologi baik tingkat dasar, menengah, dan tinggi lintas dan multi disiplin ilmu. JNANALOKA juga menerima artikel yang didasarkan pada penelitian ilmiah secara umum.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 04 No. 02 September Tahun 2023" : 5 Documents clear
Analisis Perbandingan Pencampuran Bijih Nikel High Grade Limonit Dan Low Grade Saprolit Untuk Memenuhi Permintaan Pasar Pada PT Mandiri Mineral Perkasa Thamsi, Alam Budiman; Yusuf, Firman Nullah; Rahma, Kismu; Hardin Wakila, Muhamad
JNANALOKA Vol. 04 No. 02 September Tahun 2023
Publisher : Lentera Dua Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36802/jnanaloka.2023.v4-no2-63-68

Abstract

PT Mandiri Mineral Perkasa is a contractor company operating in the field of nickel mining and has fulfilled the market/smelter demand requirements for Ni 1.5% - 2.0%, by setting a Cut Of Grade (COG) collection limit of Ni 1.4%. The aim of this research is to determine the Ni content of high grade limonite and low grade saprolite at the research location, and to determine the Ni content of high grade limonite and low grade saprolite, and to determine the additional tonnage and levels to meet market demand. In this study, the blending method was used, a mixing process between different low grade and high grade nickel ores to obtain appropriate mixture results, so that from the results of blending/mixing high grade limonite nickel ore, Ni 1.43 and Fe 26.71% were obtained, and for low grade saprolite you get 1.59% Ni and 26.73% Fe, for the results of blending/mixing high grade limonite and low grade saprolite you get 1.51% Ni and 26.72% Fe, efforts can be made to meet demand Ni 1.8% market with 5,000 tons needs to increase the grade and tonnage, namely, Ni grade 2.32% and 2,111.45 tons.
Prediksi Harga Forex Menggunakan Algoritma Long Short-Term Memory Pahlevi, Mohammad Rezza Pahlevi; Pahlevi, Mohammad Rezza
JNANALOKA Vol. 04 No. 02 September Tahun 2023
Publisher : Lentera Dua Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36802/jnanaloka.2022.v3-no2-69-76

Abstract

Trillions of dollars per day of foreign currency trading activity occur in the forex market, which has very volatile movements in foreign currency trading. Trade based on bid and ask prices. The market determines foreign exchange rates based on supply and demand rules. Currency trading in pairs such as EUR/USD is a comparison of the value of the Euro against the Dollar as a basis for research, rising and falling currency prices in forex move fluctuatingly, so a market participant must be able to decide on buying and selling positions. Because wrong decisions can lead to losses. One of the ways to reduce risk in making decisions in buying and selling in forex can be using forecasting. This study uses the LSTM method in predicting forex prices which will be tested on several scales of dataset distribution. The smallest error results using a total dataset of 2631 with a dataset division of 70:15:15, which is divided into 70% data for training, 15% data for validation and 15% data for testing produces an RMSE value of 0.038, MAPE 2.5%. In measuring how well the regression model used with Rsquare on the data distribution is 70:15:15 and the total dataset used is 4979 to get the best results, namely 97%.
Penerapan model InceptionV3 dalam klasifikasi penyakit ayam Muhammad Salimy Ahsan; Kusrini Kusrini; Dhani Ariatmanto
JNANALOKA Vol. 04 No. 02 September Tahun 2023
Publisher : Lentera Dua Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36802/jnanaloka.2023.v4-no02-55-62

Abstract

Chicken disease is one of the problems that can have a very significant impact on chicken farmers, in addition to having an impact on the farm itself, chicken disease can also have an impact on the surrounding environment. Lack of knowledge about the symptoms and diseases that occur in chickens, makes some chicken breeders treat and treat diseases in a traditional way. This method often takes a long time and is prone to errors. In this study, technology will be used to classify chicken diseases by utilizing a deep learning model from the Convolutional Neural Network (CNN) architecture, namely InceptionV3. In carrying out the process of classifying chicken diseases, using a dataset of chicken feces images with a number of 8067 Healthy, Salmonella, Coccidiosis, and Newcastle disease. In the research process, three experimental scenarios were carried out using 20 epochs, 50 epochs and 100 epochs. From the experimental results, using a value of 100 epochs produces the highest accuracy value with a value of 94.05%.
Penggunaan  Metode Forensik  Dalam Pengungkapan Kejadian  Klaim Asuransi  Kebakaran Ferdinand, Sean Michael; Nasyubun, M; Awaloedin, Mulawarman
JNANALOKA Vol. 04 No. 02 September Tahun 2023
Publisher : Lentera Dua Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36802/jnanaloka.2023.v4-no02-77-89

Abstract

When an insurance claim occurs, there is often a difference of opinion between the insurer and the insured in interpreting the contents of the policy. In order to resolve claim disputes, according to the clauses in the policy, an opinion from an independent third party is needed. The purpose of third party involvement is to provide an opinion from another point of view. In this research, it is described how third parties are involved in resolving an insurance claim. Starting from the incident report, it was reported that a fire had occurred at latitude coordinates 7°25'26"S and longitude 112°43'33"E. Appointed investigators visit places affected by the fire to carry out inspections at the scene and investigate the origin of the fire and look for possible causes of the fire. Using forensic methods that include on-site investigation, damage analysis, witness statements, interpretation, and deductive reasoning processes,  data collected in the field is then analyzed to be tested against a number of proposed hypotheses. Debris and electrical cable samples were collected for further analysis. Based on physical evidence collected during the investigation, it was discovered that the fire started in the northwest portion of the building. The results of the findings were then traced by tracing the parts of the building that were damaged, and investigators found an electrical short circuit  due to a failure in the lights. These findings are then analyzed by the insurance claims team to determine the amount of the claim that must be paid by the insurer. There were no suspicious elements or circumstances surrounding the fire and other possible causes of the fire have been considered and ruled out.
Robust Spatial Durbin Model Untuk Pemodelan Tingkat Pengangguran Terbuka di Provinsi Jawa Tengah Dwi Bekti, Rokhana; Rifdha Rahmadhani, Wahyu; Noeryanti, Noeryanti
JNANALOKA Vol. 04 No. 02 September Tahun 2023
Publisher : Lentera Dua Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36802/jnanaloka.2022.v4-no2-91-103

Abstract

Unemployment is still a very crucial problem faced by the Indonesian state. The Central Bureau of Statistics noted that the number of unemployed in Indonesia in 2019 was 4.44 percent, an increase of 2.04 percent in 2020. The purpose of this study was to find out the characteristics of the spatial pattern and modeling the open unemployment rate in Central Java Province. Removing outliers in spatial analysis can change the composition of the spatial effects on the data. One method of solving due to outliers in the spatial regression model is using spatial robust regression. Robust Spatial Durbin Model method which is one of the methods used when spatial outliers occur. The results showed that there are spatial pattern characteristics and modeling for each dependent and independent variable which are different from the independent variables which are mutually correlated. In addition, the RSDM model is a better model than the OLS and SDM models in modeling the Open Unemployment Rate in Central Java Province in 2021 because it has an R2 value of 49.85% and the smallest AIC value of 22,563.

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