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All Journal SINTECH (Science and Information Technology) Journal JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jusikom: Jurnal Sistem Informasi Ilmu Komputer Cyber Security dan Forensik Digital (CSFD) Journal of Dinda : Data Science, Information Technology, and Data Analytics Journal of Intelligent Software Systems Journal Of Artificial Intelligence And Software Engineering

Bambang Purnomosidi Dwi Putranto

Universitas Teknologi Digital Indonesia

Author-ID : 8145158

Computer Science & IT Decision Sciences, Operations Research & Management Education

Published : 16 Documents Claim Missing Document

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Articles

Title

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.

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.

ANALYSIS AND DESIGN OF DATA WAREHOUSE AND DATA MART BUDGET Hendra Maryanto; Bambang Purnomosidi Dwi Putranto; Rikie Kartadie; Muhammad Guntara; Robertus Saptoto
Journal of Intelligent Software Systems Vol 2, No 1 (2023): July
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiss.v2i1.927

University as higher education institutions must be able to manage budgets properly. The budget is a future financial plan which includes the expectations of university management. This research will design a data warehouse, which is a place where data can be stored on a large scale. In this research, a data warehouse will be designed as a place to store budget data. The method applied in this study is the Kimball method with a nine-step methodology. The result of this research is a data warehouse design and budget data mart

IOT BASED SOIL MOISTURE MONITORING AND SOIL MOISTURE PREDICTION USING LINEAR REGRESSION (CASE STUDY OF VINCA PLANTS) Kuindra Iriyanta; Bambang Purnomosidi Dwi Putranto; Widyastuti Andriyani
Journal of Intelligent Software Systems Vol 2, No 1 (2023): July
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiss.v2i1.929

Soil moisture is something that becomes important. Indonesia as an agricultural country, most of the population has a profession as a farmer. In agriculture, one of the important parts is the water composition in the soil or soil moisture. One attempt to maintain soil moisture is to provide sufficient water intake to the soil. However, in practice, it is sometimes complicated for farmers to do proper irrigation of their agricultural land. This humidity condition will ultimately determine the success of vinca plant cultivators. The accuracy of giving water both in terms of time management and volume are two things which are an important focus of vinca crop growing. This system is designed using a humidity sensor which is used to measure the moisture composition contained in the soil, and an air temperature sensor. The NodeMCU ESP2866 microcontroller acts as a link between Google spreadsheet sensors. NodeMCU ESP2866 will send humidity and temperature sensor reading data to Google spreadsheets using a RESTfull API which can connect one application to another. The sensor data is then saved to Google spreadsheet and processed using the linear regression method. The processing results will be displayed on the Google Data Studio dashboard. The output of this process is to provide information about soil moisture conditions, notification of soil moisture conditions if it is too dry or damp, thus the prevention of the death of vinca plants can be carried out. The benefit for users is that they can carry out periodic and real-time monitoring by simply using the Telegram instant messaging application, which is expected to reduce the risk of plant death due to drought or excessive watering

Polynomial Regression Method and Support Vector Machine Method for Predicting Disease Covid-19 in Indonesia Bambang Purnomosidi Dwi Putranto; Moh. Abdul Kholik; Muhammad Agung Nugroho; Danny Kriestanto
Journal of Intelligent Software Systems Vol 2, No 1 (2023): July
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiss.v2i1.931

The COVID-19 pandemic has become a major threat to the entire country. According to the WHO report, COVID-19 is a severe acute respiratory syndrome transmitted through respiratory droplets resulting from direct contact with patients. This study of data history is then processed using data mining prediction methods, namely the Polynomial Regression method compared to the Support Vector Machine method. Of the two methods will be sought the most accurate method by testing accuracy with MAE, MSE, and also MAPE to get the results of covid-19 predictions in Indonesia. Based on the comparison of test results through various scenarios against both methods, the Polynomial Regression method obtained the smallest test value, resulting in an accuracy value of MAE = 4146.025749867596, MSE = 19031800.02642069, MAPE = 0.006174164877416524. Polynomial regression is the best-recommended method

A Decision Model to Support the Selection of SENKOM Personnel Using the Profile Matching Method with the Capability of Cyber Security I Nyoman Oka Semadi; Domy Kristomo; Bambang Purnomosidi
Journal of Intelligent Software Systems Vol 2, No 2 (2023): December 2023
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiss.v2i2.1135

The very rapid development of information technology has brought tactical and strategic advantages, but it can also be a potential attack from opposing parties on the information and communication systems and networks used, thus opening the way for the emergence of a new war, namely cyber warfare. Cyber attacks are a new threat to Adisutjipto Air Base, which targets vital parts that can impact the organization and make the command and control system ineffective and inefficient. One of the important elements of Adisutjipto Lanud in facing cyber attacks is the readiness of data and communication network security personnel. In the direct or conventional personnel selection process, it is not possible to see the abilities possessed by prospective data security personnel, both in terms of skills, management aspects, analytical aspects, competency weight, and so on. A decision support system can be used to assist decision-making based on existing criteria. This research is limited to only considering the selection of personnel who will become members of komlek or senkom who are responsible for data security and communications networks at Adisutjipto Air Base. In this research, the method used is the profile matching method. The concept of the profile matching method is to compare the selection using the conventional method with the decision support system method in selecting komlek/senkom personnel as cyber security personnel so that differences in competency can be identified, also called GAP (Gross Across Product). The smaller the GAP produced, the greater the weight of the value. large, this means that personnel who meet the requirements have a greater chance of someone occupying that position. The final result of this research is to obtain ranking information for each cyber security candidate based on profile matching calculations to be able to carry out tasks optimally in securing data and networks at Adisutjipto Air Base.

Co-Authors Almagribi, Ahmad Bilal Andre Argisitawan Andriyani, Widyastuti Anwarudin Anwarudin Arma Fauzi Bagas Triaji Cucut Hariz Pratomo Danny Kriestanto Dommy Kristomo Domy Kristomo Faizal Makhrus Faizal Makhrus Femi Dwi Astuti Hamdani Hamdani Hendra Maryanto Heri Muhrial I Nyoman Oka Semadi Kuindra Iriyanta Moh. Abdul Kholik Muhammad Guntara Muhammad Najib Nenen Isnaeni Nugroho, Muhammad Agung Rikie Kartadie Robertus Saptoto Robertus Saptoto Siti Khomsah, Siti Sri Redjeki Widyastuti Andriyani

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