Pub Date : 2023-09-15DOI: 10.25126/justsi.v4i2.160
Renaldy Wijaya Putra, Yusi Tyroni Mursityo, Widhy Hayuhardhika Nugraha Putra
Perkembangan teknologi informasi membuat banyak organisasi atau perusahaan menginginkan untuk mengadopsi teknologi informasi demi meningkatkan kinerja dan hasil bisnis yang maksimal dalam suatu organisasi. Saat ini perkembangan teknologi informasi sangatlah pesat dan cepat termasuk di Indonesia sendiri. Salah satu bentuk penerapan teknologi informasi yaitu sistem informasi monitoring untuk tujuan apapun bentuknya, baik untuk tujuan kesehatan, pendidikan, keuangan, dan kebutuhan instansi atau organisasi pada tingkat management terkait kepegawaian. Pada praktiknya, sistem informasi monitoring tidak selalu berjalan dengan maksimal, bahkan ditemukan di beberapa instansi atau organisasi yang belum menerapkan sistem ini, salah satu contohnya yaitu di Universitas XYZ. Saat ini, di Universitas XYZ kehadiran dosen masih terpusat mengikuti sistem kehadiran dari Universitas yang mana tujuannya jelas hanya untuk kebutuhan tingkat management saja, padahal pada praktiknya informasi monitoring tersebut juga dibutuhkan mahasiswa. Pada penelitian ini, dilakukan analisis serta desain Sistem Informasi Monitoring Dosen (SIMD) dengan menggunakan metode Rapid Application Development (RAD) serta melibatkan User Experience Questionnaire (UEQ) untuk menguji user experience dan usability system yang telah dikembangkan. Hasil pengujian sistem menggunakan UEQ menghasilkan nilai skala “Daya tarik” 1.700, skala “Kejelasan” 1.800, skala “Efisiensi” 1.463, skala “Ketepatan” 0.950, skala “Stimulasi” 1.000, dan skala “Kebaruan” 1.363. Nilai yang didapat tersebut sudah melewati batas minimum UEQ yang berada pada nilai 0.8, sehingga dapat dikatakan Sistem Informasi Monitoring Dosen (SIMD) dapat diterima dengan baik oleh pengguna.
{"title":"Analisis dan Desain Sistem Informasi Monitoring Dosen Menggunakan RFID pada Universitas XYZ","authors":"Renaldy Wijaya Putra, Yusi Tyroni Mursityo, Widhy Hayuhardhika Nugraha Putra","doi":"10.25126/justsi.v4i2.160","DOIUrl":"https://doi.org/10.25126/justsi.v4i2.160","url":null,"abstract":"Perkembangan teknologi informasi membuat banyak organisasi atau perusahaan menginginkan untuk mengadopsi teknologi informasi demi meningkatkan kinerja dan hasil bisnis yang maksimal dalam suatu organisasi. Saat ini perkembangan teknologi informasi sangatlah pesat dan cepat termasuk di Indonesia sendiri. Salah satu bentuk penerapan teknologi informasi yaitu sistem informasi monitoring untuk tujuan apapun bentuknya, baik untuk tujuan kesehatan, pendidikan, keuangan, dan kebutuhan instansi atau organisasi pada tingkat management terkait kepegawaian. Pada praktiknya, sistem informasi monitoring tidak selalu berjalan dengan maksimal, bahkan ditemukan di beberapa instansi atau organisasi yang belum menerapkan sistem ini, salah satu contohnya yaitu di Universitas XYZ. Saat ini, di Universitas XYZ kehadiran dosen masih terpusat mengikuti sistem kehadiran dari Universitas yang mana tujuannya jelas hanya untuk kebutuhan tingkat management saja, padahal pada praktiknya informasi monitoring tersebut juga dibutuhkan mahasiswa. Pada penelitian ini, dilakukan analisis serta desain Sistem Informasi Monitoring Dosen (SIMD) dengan menggunakan metode Rapid Application Development (RAD) serta melibatkan User Experience Questionnaire (UEQ) untuk menguji user experience dan usability system yang telah dikembangkan. Hasil pengujian sistem menggunakan UEQ menghasilkan nilai skala “Daya tarik” 1.700, skala “Kejelasan” 1.800, skala “Efisiensi” 1.463, skala “Ketepatan” 0.950, skala “Stimulasi” 1.000, dan skala “Kebaruan” 1.363. Nilai yang didapat tersebut sudah melewati batas minimum UEQ yang berada pada nilai 0.8, sehingga dapat dikatakan Sistem Informasi Monitoring Dosen (SIMD) dapat diterima dengan baik oleh pengguna.","PeriodicalId":34309,"journal":{"name":"Jurnal Sisfokom","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135436582","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}
Pub Date : 2023-08-23DOI: 10.24912/jiksi.v11i2.26029
Muhammad Farras, Viny Christanti Mawardi, T. Sutrisno
