Jurnal Teknoinfo最新文献

{"title":"SISTEM PENDUKUNG KEPUTUSAN PENERIMAAN BEASISWA PENINGKATAN PRESTASI AKADEMIK MENGGUNAKAN METODE PREFERENCE SELECTION INDEX","authors":"Rizal Tjut Adek, Hafizh Al Kautsar Aidilof, Ali Imran Nasution","doi":"10.33365/jti.v16i2.1802","DOIUrl":"https://doi.org/10.33365/jti.v16i2.1802","url":null,"abstract":"The rapid development of information technology is in line with the development of computational methods that help solve various problems, one of which is the method of decision support systems. Higher education institutions, especially Malikussaleh University, have many scholarship programs like the Academic Achievement Improvement Scholarship or PPA. PPA is a scholarship that has existed since 2012 which was launched and allocated by the Ministry of Research, Technology and Higher Education with a focus on aspects of improving academic achievement. However, the selection system is still conventional or manual, so it takes longer. This study aims to implement a decision-making system in an application to recommend PPA scholarship recipients automatically. The existence of an automatic decision-making system will be more efficient and effective to help speed up the process of making decisions based on the criteria they have. Some of the assessment criteria used include GPA, semester, the total income of parents, and the number of dependents of parents. Also, the alternative data used are 825 data. The method applied to the system is the Preference Selection Index (PSI) method, which is used as a reference for ranking results and measuring accuracy. In this method, it is not necessary to determine the relative importance between the criteria. In addition, this method does not have certain conditions that require calculating the weight of the related criteria in decision-making problems. The research steps used are the waterfall model with several main stages, namely planning, modeling, implementation, and testing. This system is built using PHP as the programming language and MySQL as the database. Based on system testing, it is found that the system is following the design and can provide ranking results in the form of recommendations for scholarship recipients with a comparison of stakeholder decisions and that the system using the PSI method is 66%. The PSI method can be implemented by displaying each alternative's most considerable PSI value by displaying the ranking results. This PPA Scholarship Acceptance DSS application can be used as an alternative to making it easier for related parties to determine who is entitled to receive the scholarship.","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126675942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"APLIKASI PANDUAN GIZI MAKANAN BALITA BERBASIS ANDROID","authors":"Yunita Rahma, Dini Suhartini, Sufiatul Maryana","doi":"10.33365/jti.v16i2.1790","DOIUrl":"https://doi.org/10.33365/jti.v16i2.1790","url":null,"abstract":"Fulfillment of rich nutrition for toddlers is something that needs to be considered in maintaining health because the age of toddlers enters a nutritional sensitive period. The impact of malnutrition in the first 1000 days of life starting from the fetus to the child is two years old, it not only affects physical development, but also affects subsequent cognitive development, which in turn affects the intelligence, dexterity, and efficiency of thinking and working children at the time. mature. Nutritional status refers to the state of the body caused by eating and using nutrients. This is due to maternity factors and poor parenting, especially the behavior and habits of children who do not eat according to their nutritional intake. Parental knowledge regarding a balanced and nutritious menu is the most influential factor in providing nutrition to toddlers. The lack of nutrition education by health workers makes mothers unable to prevent and overcome nutritional problems in their babies. Based on this, an application is needed that can facilitate parents, especially mothers, to control the nutritional status of their toddlers accompanied by nutritional guidelines for appropriate and balanced toddler food according to their age and nutritional adequacy. This research will build a mobile-based application in the form of a nutritional guide for toddlers' food that is appropriate and balanced according to their age and nutritional adequacy and a nutritional calculator for toddlers to control their nutritional status.","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131576941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PEMILIHAN PUPUK EFEKTIF UNTUK BUDIDAYA TANAMAN BAWANG MERAH DI KABUPATEN DEMAK","authors":"Aditya Mahendra, Saefurrohman Saefurrohman","doi":"10.33365/jti.v16i2.1931","DOIUrl":"https://doi.org/10.33365/jti.v16i2.1931","url":null,"abstract":"","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133056506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A MULTICRITERIA INDEX USING NEURAL NETWORK TO EVALUATE THE POTENTIAL LANDS OF