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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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OPTIMASI PENJADWALAN MATAKULIAH MENGGUNAKAN ALGORITMA GENETIKA DI FAKULTAS TEKNOLOGI INFORMASI UNIVERSITAS HASYIM ASY’ARI Ilham Zulhardani, Muhammad; Sujatmiko, Bambang; Faizah, Arbiati
Inovate Vol 4 No 2 (2020): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v4i2.690

Abstract

Scheduling is a process schedule or entering data into a schedule. In academic sector, scheduling is used toschedule course subjects. In the Faculty of Information Technology Hasyim Asy’ari University schedule is madefor the study programs for Bachelor of Computer Science (S1), Bachelor of Information System (S1), and AssociateDegree of Information Management (D3). However there are 4 students academic years in each degree or studyprogram. The room provided is only 5 rooms and lecture time starting from Saturday to Wednesday with lecturehours starting at 08.00 a.m until 6 p.m. Furthermore the scheduling still made by using Microsoft Excel. The casesoften cause a schedule crash. Therefore it is necessary to use an application of scheduling optimation in order tominimize the schedule crash. Optimization problems often solved using genetics algorithm. Genetics algorithm ispretty good to used in scheduling the course subjects because it is able to finish multi-criteria cases and multiobjectivesmodeledasbiologyandevolution.Theresultresearchshowsthattheschedulethathasbeenmadehas anerrorvalueof21,6%withfitnessvalueof0,05andthenumberofschedulecrashis19crashes.Thefitness valueisresultedfromthecombinationofgeneticsparameterthatisthepopulationsize is 100, crossover 0,7,mutation 0,3 and generation 500. The schedule settlement cannot reach a perfect value because in this case theclassroom number is this scheduling is very limited, that is only 5 classrooms. Keywords: Genetics Algorithm, Courses, Optimation, Scheduling
PENGEMBANGAN SISTEM INFORMASI MANAGEMEN MASJID UNTUK PENGURUS MASJID SE-BANJARMASIN UTARA MUHAMMAD, ALI; HIDAYAH, YULIANTI; CITRAWATI LESTARI, NANA
Inovate Vol 4 No 2 (2020): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v4i2.691

Abstract

The mosque is a center for education, teaching, and development of science, a community information center, acenter for the collection and distribution of zakat, infaq, and shodaqoh. Observation results indicate that 80% ofmosques in the North Banjarmasin city have a conventional management and information delivery (not displayedtransparently using information systems). The objective of the study is to facilitating the mosque administrator inmanaging and delivery information about the mosque using the mosque management information system. Theresults of this study showed that the proposed mosque management information system had a 100% informationsystems success in terms of security, content, accuracy and format of the management information system. Thelowest percentage of information systems success is 82% in terms of system quality at ease of use.Keyword: Management, MIS, Mosque.
PENERAPAN ALGORITMA K-MEANS CLUSTERING SEBAGAI STRATEGI PROMOSI PENERIMAAN MAHASISWA BARU PADA UNIVERSITAS HASYIM ASY’ARI JOMBANG Mahmudi, Imam; Dwi Indriyanti, Aries; Lazulfa, Indana
Inovate Vol 4 No 2 (2020): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v4i2.692

Abstract

Admission of new students at the Hasyim Asy'ari University in Jombang is held every year. To more of the newstudents, admissions Committee conducted several promotions as very important early activities such as: online,banners, brochures, school events, and orally with student roles and Alumni. The number of competition infinding new student applicants, requiring the University of Hasyim Asy'ari to conduct analysis of several waysof promotion that have been done so that the promotion strategy can be seen which is more precise and effective.This research will conduct grouping/clustering of districts or cities based on certain attributes in a Web-basedapplication. The method used in this study is a K-means clustering algorithm that can group student data intomultiple clusters based on similar attribute agreements. The attributes used are hometown, online, oral,banners/billboards, brochures and events. At this Peletitian generate a total of 5 clusters (k = 5) with the firstcluster 20 hometown with the most effective promotional media online and oral, the second cluster of 31 Origincities with the most effective promotional media oral and online, the third cluster of 4 cities originating withmedia The most effective promotion of events and banners, the fourth cluster of 15 hometown with the mosteffective promotional media brochures and oral, the fifth cluster 2 hometown with the most effective promotionalmedia oral and event. The results of this study were used as a recommendation to determine a promotionalstrategy based on the promotional media of each cluster formed.Keywords: Promotion strategy, Admission of New Students, K-means Algorithm, Clustering
SISTEM PERAMALAN PENJUALAN TAS PADA TOKO FIRDAUS BAG BERBASIS WEB MENGGUNAKAN METODE MOVING AVERAGE Uswatun Khasanah, Siti; Dwi Indriyanti, Aries; Andriani, Anita
Inovate Vol 4 No 2 (2020): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v4i2.693