Google Play functions as the official app store for the Android operating system, allowing users to browse and discover applications developed with the Android software development kit (SDK) and published through Google. Google Play also serves as a digital media store, offering music programs, books, movies, and television shows. It previously offered Google hardware for purchase until it introduced a separate online hardware store, Google Store, on March 11, 2015.The research will utilize a web-based application development tool that uses Flask and JavaScript as the application interface, and the Pandas library from Python for data manipulation. Naïve Bayes will be employed as the methodology for analyzing sentiments based on words, and K-Fold Cross Validation will be used to strengthen the accuracy of the analysis results.Sentiment analysis typically classifies opinions into three categories: positive and negative. However, applications that can perform the process of creating training and testing sets from consumer opinion data, simultaneously analyzing consumer sentiment and dynamically measuring the accuracy of the analysis results, are still scarce. This study aims to develop an application capable of analyzing consumer sentiment with the mentioned functionalities, wherein Naive Bayes is used as the classification method.
Google Play是Android操作系统的官方应用商店，允许用户浏览和发现使用Android SDK (software development kit)开发并通过Google发布的应用。Google Play也是一个数字媒体商店，提供音乐节目、书籍、电影和电视节目。在2015年3月11日推出单独的在线硬件商店Google store之前，它曾提供谷歌硬件供购买。该研究将利用基于web的应用程序开发工具，该工具使用Flask和JavaScript作为应用程序接口，并使用Python的Pandas库进行数据操作。Naïve将使用贝叶斯作为基于单词的情感分析方法，并使用K-Fold交叉验证来加强分析结果的准确性。情感分析通常将观点分为三类:积极的和消极的。然而，能够执行从消费者意见数据创建训练和测试集的过程，同时分析消费者情绪并动态测量分析结果准确性的应用程序仍然很少。本研究旨在开发一个能够分析消费者情绪的应用程序，其中使用朴素贝叶斯作为分类方法。
{"title":"Aplikasi Analisis Sentimen Komentar Pengguna Genshin Impact Di Play Store","authors":"Muhammad Farras, Viny Christanti Mawardi, T. Sutrisno","doi":"10.24912/jiksi.v11i2.26029","DOIUrl":"https://doi.org/10.24912/jiksi.v11i2.26029","url":null,"abstract":"Google Play functions as the official app store for the Android operating system, allowing users to browse and discover applications developed with the Android software development kit (SDK) and published through Google. Google Play also serves as a digital media store, offering music programs, books, movies, and television shows. It previously offered Google hardware for purchase until it introduced a separate online hardware store, Google Store, on March 11, 2015.The research will utilize a web-based application development tool that uses Flask and JavaScript as the application interface, and the Pandas library from Python for data manipulation. Naïve Bayes will be employed as the methodology for analyzing sentiments based on words, and K-Fold Cross Validation will be used to strengthen the accuracy of the analysis results.Sentiment analysis typically classifies opinions into three categories: positive and negative. However, applications that can perform the process of creating training and testing sets from consumer opinion data, simultaneously analyzing consumer sentiment and dynamically measuring the accuracy of the analysis results, are still scarce. This study aims to develop an application capable of analyzing consumer sentiment with the mentioned functionalities, wherein Naive Bayes is used as the classification method.","PeriodicalId":34309,"journal":{"name":"Jurnal Sisfokom","volume":"34 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88438635","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}
Pub Date : 2023-08-23DOI: 10.24912/jiksi.v11i2.26020
Jeffrey Triguna, Bagus Mulyawan
Dashboard is design for CV Mirko Sejahtera Abadi aims to improve the sales performance of CV Mirko Sejahtera Abadi. Making the dashboard can make CV Mirko Sejahtera Abadi easier to know their sales every month and also, they sales performance every month. The design of this dashboard uses the Waterfall model System Development Life Cycle (SDLC) development methodology. The database used in this application is MySQL. The programming languages used are HTML and PHP.
