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Inovate : Jurnal Ilmiah Inovasi Teknologi Informasi
Published by Universitas Hasyim Asy'ari
ISSN : 31090117     EISSN : 25487795     DOI : -
Core Subject : Science,
Computer Science & IT
INOVATE: Jurnal Ilmiah Inovasi Teknologi Informasi adalah jurnal ilmiah yang diterbitkan oleh Fakultas Teknologi Informasi, yang bertujuan untuk menampung dan mempublikasikan hasil penelitian yang dilakukan oleh dosen dan mahasiswa dari program studi Teknik Informatika, Sistem Informasi, serta Ilmu Komputer. Jurnal ini berfungsi sebagai wadah untuk pengembangan ilmu pengetahuan di bidang teknologi informasi, dengan penekanan pada inovasi serta penerapan teknologi terbaru dalam menyelesaikan permasalahan yang ada di masyarakat dan industri. Fokus utama jurnal ini meliputi penelitian yang berkaitan dengan bidang teknologi informasi, sistem informasi, rekayasa perangkat lunak, serta ilmu komputer. Setiap artikel yang diterbitkan dalam jurnal ini melalui proses review yang ketat, dengan tujuan memberikan kontribusi yang signifikan terhadap pengembangan teori, konsep, serta aplikasi dalam dunia teknologi informasi. Selain itu, jurnal ini juga bertujuan untuk memfasilitasi kolaborasi antara akademisi dan praktisi guna mendorong implementasi solusi teknologi yang relevan dengan kebutuhan industri serta perkembangan sosial yang dinamis. INOVATE diterbitkan secara berkala dengan frekuensi dua kali setahun dan terbuka untuk publikasi berbagai jenis artikel, termasuk penelitian dasar, pengembangan teknologi, serta studi kasus yang mengangkat inovasi di bidang sistem informasi, kecerdasan buatan, dan teknologi berbasis web maupun mobile.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 216 Documents
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Memprediksi Jumlah Produksi Roti Dengan Menerapkan Metode Monte Carlo Nur Rohmah, Fitri; Arwin Dermawan, Dodik; Andriani, Anita
Inovate Vol 5 No 2 (2021): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v5i2.3120

Abstract

The process of predicting the amount of production is useful for reducing the level of producer losses due to inaccuracy in determining the amount of production, so that the stock of goods which usually experience accumulation or even out of stock is expected no longer. The purpose of this research itself is to design a system using Monte Carlo as a method to predict the amount of bread production. In the Monte Carlo method there is one step in the process using random numbers. The method used to generate random numbers this time is using the Linear Congruent Method (LCM). Hasil method. The results of this research is an application to facilitate the admin of the production sector to predict the amount of bread production for the next day. The prediction of the amount of production for this type of comb bread yields 1461 seeds of bread. The results of testing the accuracy of the Monte Carlo method in predicting the amount of bread production using MAPE, resulting in a fairly small error value of 9.43%. So this research is quite appropriate to be used as a method of predicting the amount of bread production. Keywords: Prediction, Production, Monte Carlo, LCM
Penerapan Algoritma Binary Searching Untuk Pencarian Berkas Pada Sistem Pengarsipan (Study Kasus: Pemerintahan Desa Kedungbetik) Nasruddin, Hammam; Mashuri, Chamdan; Wiratsongko, Radityo
Inovate Vol 5 No 2 (2021): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v5i2.3121

Abstract

Archiving files and searching files that are still using manual or not computerized methods. The purpose of this research is to create a website-based filing system that has a file search feature with a fast and accurate time of the many files that have been archived. To find files quickly and accurately from a lot of data, we need an algorithm, the binary searching algorithm. This algorithm is a search algorithm that can search for files in a fast time and has a lighter amount of computing. From the results of testing the search speed using a binary search algorithm, the data search speed test is 100 document archive data, with the name of the data sought is population data. Searching using an algorithm has a time of 148 / ms while searching without using an algorithm is 799 / ms. From testing the search speed using a binary search algorithm this is 95% Keywords: System, Archiving, Algorithm, Binary Searching, File, Searching
Penerapan Metode Exponential Smoothing Pada Prediksi Dana Donatur Di Lembaga Amil Zakat Ummul Quro Kabupaten Jombang Anggung Mestuti Kaprawiran, Immas; Dwi Nuryana, I Kadek; Augusta Jannatul Firdaus, Reza
Inovate Vol 5 No 2 (2021): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v5i2.3122

