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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Simetris PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal technoscientia Sinkron : Jurnal dan Penelitian Teknik Informatika JIKO (Jurnal Informatika dan Komputer) JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Review Pendidikan dan Pengajaran (JRPP) Jurnal Informatika dan Rekayasa Perangkat Lunak JURNAL TEKNOLOGI TECHNOSCIENTIA Jurnal Pendidikan dan Teknologi Indonesia Journal of Dinda : Data Science, Information Technology, and Data Analytics COMSERVA: Jurnal Penelitian dan Pengabdian Masyarakat Journal of Computers and Digital Business Journal of Intelligent Software Systems Journal of Public Health Concerns Eduvest - Journal of Universal Studies Journal Of Artificial Intelligence And Software Engineering CYBER-Techn(Jurnal Informatika dan Industri) INOVTEK Polbeng - Seri Informatika BHAKTI JIVANA Quality

Andriyani, Widyastuti

Universitas Teknologi Digital Indonesia

Author-ID : 3872781

Religion Aerospace Engineering Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Neuroscience Nursing Public Health Social Sciences Other

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LOGIKA FUZZY SWARM INTELLIGENCE BEE COLONY UNTUK MEMINIMALISASI KEMACETAN TRANSPORTASI Andriyani, Widyastuti; Wardoyo, Retantyo
JURNAL TEKNOLOGI TECHNOSCIENTIA Technoscientia Vol 5 No 2 Februari 2013
Publisher : Lembaga Penelitian & Pengabdian Kepada Masyarakat (LPPM), IST AKPRIND Yogyakarta

This paper uses the concept of fuzzy logics to integrate with bee systems to solve inexact model problems. As an example, in this paper the integration will be used to minimalise the congestion of transportation problems. Bee systems face many problems for decision making when seeking for the best solution, some of them: to determine the next solution components to be added to partial solution, to determine which partial solutions should be left or not, and to determine the same partial solutions without recruiting friends from the same nest. The majority of these selection models is based on the assumption that the decision makers have the ability of processing perfect information, and are always acting rationally and exactly. However, in certain conditions, information is not exact, but is still realistic.

STUDI KOMPARASI MENYIMPAN DAN MENAMPILKAN DATA HISTORI ANTARA DATABASE TERSTRUKTUR MARIADB DAN DATABASE TIDAK TERSTRUKTUR INFLUXDB -, Hendra; Andriyani, Widyastuti
JURNAL TEKNOLOGI TECHNOSCIENTIA Technoscientia Vol 12 No 2 Februari 2020
Publisher : Lembaga Penelitian & Pengabdian Kepada Masyarakat (LPPM), IST AKPRIND Yogyakarta

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The use of structured databases is still very widely used by companies in small and medium scale with the aim of processing data so that from these data conclusions can be drawn to determine a decision. But over time, of course the need for data that continues to grow can make a system run very slowly when using a structured database. That is caused by the amount of data that continues to increase every day, even for certain cases the data can increase every second. For this reason, an unstructured database is needed specifically for storing history data. From some existing unstructured databases, InfluxDB is one of the unstructured databases specifically intended for storing history data and has a very good ability to process data into a matrix for analysis. One of the key factors in an unstructured database is the database structure which is very different and supports to maximize database performance.

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The Prediction on the Students’ Graduation Timeliness Using Naive Bayes Classification and K-Nearest Neighbor Anwarudin Anwarudin; Widyastuti Andriyani; Bambang Purnomosidi DP; Dommy Kristomo
Journal of Intelligent Software Systems Vol 1, No 1 (2022): July
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

The college quality can be seen from the level of punctuality of student graduation. The Prediction on students’ graduation timelines can be used as one of the supporting decisions to evaluate students’ performance. Currently, the Medical Laboratory Technology study program of STIKES Guna Bangsa Yogyakarta does not have tools to predict the level of students’ graduation punctuality early yet. The purpose of this study is to evaluate the application of the Naive Bayes Classification and K-Nearest Neighbor algorithms with predictive modeling of student graduation period. This study applied the academic data from students of the Medical Laboratory Technology study program for the Academic Year (TA) 2015/2016 to 2018/2019. This study utilized an experimental approach by comparing the methods of the Naive Bayes Classification (NBC) and K-Nearest Neighbor (KNN) algorithms. The validation model uses 5-fold Cross Validation, while the evaluation model uses a Confusion Matrix. The results illustrated that the prediction with NBC in this case obtained an accuracy of 96.11%, precision of 82.11% and Recall of 100.00%. Meanwhile, predictions using KNN obtained accuracy of 97.68%, precision of 100.00% and Recall of 86.11%. Thus, KNN is an algorithm with an enhanced level of accuracy to solve the case of predicting the timeliness of students’ graduation of the Medical Laboratory Technology Study Program STIKES Guna Bangsa Yogyakarta