{"title":"PERANCANGAN DASHBOARD PERFOMA SALES DI CV MIRKO SEJAHTERA ABADI","authors":"Jeffrey Triguna, Bagus Mulyawan","doi":"10.24912/jiksi.v11i2.26020","DOIUrl":"https://doi.org/10.24912/jiksi.v11i2.26020","url":null,"abstract":"Dashboard is design for CV Mirko Sejahtera Abadi aims to improve the sales performance of CV Mirko Sejahtera Abadi. Making the dashboard can make CV Mirko Sejahtera Abadi easier to know their sales every month and also, they sales performance every month. The design of this dashboard uses the Waterfall model System Development Life Cycle (SDLC) development methodology. The database used in this application is MySQL. The programming languages used are HTML and PHP.","PeriodicalId":34309,"journal":{"name":"Jurnal Sisfokom","volume":"59 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88696458","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}
Pub Date : 2023-08-23DOI: 10.24912/jiksi.v11i2.26005
Timothy Reynaldi, Lely Hiryanto, Darius Andana Haris
Universitas Tarumanagara memiliki dua status mahsiswa, yaitu mahasiswa aktif dan mahasiswa non aktif. Saat ini, bidang administrasi di Universitas Tarumanagara belum memiliki sistem yang baik untuk menangani tunggakan uang kuliah dari mahasiswa non aktif. Tujuan dari perancangan Aplikasi Monitoring Tunggakan Uang Kuliah Mahasiswa Non Aktif ini adalah untuk memperbaiki dan memudahkan user untuk memonitoring tunggakan uang kuliah dari mahasiswa non aktif di Universitas Tarumanagara. Aplikasi ini menggunakan metode Naive Bayes. Penerapan dari metode Naive Bayes ini berfungsi untuk menghitung probabilitas kemungkinan mahasiswa Universitas Tarumanaga yang non aktif selama tiga semester berturut-turut harus di keluarkan atau tidak. Hasil dari penerapan metode Naive Bayes ini berhasil untuk menampilkan output prediksi untuk dikeluarkan atau dilanjutkannya mahasiswa yang sudah non aktif selama tiga semester berturut-turut. Hasil dari pengujian fungsional aplikasi menggunakan mendapatkan output sukses untuk pengetesan pada semua halaman yang di uji dan metode pengambilan keputusan dari aplikasi ini memiliki akurasi untuk prediksi tindakan pengambilan keputusan sebesar 91%.