Abstract

Donor Fund Prediction is a prediction system that aims to predict donor funds at the Ummul Quro Amil Zakat Institution, Jombang Regency. The Donor Fund Prediction is used to predict the next year based on previous year's data. This study focuses on using exponential smoothing while for the prediction method initially using moving averages. The calculated data is 2014-2018 while 2019 is used for testing prediction errors. In predicting exponential smoothing, alpha constant value which has the smallest error is needed. To get it, several stages are needed, namely, predicting 2014-2019 using a moving average with a constant defined by the user, predicting 2014-2018 with exponential smoothing with an alpha value between 0 to 1, looking for the MAPE (Mean Absolute Percentage Error) value at each value alpha used. After obtaining alpha with the smallest MAPE, the alpha value is used to predict 2019. The test results explain that calculations using a program with the Moving average method and Exponential smoothing successfully predict with an accuracy of 93.32% or only have an error of 6.68% instead of using only the method. The moving average only has an accuracy of 90.25%. Keywords: Prediction, Exponential smoothing, Moving average
Penentuan Sekolah Terdekat Untuk Visitasi Asesor Menggunakan Metode Algoritma K-Means Berbasis Web Zainal Ikhwan, Muhammad; Putra Eka Prismana, IGL; Mashuri, Chamdan
Inovate Vol 5 No 2 (2021): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v5i2.3124

Abstract

The closest school determination to visitation of assessors is a step made to facilitate the assessors to implement school accreditation. School Accreditation is an effort to improve the quality of National Education. The provincial school accreditation body or Madrasah (BAP-S/M) conducts recruitment of assessors and is divided by a number of places or regions to perform visitation. The Research aims to design a nearby school-based website determination System and implement the K-means method for such systems. This method is used to group the data by specifying the number of clusters or previous groups, calculating the centroid Center and grouping the data that has the similarity of variables. This method calculation generates multiple iterations that have cluster values. Of these iterations used the least number of cluster values to determine the group of schools within one province. The result of this research is a nearby school determination information system for the visitation of assessors. The testing of this system was conducted at the school in the province of East Java with the coordinate point as a variable of latitude and longitude coordinates. From the test results with 20 school data data into 3 clusters, obtained the result of cluster 1 with the coordinate center point (-7,213605, 112,769658) amounting to 8 schools, cluster 2 with the coordinate center point (-7,202459, 112,636323) amounting to 7 school and cluster 3 with coordinate center point (-7,249299, 112,636909) amounting to 5 schools. Keywords : K-Means, Clustering, Accreditation, School, Web.
Rancang Bangun Game Edukasi Pembelajaran Aksara Jawa Berbasis Android Margareta, Adhitya; Putra Eka Prismana, IGL; Setyo Permadi, Ginanjar
Inovate Vol 6 No 1 (2021): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v6i1.3144

Abstract

The written communication tool used by the Javanese tribe is Javanese script. Javanese script education is important to be taught to children from an early age so that children are not blind to Javanese script itself and to support the preservation of the nation's culture. The purpose of this research is to build Javanese script learning educational games for children, as well as to help the government in preserving local culture. The method used in this game is the Decision Tree and Finite State Machine (FSM) method. Decision Tree is used as an assessment or scoring in the game. The steps of the Decision Tree method are to determine the first parameter that will be used as the highest score to be obtained, the next step is to determine the second parameter that will be used as the score, and so on. The Finite State Machine (FSM) works based on the results obtained from the previous decision tree calculations, which will determine the continuation of the game. The results of this study are a Javanese script educational game for Javanese script learning in the form of connecting dots to become a script. Java, so players can play while learning. Keywords: Game, Javanese Script, Finite State Machine (FSM), Decision Tree
Penentuan Produk yang Diminati Pasar Menggunakan Algoritma K-Means Irwan Mahfud, Muhammad; Imam Agung, Achmad; Lazulfa, Indana
Inovate Vol 6 No 1 (2021): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v6i1.3145

Abstract

Grouping to get class similarity and dividing into several classes is one of the processes of data mining. The accuracy of the grouping is an important factor to determine the product's interest in the market. The purpose of this study is to determine which products are classified as the most desirable, desirable and lessdesirable markets, so that petrified in decision making. This research uses the CRISP-DM (Cross Industry Standard Process for Data Mining) method is a methodology from minimum data that is used to analyze problems in business processes or research units. K-Means algorithm is used for grouping products that are of interest to the market. K-Means algorithm partitioned class similarity based on predetermined parameters, by calculating the centroid distance in a class. This research resulted in a product determination information system that is of interest to the market. From the test results using six parameters, namely, the number of transactions, sales volume, product categories, product diversity, average sales and number of stocks with transaction data of 1,235 transactions. Obtained the three best clusters, performance testing has been done using the Elbow method with the most SSE difference of 28,00782. Keywords: Data mining, K-Means, clustering, products market demand.
Rancang Bangun Game Edukasi “Kuy Ngaji” Berbasis Android Menggunakan Metode Finite State Machine Haqiqi Tegar Sanubari, Ahmad; Putra Eka Prismana, IGL; Kistofer, Terdy
Inovate Vol 6 No 1 (2021): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v6i1.3158

