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Suwanto Raharjo
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INDONESIA
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 61 Documents
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Penerapan transfer learning pada convolutional neural networks dalam deteksi covid-19. Buyut Khoirul Umri; Visq Delica
JNANALOKA Vol. 02 No. 02 September Tahun 2021
Publisher : Lentera Dua Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36802/jnanaloka.2021.v2-no2-53-61

Abstract

The Covid-19 pandemic has become a serious problem in the world, including Indonesia, until now, the virus that emerged at the end of 2019 is still a serious problem. The number of cases of infected people continues to increase and reaches more than two hundred million cases worldwide. To carry out this rapid test, it did not run smoothly but experienced many obstacles experienced by the Medical team, one of which was the limitation of the Covid-19 test kit, so scientists took other diagnostic steps. In the field of informatics, scientists use several diagnoses, one of which is X-ray images of the lungs. CXR images are currently often used for the detection process using the CNN algorithm. This research uses transfer learning method which will be tested in large and small scale datasets. The best result of all the models tested is MobileNet with an accuracy of 98.11% which was tested on a large-scale dataset and the lowest was obtained by ResNet50 which was tested on a small-scale dataset with an accuracy of 41.94%. The large-scale dataset also shows improved accuracy across all tested transfer learning models.
Analisis Sentemen Terhadap Aplikasi Bukalapak Sebelum IPO dan Sesudah IPO Menggunakan Algoritma Naive Bayes Bayu Yanuargi
JNANALOKA Vol. 03 No. 01 Maret Tahun 2022
Publisher : Lentera Dua Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36802/jnanaloka.2022.v3-no1-17-25

Abstract

Bukalapak is one of the earliest eCommerce startups established in Indonesia. Bukalapak has been bridging between sellers (Pelapak) and buyers since 2010. In 2021 Bukalapak ventured to conduct Initial Public Offers on the IDX. There are many kinds of responses from Bukalapak users to Bukalapak's steps, both positive and negative. These negative or positive sentiments can be used as input and evaluation for Bukalapak itself to maintain the loyalty of its users. The research process starts from collecting data obtained from scrapping data on Bukalapak product reviews on Google Playstore before and after the IPO. Then preprocessing the data starting from casefolding, removing stop words, tokenization, steming to TF-IDF. The results of the preprocessing are then used as data for classification using Naive Bayes. The classification was then tested and obtained an accuracy value for the data before the IPO of 77% and the data after the IPO of 76%.
Analisis Sentimen pada review hotel menggunakan metode pembobotan dan klasifikasi Aam Munir; Enda Putri Atika; Aziza Devita Indraswari
JNANALOKA Vol. 03 No. 01 Maret Tahun 2022
Publisher : Lentera Dua Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36802/jnanaloka.2022.v3-no1-33-38

Abstract

Globally, the tourism industry has an important role in the economic progress of a region or country. This development is assisted by the development of internet technology such as social media, tourism portal websites and others. The assessment of a hotel on the portal website can also affect the consumer's desire to choose the hotel or not. Sentiment analysis on reviews issued by consumers can be divided into positive reviews or negative reviews. Sentiment analysis starts from data retrieval, namely scrapping and then proceeds to the preprocessing process so that data is obtained that is ready for analysis. After the preprocessing process is carried out, it is continued with the weighting process. the weighting process uses three methods, namely Unigram, bigram and term frequency Inverse Document frequency. After the weighting process is carried out, the classification process is carried out using two methods, namely Naive Bayes and Support vector Machine. The result of the classification process is the highest accuracy obtained by the TF-IDf weighting method and the SVM method of 95% followed by the Unigram weighting method with the SVM method of 94%.
Sentimen Twitter terhadap PILKADA kota Medan menggunakan metode Naive Bayes Prasetyo Mimboro
JNANALOKA Vol. 03 No. 01 Maret Tahun 2022
Publisher : Lentera Dua Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36802/jnanaloka.2022.v3-no1-27-32