{"title":"Aplikasi Monitoring Tunggakan Uang Kuliah Mahasiswa Non Aktif Di Universitas Tarumanagara Menggunakan Metode Naive Bayes","authors":"Timothy Reynaldi, Lely Hiryanto, Darius Andana Haris","doi":"10.24912/jiksi.v11i2.26005","DOIUrl":"https://doi.org/10.24912/jiksi.v11i2.26005","url":null,"abstract":"Universitas Tarumanagara memiliki dua status mahsiswa, yaitu mahasiswa aktif dan mahasiswa non aktif. Saat ini, bidang administrasi di Universitas Tarumanagara belum memiliki sistem yang baik untuk menangani tunggakan uang kuliah dari mahasiswa non aktif. Tujuan dari perancangan Aplikasi Monitoring Tunggakan Uang Kuliah Mahasiswa Non Aktif ini adalah untuk memperbaiki dan memudahkan user untuk memonitoring tunggakan uang kuliah dari mahasiswa non aktif di Universitas Tarumanagara. Aplikasi ini menggunakan metode Naive Bayes. Penerapan dari metode Naive Bayes ini berfungsi untuk menghitung probabilitas kemungkinan mahasiswa Universitas Tarumanaga yang non aktif selama tiga semester berturut-turut harus di keluarkan atau tidak. Hasil dari penerapan metode Naive Bayes ini berhasil untuk menampilkan output prediksi untuk dikeluarkan atau dilanjutkannya mahasiswa yang sudah non aktif selama tiga semester berturut-turut. Hasil dari pengujian fungsional aplikasi menggunakan mendapatkan output sukses untuk pengetesan pada semua halaman yang di uji dan metode pengambilan keputusan dari aplikasi ini memiliki akurasi untuk prediksi tindakan pengambilan keputusan sebesar 91%.","PeriodicalId":34309,"journal":{"name":"Jurnal Sisfokom","volume":"42 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84719145","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}
Pub Date : 2023-08-23DOI: 10.24912/jiksi.v11i2.26028
Monica Saputra, Tony
One of the most popular and most widely used technologies among people today is the internet. Starting from studying, shopping, working, doing business, communicating, everything can be accessed only by using the internet or in other words referred to as online activities. People are now trying to expand their business online, one of which is PT. XYZ. This company is a retail company that has an online and offline distribution system and sells power tools and household appliances. This company already has an application-based system. Therefore, the dashboard design for this company will be used to provide a summary of sales for three months from tokopedia, shoppe, lazada and tiktok shop to make it easier for company leaders to make decisions. The data collection method was carried out by interviewing and dashboard design using the prototyping method. This design will produce a dashboard using the Microsoft PowerBI Desktop application which can provide visual information about PT.XYZ's sales data.
{"title":"Rancang Bangun Dashboard Penjualan pada PT. XYZ dengan Microsoft PowerBI","authors":"Monica Saputra, Tony","doi":"10.24912/jiksi.v11i2.26028","DOIUrl":"https://doi.org/10.24912/jiksi.v11i2.26028","url":null,"abstract":"One of the most popular and most widely used technologies among people today is the internet. Starting from studying, shopping, working, doing business, communicating, everything can be accessed only by using the internet or in other words referred to as online activities. People are now trying to expand their business online, one of which is PT. XYZ. This company is a retail company that has an online and offline distribution system and sells power tools and household appliances. This company already has an application-based system. Therefore, the dashboard design for this company will be used to provide a summary of sales for three months from tokopedia, shoppe, lazada and tiktok shop to make it easier for company leaders to make decisions. The data collection method was carried out by interviewing and dashboard design using the prototyping method. This design will produce a dashboard using the Microsoft PowerBI Desktop application which can provide visual information about PT.XYZ's sales data.","PeriodicalId":34309,"journal":{"name":"Jurnal Sisfokom","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82180742","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}
Pub Date : 2023-08-23DOI: 10.24912/jiksi.v11i2.26014
Matthew Oni, Manatap Dolok Lauro, Teny Handhayani
Food problems often occur among the community, this occurs due to a lack of predictions made to determine future food prices. Food prices can be achieved if the government can provide sufficient food supplies both in terms of quality and quantity. The availability of sufficient food is an important factor in maintaining the health and welfare of the community. However, the high price fluctuations of staple foods in traditional markets have a negative impact on the availability and quality of food for the community, especially those with low incomes. This was caused by various factors such as rising raw material prices, the influence of weather factors, and changes in people's consumption patterns. In addition, the process of distribution and marketing of staple foods in traditional markets in Bandung City, which still relies on manual processes and is less structured, can also cause high price fluctuations. Therefore we need an application to predict staple food needs for the future accurately and effectively. This study uses the Gated Recurrent Unit method. This method is used because the Gated Recurrent Unit method has good performance in making predictions and fits the data used for this study. In this study, there were 5 types of commodities used, namely rice, chicken meat, chicken eggs, shallots, and garlic. All datasets used were taken from the website of the National Strategic Food Price Information (PIHPSNasional, https://www.bi.go.id/hargapangan). Predictive results by evaluating MAE and MAPE for rice 12.8, and 0.10, for chicken meat 12.8 , and 0.10, for chicken egg 244.5, and 0.64, for onion 296.9, and 1.05, for garlic 602.8, and 1.32.
