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All Journal Journal of Dinda : Data Science, Information Technology, and Data Analytics Journal of Intelligent Software Systems CYBER-Techn(Jurnal Informatika dan Industri) INOVTEK Polbeng - Seri Informatika BHAKTI JIVANA

Widyastuti Andriyani

Unknown Affiliation

Author-ID : 5670107

Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Nursing

Published : 9 Documents Claim Missing Document

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Articles

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

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.

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.

Comprehensive Lakehouse Data Architecture Model for College Accreditation Nenen Isnaeni; Bambang Purnomosidi Dwi Putranto; Widyastuti Andriyani; Siti Khomsah
Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 5 No 1 (2025): February
Publisher : Research Group of Data Engineering, Faculty of Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/dinda.v5i1.1759

Accreditation is an assessment activity that determines the feasibility of study programs at a university. College accreditation data comes from various sources and includes multiple data types: semi-structured, unstructured, or structured. Over time, the volume of data will continue to grow and develop, so there is a possibility of data redundancy and a long time to collect the data needed for accreditation activities. The solution is integrating data. This research aims to design a data architecture to facilitate the management of university accreditation data using the Lakehouse data architecture model. All data types can be stored on one platform in the Lakehouse data architecture. In this research, the identification, integration, and data transformation process for university accreditation data is carried out. The data used in this research is academic data in which there are with. The study's results provide an overview of the data flow process in the Lakehouse data architecture model to help better manage university accreditation data. This architecture also supports real-time data analysis so that the accreditation process can be carried out more effectively and efficiently. Keywords: accreditation, data analysis, data architecture, data lakehouse, data warehouse

Decision Support System for Business Location Selection using the AHP Method Based on Android Hizkia Hendra Rianingsih; Widyastuti Andriyani
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 1 (2025): March
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/z5xfh608

The selection of a strategic business location is a crucial factor in the success of an enterprise. However, the decision-making process for choosing a location often involves various complex criteria that require careful analysis. This study aims to develop an Android-based Decision Support System (DSS) to assist entrepreneurs in selecting an optimal business location using the Analytical Hierarchy Process (AHP) method. AHP is chosen for its ability to break down complex problems into a hierarchy and quantitatively evaluate each criterion. The system is designed to allow users to easily access and operate the DSS through mobile devices. The criteria used in the location selection process include accessibility, cost, demographics, competition, security, infrastructure, regulations, and growth potential. Each criterion is weighted using pairwise comparisons, enabling objective and comprehensive assessments. The Android-based implementation allows for flexibility, enabling users to make decisions efficiently anytime and anywhere. System testing results indicate that the application can provide accurate business location recommendations based on the desired criteria, and it features a user-friendly interface. This Android-based DSS is expected to be a practical solution for supporting business decision-making processes quickly and accurately.

A PELATIHAN DASAR PENGGUNAAN AI GENERATIF UNTUK MEMBANTU PRODUKSI KONTEN UMKM Widyastuti Andriyani; Prisilia Talakua; Lisa Astria Milasari; Firman Noor Hasan
Komunikasi Vol 2 No 2 (2025): Volume 2 No 2 Agustus 2025
Publisher : Forum Komunikasi Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65055/bhaktijivana.v2i2.36

The purpose of this community service research is to measure the effectiveness of basic training on the use of generative AI in assisting content production for MSMEs in Yogyakarta. This training was designed to address the main challenges faced by MSMEs, namely limited resources and expertise in creating consistent and high-quality digital marketing content. Through an interactive workshop method focused on hands-on practice, 25 MSME actors were educated on the concept of generative AI, prompt engineering techniques, and the utilization of AI tools. The evaluation results showed a significant increase in participant understanding, content quality, and time efficiency, where participant understanding jumped from 15% to 95%, content quality increased by 60%, and time efficiency improved by 40%. In conclusion, this training proves that the integration of generative AI is an effective strategic solution for empowering MSMEs, enhancing their competitiveness, and fostering sustainable business growth in the digital era.

PENILAIAN PRESTASI KINERJA PIMPINAN KANTOR CABANG PEMBANTU (KCP) DENGAN MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING (SAW) STUDI KASUS PADA KSPPS TUNAS ARTHA MANDIRI CABANG NGANJUK Dwi Wibowo; Widyastuti Andriyani; Bambang P.D.P
CYBER-TECHN Vol. 19 No. 01 (2025): CYBER-Techn
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Penilaian Kinerja (Performance Appraisal) adalah suatu proses yang memungkinkan organisasi mengetahui, mengevaluasi, mengukur dan menilai kinerja anggota-anggotanya secara tepat dan akurat. Kegiatan ini sangat terkait dan berpengaruh terhadap keefektifan pelaksanaan aktivitas-aktivitas sumberdaya manusia dalam perusahaan, seperti promosi, kompensasi, pelatihan (training), pengembangan manajemen karir dan lain-lain.Hal ini disebabkan karena fungsi penilaian kinerja dapat memberikan informasi penting kepada perusahaan untuk memperbaiki keputusan dan menyediakan umpan balik kepada para karyawan tentang kinerja mereka yang sesungguhnya. Implementasi penilaian prestasi dan kinerja pimpinan KCP pada KSPPS Tunas Artha Mandiri Cabang Nganjuk selama ini masih manual dan belum menggunakan sistem pendukung keputusan sehingga data yang di hasilkan tidak akurat dan membutuhkan waktu yang cukup lama. Akibatnya jika digunakan dalam pengambilan keputusan tidak sesuai dan menimbulkan masalah seperti pengelolaan yang tidak transparan, penurunan kualitas dan kinerja pimpinan KCP.Penulis menerapkan dan mengimplementasikan metode Additive Weighting methods (SAW) untuk mengukur penilaian prestasi dan kinerja pimpinan Kantor Cabang Pembantu pada KSPPS Tunas Artha Mandiri Cabang Nganjuk. Dengan tujuan sistem pendukung keputusan ini dapat memberikan informasi dan rekomendasi serta data penilaian kinerja yang akurat dan efisian.

Co-Authors Andre Argisitawan Anwarudin Anwarudin Arma Fauzi Bagas Triaji Bambang P.D.P Bambang Purnomosidi Dwi Putranto Dommy Kristomo Dwi Wibowo Faizal Makhrus Faizal Makhrus Firman Noor Hasan Hizkia Hendra Rianingsih MILASARI, LISA ASTRIA Nenen Isnaeni Prisilia Talakua Rikie Kartadie Robertus Saptoto Siti Khomsah, Siti

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