Query Execution Performance Analysis of Column-Oriented Database in Dashboard Bagas Triaji; Widyastuti Andriyani; Totok Suprawoto; Muhammad Agung Nugroho; Rikie Kartadie
Journal of Intelligent Software Systems Vol 1, No 2 (2022): Desember
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

In making reports or dashboards from operational data, problems often occur in the query process with low speed in responding to an output, causing the server to experience overload. This condition often occurs in companies or higher education organizations in managing academic data. This condition can be improved by optimizing the database server by integrating relational databases with column-oriented databases to speed up query responses and save development costs. Based on the experiments that had been carried out, column-oriented has succeeded in optimizing with a significant difference in query execution time and the server does not crash.

Building a Knowledge Graph on Video Transcript Text Data Bagas Triaji; Widyastuti Andriyani; Bambang Purnomosidi DP; Faizal Makhrus
Journal of Intelligent Software Systems Vol 1, No 1 (2022): July
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Youtube is a video platform which not only provides entertainment but also education in which knowledge can be dug based on video transcripts. The results of this knowledge can be formed as a knowledge graph to build a knowledge base that saves storage space. Moreover, it can be used for other purposes such as recommendation systems and search engines. Prosen built a knowledge graph using NLP to extract the text by identifying the subject-verb-object (SVO) and stored in the graph database. The construction of a knowledge graph on a Youtube video transcript was successfully carried out. However, there are still obstacles in the process of extracting text using NLP which is less optimal so it is possible that there is still a lot of knowledge that has failed to be obtained.

Analysis of Determining the Types of Wireless BTS Devices Using the Dude Implementation and Telegram Notifications on Internet Services Provider XYZ Robertus Saptoto; Bambang Purnomosidi DP; Widyastuti Andriyani; Rikie Kartadie
Journal of Intelligent Software Systems Vol 1, No 1 (2022): July
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

ISP XYZ is a company engaged in the field of Internet Service Providers (ISP). Network monitoring is something that an ISP must have in monitoring network router traffic, wireless Base Transceiver Station (BTS) traffic and wireless client traffic. Connections between BTS backbone and BTS use wireless devices. Because currently the main network (backbone) inter BTS to BTS uses wireless devices, sometimes disturbances occur such as frequency interference and high data loads on BTS which lead data distribution to customers disrupted. The factors that affect this incident are the number of similar frequency number usage, the distance between BTS to BTS, the type of wireless device that can no longer carry large data loads as its main source. Telegram makes it possible to send and receive text messages over the internet. In addition, the function of telegram is usable. This research will be used to determine policies for updating wireless devices, especially on the BTS to BTS backbone. Chat, video calls, shared photos and files, telegram supports bots. This bot will later be used to mechanize notifications from the dude application to telegram messages, which of course are connected to the internet. You can provide reports on the use of data traffic, wireless device data resources that are currently implemented.

Data Warehouse to Support the Decision Using Vikor Method Heri Muhrial; Bambang Purnomosidi.D.P; Widyastuti Andriyani; Hamdani Hamdani
Journal of Intelligent Software Systems Vol 1, No 2 (2022): Desember
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Data warehouse is a place where data compilations are stored extensively and periodically. The ability of the data warehouse to integrate data lightens CV. Visi Indonesia Mandiri companies in evaluating and making decisions on operational, strategic and tactical processes. The problem is that the company has not provided a data warehouse yet. Moreover, there is no service to give out the needs of easy, consistent, valid and accurate information on operational data, tactical data and strategic data from the decision-making process at the executive level. The data warehouse architecture was established as decision making using the Vikor method analysis.