{"title":"PREDIKSI HARGA PANGAN KOTA BANDUNG MENGGUNAKAN METODE GATED RECURRENT UNIT","authors":"Matthew Oni, Manatap Dolok Lauro, Teny Handhayani","doi":"10.24912/jiksi.v11i2.26014","DOIUrl":"https://doi.org/10.24912/jiksi.v11i2.26014","url":null,"abstract":"Food problems often occur among the community, this occurs due to a lack of predictions made to determine future food prices. Food prices can be achieved if the government can provide sufficient food supplies both in terms of quality and quantity. The availability of sufficient food is an important factor in maintaining the health and welfare of the community. However, the high price fluctuations of staple foods in traditional markets have a negative impact on the availability and quality of food for the community, especially those with low incomes. This was caused by various factors such as rising raw material prices, the influence of weather factors, and changes in people's consumption patterns. In addition, the process of distribution and marketing of staple foods in traditional markets in Bandung City, which still relies on manual processes and is less structured, can also cause high price fluctuations. Therefore we need an application to predict staple food needs for the future accurately and effectively. This study uses the Gated Recurrent Unit method. This method is used because the Gated Recurrent Unit method has good performance in making predictions and fits the data used for this study. In this study, there were 5 types of commodities used, namely rice, chicken meat, chicken eggs, shallots, and garlic. All datasets used were taken from the website of the National Strategic Food Price Information (PIHPSNasional, https://www.bi.go.id/hargapangan). Predictive results by evaluating MAE and MAPE for rice 12.8, and 0.10, for chicken meat 12.8 , and 0.10, for chicken egg 244.5, and 0.64, for onion 296.9, and 1.05, for garlic 602.8, and 1.32.","PeriodicalId":34309,"journal":{"name":"Jurnal Sisfokom","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86425336","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}
Pub Date : 2023-08-23DOI: 10.24912/jiksi.v11i2.26035
Richard, Bagus Mulyawan
Project management is a way for organizing to managing and completing projects from start to finish. Using weather data collected from BMKG to carry out data processing by creating a dashboard to display rainfall visualizations using Power BI. This methode research implements use the BI roadmap method. The purpose of this research is to be one of the ways to make decisions. The purpose of the results in this research, it is hoped that making a dashboard visualizations can be useful for users, namely everyone who needs weather information for outdoor activities.