Abstract

Indonesia is the fifth largest country with twitter users with 19.5 million users. Along with the development of information technology, twitter has become a source of information based on twitter sentiment and trending as well as the use of hashtags that are trending. Recently, the archipelago vaccine has reaped the pros and cons, to be able to classify positive and negative sentences in twitter sentiment towards the archipelago vaccine, it requires data from twitter users by taking data based on sentence classification which is then processed in the initial data before being entered into the indoBERT model which will later be resulting in the accuracy of twitter sentiment towards the archipelago vaccine. Indonesia has 19.5 million Twitter users out of a total of 500 million global users and continues to grow from time to time. Twitter users used it as an open forum for campaigns by the Medan mayoral candidate and their volunteers were asked by Netizens to respond. Netizens' responses to each tweet are both Positive and Negative. Therefore, this study tries to analyze tweets about netizens' sentiments towards the 2020 Medan City Election. Opinions or sentiments from Twitter users can of course be used as criticisms and suggestions that can be accommodated by candidates for mayor and deputy mayor of Medan. Twitter netizens often have opinions about Regional Head Candidates through their uploads. The opinions of Twitter Netizens are still random or unclassified. To facilitate the process of classifying netizen opinion data requires Sentiment Analysis. Sentiment analysis was carried out by classifying tweets containing Netizen sentiments towards the 2020 Medan City Election. The classification method used in this study is the Naive Bayes method combined with TF-IDF feature extraction. NS The validity test applied in this study used a confusion matrix. With the tf-idf extraction feature and the Naive Bayes method, it will be able to automatically classify sentiment analysis with an accuracy of 76.00%.
Analisa Perbandingan Algoritma Fuzzy Tsukamoto Dan Sugeno Untuk Menentukan Jumlah Produksi Batik Berdasarkan Data Persediaan Dan Jumlah Permintaan (Studi Kasus : Batik Jiwo Creation, Sukoharjo) Rajnaparmaitha Kusumastuti
JNANALOKA Vol. 03 No. 01 Maret Tahun 2022
Publisher : Lentera Dua Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36802/jnanaloka.2022.v3-no1-11-16

Abstract

Batik Jiwo Creation is a batik convection and sales shop that stands in the city of Sukoharjo. The amount of demand that changes every period causes uncertainty in determining the company's production amount in the coming period. Planning the number of products is very important in meeting market demand correctly and in the right amount. Analysis of determining the amount of production is carried out using the Fuzzy Tsukamoto and Sugeno Algorithm based on the amount of inventory and the number of requests. Tsukamoto and Sugeno algorithm is a method of fuzzy inference system. In the Tsukamoto method, every consequence of the if-then rule must be represented by a fuzzy set with a monotonous membership function, while the Sugeno method has the final form in the form of constants or linear equations. Based on the MAD error value on Fuzzy Tsukamoto is 17.93 while on Fuzzy Sugeno it is 210.73. This shows that the Fuzzy Tsukamoto method is better used in the calculation of production forecasting. This comparison algorithm is used to help determine the amount of production in the next period depending on the amount of demand and supply from the previous period.
Analisis Perbandingan Algoritma Nazief Adriani dan Levenshtein Distance untuk mengukur Tingkat Similaritas Berita Menggunakan Rabin Krap: Studi Kasus Berita Berbahasa Jawa Danang Kastowo; Andy Saputra; Wachid Daga Suryono; Erna Setyowati
JNANALOKA Vol. 03 No. 01 Maret Tahun 2022
Publisher : Lentera Dua Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36802/jnanaloka.2022.v3-no1-1-10

Abstract

For people in Indonesia, the regional language is the everyday language used to communicate. One of them is the Java language. In natural language-based research, regional languages are considered difficult languages to develop, given the availability of a limited number of datasets. This study analyzes 2 word stemming methods, namely the Nazief-Adriani method and the Levenshtein Distance method to carry out the Javanese word stemming process. This study wanted to find out the appropriate method with the best accuracy for stemming Javanese words. In addition, this study also considers word weighting to produce better article similarity accuracy. The nazief adriani method produces an average similarity value of 6.8% with an average execution time of 0.0443 second.
Analisa gambar citra MRI otak dengan watershed dan ekstraksi fitur GLCM Astika Wulansari; Aulia Tegar Rahman
JNANALOKA Vol. 03 No. 02 September Tahun 2022
Publisher : Lentera Dua Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36802/jnanaloka.2022.v3-no2-39-46

Abstract

Brain tumor is an infection in the form of unwanted tissue and considered as malignant. Nevertheless, it is very difficult to distinguish brain tumor tissue from the rest of the brain. Early detection of tumors is crucial to save the patient’s life. Segmentation strategy is used to identify and parse brain tumor areas utilizing the Magnetic ResonanceImaging (MRI) images of the brain. This is an important breakthrough for the future. Magnetic Resonance Imaging is an extreme field in the image processing area due to the very high level of precision needed by the doctors to obtain precise recommendations about the infections to save the patients’ lives. MRI images can be used to provide information on the separation of brain tumor tissue. Segmentation of MRI images with median filtering and skull stripping preprocessing techniques, threshold grip with watershed obtained contrast results of 4.287, correlation 0.946, homogeneity 0.721, and energy 0.278.
Analisis Efektivitas Marka Kotak Kuning Di Simpang Tiga Jalan Soekarno Hatta – Jalan Arifin Ahmad Kota Pekanbaru Muchammad Zaenal muttaqin; Abdul Kudus Zaini; Zhella Indah Saviri
JNANALOKA Vol. 03 No. 02 September Tahun 2022
Publisher : Lentera Dua Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36802/jnanaloka.2022.v3-no2-57-65