Price Intelligence Using K-Means Clustering and Linear Regression, Case Study of Store Dk Nutritionindo at Tokopedia Arma Fauzi; Bambang Purnomosidi DP; Faizal Makhrus; widyastuti Andriyani
Journal of Intelligent Software Systems Vol 1, No 1 (2022): July
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

The ability to find the right price recommendation will determine the fate of product sales in the market. This is necessary to prevent whey concentrate products from being sold in the market and to avoid customers fleeing or switching to other competitors. This study uses a price intelligence approach using the k-means clustering method for price grouping based on the closest competitor and demand forecasting using linear regression to determine fair and competitive prices. The results of the k-means clustering price of 145000 from dk nutritionindo are included in C4. The closest competitor has 7 prices cheaper and 5 prices more expensive. The highest price is 495000 and the lowest price is 90000. The results of the 26th month to 33rd month demand forecasting have 2 graphs up and 6 graphs down. Forecasting confusion matrix test produces 62.5% accuracy, 75% precision, 60% recall. With MAPE = 28.95% according to Lewis (1982) then the influence of forecasting is declared feasible (good enough). Because the trend chart illustrates a decline, it is recommended that the shop lowers the price with a recommended price range from 135000 to 90000.

Determining the Target of Independent Graduation for Beneficiary Families of the Hopeful Family Program Andre Argisitawan; Widyastuti Andriyani; Bambang Purnomosidi DP; Dommy Kristomo
Journal of Intelligent Software Systems Vol 1, No 1 (2022): July
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

The Family Hope Program (Program Keluarga Harapan) or better known as PKH is the conditional social assistance to the Poor Families which are designated as PKH Beneficiary Families. Self-Graduation is one of the goals of the PKH program, Self-Graduation is a condition in which the PKH Beneficiary Families is declared ‘passed’ from PKH participation with their respective awareness. This recommendation system uses the Simple Additive Weighting (SAW) method to calculate the criteria for several website-based alternatives with the Model View Controller concept.

Co-Authors Akhmad Dahlan Andre Argisitawan Anwarudin Anwarudin Arif Setiadi, Rizki Arma Fauzi Asyahri Hadi Nasyuha B.T. Sutrisno Bagas Triaji Bambang P.D.P Bambang Purnomosidi Dwi Putranto Bradika Almandin Wisesa Brahmana, Ivanna Beru Brian Duen Rakly Cucut Hariz Pratomo D P, Bambang Purnomosidi Danny Kriestanto, Danny Dian Tri Wiyanti Dommy Kristomo Domy Kristomo, Domy Duen Rakly, Brian Dwi Wibowo Eny Retna Ambarwati Faizal Makhrus Faizal Makhrus Femi Dwi Astuti Femi Dwi Astuti Fika Pratiwi Firman Noor Hasan Hamdani Hamdani Hendra Hengki Hengki Heri Muhrial Herwantono, Herwantono Hizkia Hendra Rianingsih Istichomah Istichomah Ivónia Fátima Ruas da Silva Kuindra Iriyanta Laksono, Triyan Agung Miftahul Huda MILASARI, LISA ASTRIA Muhammad Ali Sofian Murgi Handari Nenen Isnaeni Nugroho, Daniel C.A. Nugroho, Muhammad Agung Nurohman, Muhamad P.D.P., Bambang Pangestika , Elza Qorina Pereira, Elisabet da Conceição Prisilia Talakua Pujianto Pujianto Purnomosidi D.P, Bambang Purnomosidi Dwi Putranto, Bambang Purnomosidi, Bambang Putra, Fadhlih Girindra Rajie Al Qadri Anwar Rakly, Brian Duen Reni Tri Lestari Retantyo Wardoyo Riadinata Riadinata Rifky Lana Rahardian Rikie Kartadie Robertus Saptoto Roh Bintang Jaya, Mabrur Ruas da silva, Ivonia Fatima Said, Famidin Saputra, Andika Jodhi Saryanto Saryanto Sipayung, Hotma Sadariahta Siti Khomsah, Siti Sri Redjeki Suningrat, Nining Suryanto Suryanto Taufik Ismail Totok Suprawoto Tri Andi, Tri Wibowo, Gunturari Wijayanti, Agnes Erida Wiwi Widayani, Wiwi Yohanni Syahra Yuli Astuti

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