{"title":"MANAJEMEN PROYEK PEMBUATAN DASHBOARD UNTUK VISUALISASI CURAH HUJAN DI JAKARTA","authors":"Richard, Bagus Mulyawan","doi":"10.24912/jiksi.v11i2.26035","DOIUrl":"https://doi.org/10.24912/jiksi.v11i2.26035","url":null,"abstract":"Project management is a way for organizing to managing and completing projects from start to finish. Using weather data collected from BMKG to carry out data processing by creating a dashboard to display rainfall visualizations using Power BI. This methode research implements use the BI roadmap method. The purpose of this research is to be one of the ways to make decisions. The purpose of the results in this research, it is hoped that making a dashboard visualizations can be useful for users, namely everyone who needs weather information for outdoor activities.","PeriodicalId":34309,"journal":{"name":"Jurnal Sisfokom","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77708211","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}
Humans have needs that must be met, one of which is the need for food, but food prices often change. Factors that affect price changes occur because the amount of demand is high while the supply is small. Making predictions about price changes will be very helpful to get an idea of the pattern of price changes. Therefore making predictions from price patterns is useful for providing information to the public. Predictions regarding price changes can be made using many methods. Long Short-Term Memory (LSTM) and Extreme Learning Machine (ELM) are several methods that can be used to predict time series data, these two methods can provide an overview of the predictions made. The results of the study show that both algorithms have good results in terms of the the evaluation value. The evaluation results showed no significant difference between the two algorithms. The evaluation value of the rice commodity showed that ELM tended to be better with MAE values of 6,721, MAPE 0.061%, MSE 115,281, RMSE 10,737 and CV 3,699%, while LSTM with MAE 31,707, MAPE 0.286%, MSE 1927.633, RMSE 43.905 and CV 3.655%. However, for other commodities, LSTM can produce a better evaluation value.
{"title":"PERBANDINGAN LSTM DAN ELM DALAM MEMPREDIKSI HARGA PANGAN KOTA TASIKMALAYA","authors":"Andry Winata, Manatap Dolok Lauro, Teny Handhayani","doi":"10.24912/jiksi.v11i2.26015","DOIUrl":"https://doi.org/10.24912/jiksi.v11i2.26015","url":null,"abstract":"Humans have needs that must be met, one of which is the need for food, but food prices often change. Factors that affect price changes occur because the amount of demand is high while the supply is small. Making predictions about price changes will be very helpful to get an idea of the pattern of price changes. Therefore making predictions from price patterns is useful for providing information to the public. Predictions regarding price changes can be made using many methods. Long Short-Term Memory (LSTM) and Extreme Learning Machine (ELM) are several methods that can be used to predict time series data, these two methods can provide an overview of the predictions made. The results of the study show that both algorithms have good results in terms of the the evaluation value. The evaluation results showed no significant difference between the two algorithms. The evaluation value of the rice commodity showed that ELM tended to be better with MAE values of 6,721, MAPE 0.061%, MSE 115,281, RMSE 10,737 and CV 3,699%, while LSTM with MAE 31,707, MAPE 0.286%, MSE 1927.633, RMSE 43.905 and CV 3.655%. However, for other commodities, LSTM can produce a better evaluation value.","PeriodicalId":34309,"journal":{"name":"Jurnal Sisfokom","volume":"282 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86739738","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}
Pub Date : 2023-08-23DOI: 10.24912/jiksi.v11i2.26004
Bryan Daniel Pinenda Pasaribu, T. Sutrisno, Bagus Mulyawan
This research was conducted to classify student learning outcomes at XYZ Middle School based on academic history during learning and student learning interests. This study aims to provide information to students and teaching staff regarding student learning outcomes. With the available information, it is hoped that teaching staff can develop methods for conveying material in order to obtain better results. The method used in solving this problem is the C.45 algorithm method. Starting from collecting data consisting of assignment scores, daily tests, UTS, and UAS. Then the formation of a decision system as initial data that has condition and decision attribute values. Then calculate the entropy value of each attribute. Calculating the highest gain value which will then be used as a node. Then, determine the decision from the results of the decision tree process by starting from the highest root to the lowest root to determine the decision criteria.