MAIZE","authors":"Muhammad Iqbal Habibie, Nety Nurda","doi":"10.33365/jti.v16i2.1873","DOIUrl":"https://doi.org/10.33365/jti.v16i2.1873","url":null,"abstract":"The criteria for planting maize should be consistent with sensible and ecological criteria to determine the potential lands. However, there is still a lack of proven methodology for this evaluation. The purpose of this analysis was to determine the parameters that affect the multi-criteria decision of maize, with the aim of a new method on the land suitability analysis. The land suitability analysis proposed was based on GIS-analysis and management parameters such as distance from roads, rivers, slope, LULC, elevation, soil type, NDVI, SAVI, rainfall, and temperature. We have found a sample of 4590 maize in Tuban, East Java, Indonesia. Based on the above criteria, maize has been classified into four groups according to FAO. Moreover, we analyzed was done using Neural Network. Results showed that the integrated AHP with Neural Network to evaluate the lands inferred that 66.7 percent of the study area was classified as highly suitable, 30.2 percent were moderately suitable, and 3 percent were marginally suitable for Maize Cultivation in Tuban Regency. The approach presented in this analysis can be extended in this analysis can be extended to other maize areas also other crops as a decision-making system.","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134136449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"KLASIFIKASI KONSUMSI ENERGI INDUSTRI BAJA MENGGUNAKAN TEKNIK DATA MINING","authors":"Sri Rahayu, Jajang jaya Purnama","doi":"10.33365/jti.v16i2.1984","DOIUrl":"https://doi.org/10.33365/jti.v16i2.1984","url":null,"abstract":"Human needs in fulfilling clothing, food and housing in today's life cannot be separated from the involvement of electrical energy. In several sectors of life, namely the household sector, industry, business, social, government office buildings, and public street lighting, electricity is needed. The energy consumption industry sector is relatively higher than other sectors, so it is necessary to control energy consumption, especially in the industrial sector. As a result, for a nation or region, forecasting the use of electrical energy becomes urgent and crucial. Research on this issue has emerged from various countries, for example, research from Korea on energy consumption prediction models for smart factories using a data mining algorithm that introduces and explores the steel industry energy consumption prediction model by producing the best model, namely Random Forest with an RMSE value of 7.33 in the test set. In addition, another study raised the title of an efficient energy consumption prediction model for an analytical data of industrial buildings in a smart city by presenting and exploring a predictive energy consumption model based on data mining techniques for a smart small-scale steel industry in South Korea using variables such as lagging and current. main reactive power, lagging power factor and leading current, carbon dioxide emission and load type. Research from Australia is also not left behind, discussing the prediction of industrial energy consumption using data mining techniques which presents and explores energy consumption prediction models using a data mining approach for the steel industry to show that the Random Forest model can best predict energy consumption and outperform other conventional algorithms in comparison. This study presents a classification of energy consumption in the steel industry, in order to know the pattern of using light loads, medium loads, and maximum loads using data mining techniques on public data that is already available on this matter, with the aim that energy users in the steel industry are wiser in using energy because you already know the pattern of each load. The methods used include Random Forest, Decision Tree, Naïve Bayes and Artificial Neural Networks resulting in accuracy of 91.13%, 90.50%, 70.97% and 75.56%, so that the classification method is the most suitable for use. In classifying industrial energy consumption on the steel industry energy consumption dataset, Random Forest.","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134345836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MESIN PENTERJEMAH BAHASA INDONESIA-BAHASA SUNDA MENGGUNAKAN RECURRENT NEURAL NETWORKS","authors":"Yustiana Fauziyah, Ridwan Ilyas, Fatan Kasyidi","doi":"10.33365/jti.v16i2.1930","DOIUrl":"https://doi.org/10.33365/jti.v16i2.1930","url":null,"abstract":"Translator is a process where one language is changed into another language. Translator in the last research was carried out using a Phrase-based Statistical Machine Translation (PSMT) approach. This research builds an Indonesian to Sundanese translator. The stages used start from pre-processing using text preprocessing and word embedding Word2Vec and the approach used is Neural Machine Translation (NMT) with Encoder-Decoder architecture in which there is a Recurrent Neural Network (RNN). Tests in the study resulted in the optimal value by the GRU of 99.17%. Models using Attention got 99.94%. The use of optimization model got optimal results by Adam 99.35% and BLEU Score results with optimal bleu 92.63% and brievity penalty 0.929. The results of the machine translator produce training predictions from Indonesian to Sundanese if the input sentences are in accordance with the corpus and the translation results are not suitable when the input sentences are different from the corpus.","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131677871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PENENTUAN MINAT KONSUMEN TERHADAP PRODUK MENGGUNAKAN ALGORITMA APRIORI PADA PT.TELKOM INDONESIA","authors":"Pardo Frans Longgana, I. Irvan, Anjar Hero Wilarto","doi":"10.33365/jti.v16i2.1977","DOIUrl":"https://doi.org/10.33365/jti.v16i2.1977","url":null,"abstract":"Dengan adanya kegiatan pesanan penjualan setiap hari, data semakin lama akan semakin bertambah. Data tersebut seharusnya dapat dimanfaatkan dan diolah menjadi informasi untuk meningkatan pesanan penjualan. Permasalahan yang timbul di PT. Telkom Indonesia Divisi Business Service (DBS) yaitu sering sekali pihak sales tidak  mengetahui produk apa saja yang banyak di minati oleh konsumen sehingga produk yang lain tidak diminati dengan cepat. Tujuan dari penelitian ini adalah untuk mendapatkan informasi minat konsumen dari produk-produk di PT. Telkomunikasi Indonesia Segement Hospitality Bussiness Service (HBS) dan mengetahui strategi dalam penjualan berdasarkan pola dan rule algoritma apriori. Dalam penelitian ini, Association Rule berfungsi untuk menganalisa seberapa sering suatu produk yang sering dijual secara bersamaan, analisis ini akan ditinjau dari data pesanan yang telah terjadi. Penerapan Algoritma Apriori dalam aplikasi ini berhasil mencari kombinasi item terbanyak berdasarkan data pesanan dan kemudian membentuk pola asosiasi dari kombinasi item tersebut. Hasil penelitian ini secara keseluruhan didapatkan rata-rata nilai pengujian user acceptance testing dengan metode TAM (Technology Acceptance Model) sebesar 89,6% dan secara keseluruhan model Data Mining dengan menggunakan metode apriori dapat diterima dengan sangat baik oleh user.","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127822513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"WEB SCRAPING OF DISEASE INFORMATION FROM SOCIAL MEDIA TWITTER","authors":"Muhammad Iqbal Habibie, Taufiq Widiaputra, Yulianingsani Yulianingsani","doi":"10.33365/jti.v16i2.1871","DOIUrl":"https://doi.org/10.33365/jti.v16i2.1871","url":null,"abstract":"Environmental degradation caused by land conversion, trash (both domestic and industrial), and natural catastrophes is all variables that contribute to the establishment of disease susceptibility. Experts throughout the world suggest “ONE HEALTH” as a strategy for dealing with the threat of zoonoses. The One Health concept is a worldwide strategy to expand interdisciplinary collaboration and communication in all aspects of health care for humans, animals, and the environment. To overcome this disease of zoonoses, we developed a system of information zoonoses and Emerging Infectious Disease (SIZE). In this system of SIZE, we gather the disease information from social media. The disease information was collected from Twitter are Demam Berdarah Dengue (DBD), malaria disease, Antraks Disease, Canine Madness (Anjing Gila), Bird Flu (flu burung), and Ebola Disease. Twitter is a social media platform that has become a constant resource developing for data collectors. To perform this task to get the data of disease information, related tweets and Twitter user details the data collection using web scraping. Data Collection from Twitter was carried out by applying web scraping technology using python language. The scraping experiment from twitter in this study has succeeded in retrieving disease information from 2015-2020 using an advanced tool for Twitter scrapping called Twint using the python script. As the results lately have been increased number of tweets of diseases from canine madness (anjing gila) 34477, followed by Malaria Disease (28046) and Demam Berdarah Dengue (DBD) 11950 in 2020.","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128395053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PEMANFAATAN JSON UNTUK MENAMPILKAN DATA REALTIME COVID-19 DENGAN MODEL VIEW PRESENTER","authors":"Rysa Sahrial, Deri Fikri Fauzi, Eva Susilawati","doi":"10.33365/jti.v16i1.780","DOIUrl":"https://doi.org/10.33365/jti.v16i1.780","url":null,"abstract":"","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122452033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"APLIKASI GAME EDUKASI MATEMATIKA TINGKAT DASAR BERBASIS ANDROID","authors":"S. Sulistyowati, E. Gunawan, Lili Rusdiana","doi":"10.33365/jti.v16i1.806","DOIUrl":"https://doi.org/10.33365/jti.v16i1.806","url":null,"abstract":"","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134097958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}