Abstract

Sales of bags every year experience a rapid growth, especially for types of school bags, therefore many ofthe bag shops that not only sell one type of school bag, but a variety of school bags, such as those that areoffered in Paradise Stores. Firdaus bag shop sells 17 types of school bags such as, ripper bags, alto bags,character bags etc. The number of bag sales reaches more than 100 pcs per month from all types of bags,but in making sales reports and reporting data the shop owner still uses a manual system. Asking the storeowner to have difficulty adding or subtracting bag data preparation data. The purpose of this research isto study the bag selling system in the web-based paradise Bag Store. The data in this study use 17 types ofbags with the method used in this study is the method of moving average or moving average. Movingaverage is one of the forecasting methods that uses time series data. The period used is period 6.Forecasting errors can be calculated using the MAD and MAPE formulas. The results of this study are abag sales system in the following month. The bag sales data used are January to December 2018 withmoving averages. The result of applying the moving average method is forecasting in January 2019.Forecasting the most bag sales in January 2019 is the sale of large ripper bags with a total of 127 pcs.Forecasting The level of accuracy is generated using MAD and MAPE. MAD for alto palo bags is 5.83while MAPE for alto palo bags is 58.02%.Keywords: Sales, Moving Average, Forecasting Error
APLIKASI PEMETAAN PONDOK PESANTREN BERBASIS WEB DI KABUPATEN JOMBANG Baharudin, Ilham; Sujatmiko, Bambang; Faizah, Arbiati
Inovate Vol 4 No 2 (2020): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v4i2.694

Abstract

Jombang Regency is known by the nickname of the city of santri because there are many Islamic boardingschools which are famous in Indonesia domiciled in this city. At least there are seven large Islamic boardingschools located in the Jombang area. Apart from the strategic geographical location in the city of santri,great figures were born, one of which was the forerunner of the resistance of the community and the santritowards the invaders who were commanded by Hadratussyaikh KH.M Hasyim Asy'ari, the founder ofNahdlotul Ulama and KH. A Wahid Hasyim, 4th President K.H Abdurrahman Wahid. Based on thedescription above, in order to help parents who want to know the geographical location and the teachingsystem in Islamic boarding schools in Jombang, the application of mapping boarding schools is neededwhich can help parents know what kind of boarding school information is in Jombang Regency with 3groups, namely: Salaf Islamic Boarding School, Traditional Islamic Boarding School and Tahfidz IslamicBoarding School and know the geographical location of Islamic boarding schools with website-basedmapping visualization.Keywords: Jombang Regency, Islamic Boarding School, Mapping
PERANCANGAN SISTEM CERDAS CHATBOT ADMIN TOKO ONLINE DENGAN ALGORITMA LEVESHTEIN DISTANCE Ibrahim, Mulyana; Imam Agung, Achmad; Sucipto, Hadi
Inovate Vol 4 No 2 (2020): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v4i2.695

Abstract

The progress of technology has become faster every year, this progress has impact so many aspec of humanslife. One of the aspec that change so much in this days is online shopping where the seller sell their producton the internet and the customer buy it from the internet. The phenomenon make the need of cutomer servicebecome more crucial than before. Because of this phenomenon this research try to make the system thatcan change customer service with chatbot. The method that used in this research is a string matching withLevenshtein Distance algorithm. After the string matching has a result, the result that will be manipulatewith natutal language processing so the customer who use the system will feel talk with human rather thanwith the machine. The resault of this research is a system that can make a conversation with humanlanguage. From the test indicating the system can handle a couples user in the same time, and from the testgive a resault that system can understand the word that being inputed.Keyword: Chatbot, Levenshtein Distane(LD), Natural Language Processing(NLP).
PENERAPAN ANALYTICAL HIERARCHY PROCESS (AHP) UNTUK PENENTUAN DOSEN BERPRESTASI BERDASARKAN TRIDHARMA PERGURUAN TINGGI Zuchrotunisa; Sujatmiko, Bambang; Faizah, Arbiati
Inovate Vol 4 No 2 (2020): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v4i2.696

Abstract

The assesment of lecturers’ performance to determine the outstanding lecturer is needed to know theresult of lecturers’ performance in doing all the teaching and learning process in the institution wherethe lecturers work. To obtain the lecturers’ highest ranking, the lecturers’ performance is evaluated byusing AHP. The software of decision support system is used with Analytical Hierarchy Process (AHP)consisting of three criteria: research, community service and some assessment indicators. The lecturersof technology and information faculty become the sample. After knowing the parameter. For the nextsteps, system requirement are analyzed, manipulating the knowledge, applying the method AnalyticalHierarchy Process and last but not least testing the system. The result of this research is an applicationthat can make the university assess the lecturers’ performance in the form of ranking become easier. Thehighest lecturer score of this research is 0.9343 that obtained from the system.Keywords: Decision Support System, AHP, Lecturers’ Performance
PENERAPAN SISTEM PENDUKUNG KEPUTUSAN METODE TECHNIQUE FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS) REKOMENDASI SISWA BERPRESTASI UNTUK DIAJUKAN KE KELAS UNGGULAN Wahyu Saputro, Angga; Rahman Prehanto, Dedy; Andriani, Anita
Inovate Vol 3 No 2 (2019): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v3i2.734

