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Journal : bit-Tech

Selection of the Best Lecturers using the AHP (Analytical Hierarchy Process) and TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution): Case Study of STMIK Insan Pembangunan Winny Purbaratri; Moedjiono Moedjiono; Moch. Fajar Purnomo Alam
bit-Tech Vol. 1 No. 2 (2018): Data and Information Quality
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (607.965 KB) | DOI: 10.32877/bt.v1i2.38

Abstract

STMIK Insan Pembangunan is a College that was established in 1990, located in Tangerang Regency. Supported by 41 Lecturer staff. Lecturers have the position as professional staff at the higher education level who are appointed in accordance with the laws and regulations. Lecturers are educators who provide a number of knowledge to students in universities or universities. The best lecturer selection system is used to support learning and teaching activities in the campus so that students are competent in the field of concentration taken. So it is needed teaching staff or lecturers who are competent in their fields, in this case to meet the criteria of the competent lecturer is needed a system that supports in this case deciding which lecturers are considered the best. The process of selecting the Best Lecturers in the current system is that there is a shortage that takes a long time to process the results of the questionnaire data and only uses one of the criteria of the Tridarma of Higher Education, namely Education and Teaching. So that the resulting decision is not yet valid. In this study a Decision Support System (DSS) will be made where the decision support system can help a person in making accurate and well-targeted decisions. The method used is AHP to calculate the weight of each criterion and TOPSIS to rank each alternative based on each criterion. The results obtained in this study are a system that is able to produce the best rank of lecturers in STMIK Insan Pembangunan.
Decision Support System Using AHP and Topsis Methods in Determining Wedding Packages Achmad Syauqi; Winny Purbaratri
bit-Tech Vol. 3 No. 3 (2021): Remote Delivery
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v3i3.214

Abstract

Choosing a wedding package is always a problem for the prospective bride and groom. The decision support system helps the wedding organizer to make it easier for consumers to choose a wedding package. In this case, the researcher uses the AHP method to find the weight of the criteria and the TOPSIS method to rank alternative consumer choices. The criteria used in this study were 7 (seven), Makeup, Clothing, Catering, Documentation, Decoration, Number of Guests and Price. The results obtained from this study are that the system is able to produce a ranking order of wedding package options in a fast time and get the right choice
IoT Security Attacks on the Public Sector: Systematic Literature Review Fandan Dwi Nugroho Wicaksono; Winny Purbaratri; Moch Fajar Purnomo Alam; Agnes Novita Ida Safitri
bit-Tech Vol. 7 No. 1 (2024): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v7i1.1627

Abstract

The primary objective of this study is to examine security threats that specifically target the Internet of Things (IoT) used in the Public Sector. This sector is widely acknowledged as a crucial element of the fourth industrial revolution. The high volume of intelligent devices employed in the public sector, which are linked in the Internet of Things (IoT), and each of them transmits sensitive data in numerous instances, makes security of utmost importance. The objective of this study is to categorize various forms of security attacks and propose strategies to mitigate security breaches through many approaches. This study employed a systematic review, which is a methodical examination of current literature. The data synthesis methodology in this study consisted of comparing 15 literature sources that had been evaluated for quality and satisfied the specified criteria for inclusion and exclusion. The utilized database sources include renowned platforms such as Scopus, ACM, and IEEE. The present study employs a qualitative methodology, specifically utilizing the perspectives of two information security specialists to examine the existing literature. The findings of this study have made a meaningful contribution to the field of public sector. This study categorizes four types of assaults against Public Sector IoT: 37% Denial-of-Service (DoS) attacks, 31% Malware attacks, and 19% Phishing attacks. System attacks account for 13% of all system attacks. By contrast, 50% of the security attack mitigation strategies rely on authentication, 36% on Secure Communication, and 14% on Application Security.
Decision Support System for Recommendation Sharia Banking Investment Products Using Simple Additive Weighting (SAW) Mukti, Muhammad Ivan; Purbaratri, Winny; Pratiwi; Istiyowati, Lucia Sri; Ranien, Zahwa Bunga
bit-Tech Vol. 7 No. 2 (2024): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v7i2.1872

Abstract

The swift expansion of Islamic banking has resulted in the creation of many investment products, such as mudharabah deposits, sukuk, and Islamic mutual funds, all compliant with sharia rules. Notwithstanding this advancement, the customers' inadequate financial literacy presents considerable obstacles in identifying appropriate investment alternatives that correspond with their objectives and risk appetite. This work seeks to fill this gap by creating a Decision Support System (DSS) that employs the Simple Additive Weighting (SAW) method to aid users in making educated decisions on Islamic banking investments. The SAW technique was selected for its straightforwardness and efficacy in normalizing data and assessing alternatives according to established criteria, including profit potential, risk level, investment duration, and compliance with sharia principles. The research encompassed multiple phases, including the identification of evaluation criteria, the collection and analysis of pertinent data, and the application of the SAW method to rank investment choices. The DSS effectively delivered precise and dependable suggestions, designating Sharia Deposits as the optimal investment choice due to its robust agreement with the established criteria. The results underscore the system's capability to improve financial inclusion and literacy, especially in Indonesia, where comprehension of sharia-compliant financial products is still inadequate. Future improvements to the DSS involve the incorporation of real-time data and the expansion of its application to include more financial industries, such as insurance and microfinance. This study highlights the importance of utilizing technology to address deficiencies in financial literacy and facilitate the sustainable development of the Islamic banking sector.
Simple Additive Weighting Method for Internet Service Provider Vendor Selection Decision Support System Rafli, Muhammad; Purbaratri, Winny; Safitri, Agnes Novita Ida; Indiarto, Budi; Wicaksono, Fandan Dwi Nugroho
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2423

Abstract

The increasing demand for high-speed, stable, and reliable internet services at IKPIA Perbanas—driven by educational, research, and administrative needs—has posed challenges in selecting the most suitable Internet Service Provider (ISP). With numerous vendors offering diverse bandwidth packages and pricing, a structured and objective decision-making method is essential. This study proposes the development of a web-based Decision Support System (DSS) using the Simple Additive Weighting (SAW) method to assist in the selection of the most appropriate ISP. The research adopts a quantitative approach, utilizing both primary and secondary data. Primary data were collected through a questionnaire distributed via Google Forms to five experts comprising the tender selection team. Secondary data were obtained through observation and interviews. Seven key criteria were identified: bandwidth, benefit, experience, service level agreement (SLA), support, hardware, and security. Each criterion was weighted and evaluated using the SAW method. The resulting system calculated normalized performance ratings and preference values for each vendor. The analysis showed that PT. B achieved the highest preference value (0.97), followed by PT. E (0.93), indicating PT. B as the most suitable vendor. The developed system successfully supports transparent, criteria-based ISP selection, enhancing the efficiency and objectivity of the procurement process at IKPIA Perbanas.