{"title":"KLASIFIKASI HASIL BELAJAR SISWA MENGGUNAKAN METODE C4.5 BERDASARKAN RIWAYAT AKADEMIK DI SMP XYZ","authors":"Bryan Daniel Pinenda Pasaribu, T. Sutrisno, Bagus Mulyawan","doi":"10.24912/jiksi.v11i2.26004","DOIUrl":"https://doi.org/10.24912/jiksi.v11i2.26004","url":null,"abstract":"This research was conducted to classify student learning outcomes at XYZ Middle School based on academic history during learning and student learning interests. This study aims to provide information to students and teaching staff regarding student learning outcomes. With the available information, it is hoped that teaching staff can develop methods for conveying material in order to obtain better results. The method used in solving this problem is the C.45 algorithm method. Starting from collecting data consisting of assignment scores, daily tests, UTS, and UAS. Then the formation of a decision system as initial data that has condition and decision attribute values. Then calculate the entropy value of each attribute. Calculating the highest gain value which will then be used as a node. Then, determine the decision from the results of the decision tree process by starting from the highest root to the lowest root to determine the decision criteria.","PeriodicalId":34309,"journal":{"name":"Jurnal Sisfokom","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77286534","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}
Rainfall is the height of rainwater that falls on a flat area, assuming it doesn't evaporate, doesn't seep, and doesn't flow. Rain levels are measured in mm (millimeters). The target of the research being conducted is in Badung Regency, Bali because Bali is a tourist area that is often visited by tourists and from Indonesian itself, so predictions of meteorology, such as rainfall will greatly impact tourism. In this test, predictions use the Long Short Term Memory (LSTM) method, using daily weather data from the BMKG from 2010 to 2020 as training data and daily weather data for 2021 as prediction data. Based on the test results above, the results show that the two LSTM tests with LSTM Model 128.64 and LSTM Model 64.32 have low MAE and MAPE error values. From First Scenario, the Mean Absolute Error (MAE) value is 8.97246598930908 and Mean Absolute Percentage Error (MAPE) value is 1.7657206683278308%. From Second Scenario, the Mean Absolute Error is 9.706669940783014 and Mean Absolute Percentage Error is 1.9028466692362323%. From the MAE and MAPE values obtained in these two scenarios, it can be proven that from the evaluation results of Rainfall predictions in Badung Regency, Bali, the predictions can be said to be very accurate because they have an error value of less than 10.
{"title":"PREDIKSI CURAH HUJAN DI KABUPATEN BADUNG, BALI MENGGUNAKAN METODE LONG SHORT-TERM MEMORY","authors":"Brando Dharma Saputra, Lely Hiryanto, Teny Handhayani","doi":"10.24912/jiksi.v11i2.26002","DOIUrl":"https://doi.org/10.24912/jiksi.v11i2.26002","url":null,"abstract":"Rainfall is the height of rainwater that falls on a flat area, assuming it doesn't evaporate, doesn't seep, and doesn't flow. Rain levels are measured in mm (millimeters). The target of the research being conducted is in Badung Regency, Bali because Bali is a tourist area that is often visited by tourists and from Indonesian itself, so predictions of meteorology, such as rainfall will greatly impact tourism. In this test, predictions use the Long Short Term Memory (LSTM) method, using daily weather data from the BMKG from 2010 to 2020 as training data and daily weather data for 2021 as prediction data. Based on the test results above, the results show that the two LSTM tests with LSTM Model 128.64 and LSTM Model 64.32 have low MAE and MAPE error values. From First Scenario, the Mean Absolute Error (MAE) value is 8.97246598930908 and Mean Absolute Percentage Error (MAPE) value is 1.7657206683278308%. From Second Scenario, the Mean Absolute Error is 9.706669940783014 and Mean Absolute Percentage Error is 1.9028466692362323%. From the MAE and MAPE values obtained in these two scenarios, it can be proven that from the evaluation results of Rainfall predictions in Badung Regency, Bali, the predictions can be said to be very accurate because they have an error value of less than 10.","PeriodicalId":34309,"journal":{"name":"Jurnal Sisfokom","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82613644","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}
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