Abstract

One of the interchanges in Pekanbaru City, namely simpang tiga (Jalan Soekarno Hatta - Jalan Arifin Ahmad) has quite dense activities, because this road is an access to the center of community activities to the market area, offices and others. An increase in the number of vehicles larger compared to the available roads leads to congestion. One of the efforts to reduce congestion at intersections is to use yellow box markings. This marking is designed as a vehicleless area, if there is a traffic congestion, vehicle users who are still outside the marking must stop and wait until the traffic jam breaks down. This study aims to analyze the effectiveness of the yellow box markings and the suitability of the yellow box markings. This study used the Regulation of the Minister of Transportation No. 34 of 2014 and the Traffic Signs Manual Chapter 5 Road Markings (2018) and the Indonesian Road Capacity Manual (MKJI) 1997 to determine the effectiveness of intersection performance. The parameter used to determine the effectiveness of interchange performance is the degree of saturation. The results of the analysis found that the size of the yellow box markings at the research site was not appropriate according to Permenhub No.34 of 2014 the width of the straight line and the diagonal line was 10-18 cm and the Traffic Signs Manual Chapter 5 Road Markings (2018) the width of the diagonal line was 15 cm and the width of the straight line was 20 cm, while at the research location the width of the straight line and the diagonal line was 30 cm. For the number of offenders the yellow box markings were 7195 offenders. Based on the results of the saturation degree analysis, for intersection three, the saturation degree value exceeds 1.00 which indicates that the yellow box marking is not effective in improving the performance of the intersection.
Pelatihan Google Classroom Untuk Meningkatkan Kompetensi Guru SD Dalam Pembelajaran Daring Nureyzwan Sabani; Reza Ulva Tamimi; Lisnawati Ruhaena
JNANALOKA Vol. 03 No. 02 September Tahun 2022
Publisher : Lentera Dua Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36802/jnanaloka.2022.v3-no2-47-56

Abstract

Teacher are not ready to carry out online learning in using online media during the covid-19 pandemic because of the lack competence of teachers. The purpose of this activity is to improve the competence of elementary school teachers in using Google Classroom to support online learning. The Program of Community Service is carried out by holding google classroom training for elementary school teachers through the Zoom aplication. To find out the increase in teacher competence, a pretest and posttest were carried out, followed by a t-test. The test results show that there is a significant difference between the results of the pretest and posttest with Z score of -2.032 and a p value of 0.042 <0.05, so it can be concluded that there is an increase in the competence of elementary school teachers in using google classroom after being given training. With this training, it is hoped that teachers can carry out learning with the help of Google Classroom so that online learning can be managed and implemented properly.
Pengembangan Soal Berpikir Kritis Menggunakan Aplikasi Wondershare Quiz Creator Pada Materi Hidrolisis Garam Irfandi Irfandi; Rosa Murwindra
JNANALOKA Vol. 03 No. 02 September Tahun 2022
Publisher : Lentera Dua Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36802/jnanaloka.2022.v3-no2-67-74

Abstract

Critical thinking ability is one of the must-have abilities for students in 21st century learning. This study aims to develop critical thinking questions on salt hydrolysis material using the wondershare quiz creator application. This research is a Research and Development with the Plomp model. The research subjects are 20 students and 2 chemistry teachers in a small-scale trial. The instruments used are critical thinking questions, material expert validation sheets, media expert, and response questionnaires for teachers and students. Based on the results of the validation of questions by the material, evaluation, language, and practitioner experts, the validation results have a score of 90% for the material aspect, 96% for the construction aspect, and 94% for the language aspect with a category of Valid. For the results from the media expert are 90% on content substance aspect, 95% on learning design aspect, and 92% on display aspect with a category of Valid. As for the result of the small-scale trial of student responses, it obtained the score of 87% in the “very good” category. While the result of the teacher responses obtained the score of 87.92% in the category of “very good” as well. Based on these results, critical thinking questions on hydrolysis material are valid to be used as an instrument for assessing critical thinking ability.

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