Abstract

Kuy Ngaji game application is an application used to support learning programs to write and hear the pronunciation of hijaiyah letters. This application can be supported by the smartphone as a tool to play the game. The purpose of this study is to design and build an educational application that is educational to children for learning hijaiyah letters writing and how to pronounce them. The method in this study uses the Finite State Machine as a game flow determination. Application of flood fill as an algorithm connecting one node to another node aims to support the process in the game. The results of this research is where the player will write hijaiyah letters in the game, the more perfect the player writes the letters, the point will be perfect. Point in the game is a star that will be obtained, the maximum number of stars is 3 stars. Keywords : Finite State Machine, Flood Fill, Education Game.
Sistem Klasifikasi Tingkat Kesesuaian Bibit Dan Pupuk Dengan Algoritma C4.5 Berbasis Website (Studi Kasus : Kecamatan Megaluh) Panji Sulanggalih, Mochammad; Rohman Nudin, Salamun; Augusta Jannatul Firdaus, Reza
Inovate Vol 6 No 1 (2021): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v6i1.3159

Abstract

Selection of suitable seeds and fertilizers will greatly affect the level of plant fertility This research was conducted to classify the types of seeds and fertilizers accordingly, in order to obtain high levels of fertility and crop yields. The attributes used in this study were the type of seed, type of soil, type of pest, type of disease, and type of fertilizer. This study uses the Classification Decision Tree method with the C4.5 Algorithm, which is one of the methods in data mining. This method is used to obtain a set of tree-shaped patterns that can separate data classes from one another, which are used for decision making. The result of this research is a website-based system, so that it can be accessed by all users. This system can be used to classify the appropriate types of seeds and fertilizers based on the rules formed by the C4.5 calculation process. From the test results with the number of training data 499 data, the first root that was formed was fertilizer with a gain value of 0.142. The rule that is formed from the test results is that there are 173 rules that match, 120 rules are very suitable. And from 125 test data, there are 108 correct data and 17 error data, with the correct data percentage is 86.4% and the percentage of error data is 13.6%. Keywords : Classification, Decision Tree, C4.5 Algorithm, Agricultural Seed and Fertilizer, Website.
Sistem Informasi Peramalan Penjualan Produk Dengan Menggunakan Metode Fuzzy Time Series Berbasis Web (Study Kasus: CV. Surya Kencana Food) Yusuf, Lutfi; Mashuri, Chamdan; Zein Vitadiar, Tanhella
Inovate Vol 6 No 1 (2021): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v6i1.3165

Abstract

Sales forecasting is a program to forecast future sales based on historical data that aims to reduce the excess in producing goods. This research was conducted at the company CV. Surya Kencana Food, Jln. Brigadier General Kretarto No 189 Jombang 61413, Jombang District, Jombang Regency. In selling goods, the company has difficulty estimating how many sales for the next month, resulting in the company producing goods in excess that are not in accordance with market demand, which results in companies experiencing losses. This study aims to build a computerized system that can help the process of selling goods that can help companies in selling goods in the next month based on historical data. In action research. This research method which consists of four stages consisting of: planning, action, observation and reflection, with the calculation process using the Fuzzt Time Series (FTS) method that uses calculations based on historical data. The results of this study are in the form of a decision support system which is expected to help the company in predicting (predicting) sales of Gerry products in the following month. In the calculation process, forecasting accuracy is done using MAPE to test how accurate the forecasting is. Results of forecasting in December 2019, namely: 13817 with a MAPE value of 9.46%. Keywords: Product Sales, Forecasting, Information System, Fuzzy Time Series
Perancangan Sistem Informasi Prediksi Curah Hujan Pada Kabupaten Jombang Menggunakan Metode Fuzzy Time Series Suhartanto, Martin; Dwi Nuryana, I Kadek; Heru Mujianto, Ahmad
Inovate Vol 6 No 1 (2021): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v6i1.3167

Abstract

Weather and climate information is very important for some people to support life. In agriculture, for example, climate change has a major effect on changing planting patterns. Fuzzy Time Series (FTS), Rainfall prediction is used to understand the intensity of future rainfall that serves as a reference in making the right decisions and preparing to address future problems. In this study using the Fuzzy Time Series (FTS), this method can be used to solve forecasting problems with linguistic historical data and real numbers by converting the real number data into linguistic variables. The results of this study are a website-based system that can predict rainfall in the coming year by using previous rainfall history data as a reference for prediction calculations. from the calculation done by the system in predicting rainfall by using the Fuzzy Time Series method as an example in this silver sub-district produces an average mape value of 0.90 which means it has excellent performance because it produces an average mape forecasting error value of less than 10. Key words: Prediction, Rainy, FTS, website

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