Abstract

Madrasah tsanawiyah negeri is an islamic school which have the same level as junior high school.Sometimes it requires outstanding students to be recommended to a special class, which not only considersacademic score, but also non-academic of each student. To avoid subjective decision, it need DecisionSupport System (DSS) in providing student recommendations.One of DSS methods to solving a problem is TOPSIS. TOPSIS is based on the concept that the chosenalternative should have the shortest distance from the positive ideal solution as well as the longest distancefrom the negative ideal solutionThis study focuses on providing recommendation of outstanding students at MTsN TambakberasJombang. Observations data are collected from students grade 7 and processed using TOPSIS method. Thecriteria variables are academic score, nonacademic score, extra score, attitude score, attendance score,communication skill, and expertness. The result of preference score is generated by system then comparedwith result of manual. The comparison obtained an accuracy of 99.75%. Then, based on blackbox testingit can be concluded that the system is feasible to be used in this study case.Keywords: DSS, TOPSIS, Recommended Student, Outstanding Class.
SISTEM PENDUKUNG KEPUTUSAN CALON PENERIMA BEASISWA KURANG MAMPU PADA SMK SULTAN AGUNG 1 MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING Fikandda, Johan; Rahman Prehanto, Dedy; Yuli Setyawan, Aditya
Inovate Vol 3 No 2 (2019): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v3i2.735

Abstract

Scholarship of underprivileged is a grant provided by goverment or institutions to students fromunderprivileged family. Scholarship covering all levels of education, whether student still in primary schooluntil college. The selection of scholarship is obtained if students meet the specified criteria. Scholarshipselection in the SMK Sultan Agung 1 Jombang sometimes not accordance with assessment results. Manyrich student are able to get scholarship while underprivileged students don’t get scholarship. The largenumber of students applying for scholarship make it difficult to make a decision. Based on this, build adecision support system can assist SMK Sultan Agung 1 Jombang to manage the selection of scholarshipbased on criteria. Decision Support System are build using PHP as programming language and MySQL asdatabase. This system is called Simple Additive Weighting (SAW). SAW method is performing a weightedsum of performance ratings on each alternative on all attributes. This method are suitable to be used inmaking decision support system because the result obtained accordingly. The System do ranking from thebest alternative of the student who applied scholarship. System has been tested to determine performanceof the system along with functions contained in the system. Testing is done using Blackbox testing method.This test done by trying the existing function on the system, whether it is suitable with the expected resultby the school. The result obtained from Blackbox testing indicate that the system created has been runningwell.Keyword : Decision Support System, Simple Additive Weighting, Scholarship
DETEKSI MINAT BELI PELANGGAN TERHADAP PRODUK PAKET INTERNET MENGGUNAKAN ALGORITMA NAÏVE BAYES CLASSIFIER Syahrul Mubarok, Ahmad; Rahman Prehanto, Dedy; Ali, Mahrus
Inovate Vol 3 No 2 (2019): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v3i2.737

Abstract

The need for communication technology that can find out the customer's buying interest is something that isneeded by the company, the goal is that the company can obtain consideration regarding product sales andappropriately take a policy regarding pricing of a product, the amount of product supply and so on. The naïvebayes classifier method is sufficient to be able to find out how much the customer's buying interest in aninternet package product is by analyzing the results of past sales, meaning that the Naive Bayes algorithmcan predict future opportunities based on past experience, by defining each class from all attribute. The naivebayes classification is assumed that there is or not a certain feature and a class has nothing to do with othercharacteristics and classes. This study defines several characteristics, namely operator, quota, active periodand product price. From the results of this study is the author can find the value of accuracy from the resultsof calculating interest and not by comparing the results of predictions with actual results outside the trainingdata. Based on data on internet package product sales as training data, the Naive Bayes method successfullyclassifies 10 product data with 858 transaction data as training data and 10 product data with 115 transactiondata as test data. From the analysis of all test data and training data, the truth ratio is 8/10, which is 8 out of10 products with predictive values that are of true value. So that the accuracy value is 80% and to find outthe customer's buying interest by calculating the sales data that has been past with the provisions and inaccordance with the specified label, the results of this prediction are expected to be a better policyconsideration for the sales business.Keywords: naïve bayes classifier, sales of internet package products.

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