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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Charity : Jurnal Pengabdian Masyarakat Journal of Informatics and Communication Technology (JICT) Teknologika SOROT: Jurnal Pengabdian Kepada Masyarakat Multifinance Journal of Informatics and Communication Technology (JICT)
Nanang Cahyadi
Universitas Telkom
Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Social Sciences Other

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BER Performance Analysis Over AWGN Channeling For GFSK Modulation To Transmitting Unstructured Data Nanang Cahyadi
Journal of Informatics and Communication Technology (JICT) Vol 4 No 2 (2022)
Publisher : PPM Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52661/j_ict.v4i2.139

Abstract

The first step to enable the optimize the use of information exchange radio-based could be started by providing research on supporting devices. Research on supporting devices and their application, especially in providing service to exchange text-based information is crucial and opens up chances to solve the rest challenges such as signal power, data transfer speed, and security. This research aims to evaluate signal behavior from design information text-based exchange using radio transmission. To achieve the goal, this research adopts a quantitative methodology by comparing theoretical results and simulation results of the design. tuning samples per symbol could give better BER with lower EbNo. The data also demonstrated great results that show using 2 samples per symbol could deliver the best performance that has lower BER and lowest EbNo compared to the rest of the data, including the estimated BER using coherent FSK. It affects the GFSK signal not only very smoothly compared to the FSK signal, but also being able to achieve a minimum BER with the IEEE standard without requiring excessive energy by simply setting samples per symbol at 2. This can be seen from the results of BER 10-3 with energy EbNo was 6.5 dB.
A Comparative Study and Analysis of Forensic Artifacts of WhatsApp and Telegram on Android Devices Rana Zaini Fathiyana; Yudiansyah -; Nanang Cahyadi; Dinda Jaelani Hidayat
Journal of Informatics and Communication Technology (JICT) Vol 4 No 2 (2022)
Publisher : PPM Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52661/j_ict.v4i2.143

Abstract

Numerous instant messaging are available for mobile devices as a cheaper alternative over operator-based text messaging via SMS. Furthermore, instant messaging allow the user to exchange textual messages, images, audio, and videos. However, the ease offered by instant messaging also had a negative impact including making instant messaging as a criminal land. This paper focuses on conducting forensic data analysis of two popular instant messaging applications on Android smartphones; WhatsApp and Telegram. In this analysis, we use open-source tools and software applied on non-rooted Android devices. By using the result, an analyst will be able to read, and reconstruct the chronology of the messages and the list of contact and also know the difference in data structures obtained from these two instant messaging applications.
A Literature Review for Understanding the Development of Smart Parking Systems Nanang Cahyadi; Pietra Dorand; Nurwan Reza Fachrur Rozi; Laksamana Aidzul Haq; Refsi Indra Maulana
Journal of Informatics and Communication Technology (JICT) Vol 5 No 1
Publisher : PPM Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52661/j_ict.v5i1.196

Abstract

Smart parking systems that use AI, data analytics, and IoT are a result of urbanization and rising automobile utilization. These systems are designed to enhance user experience, shorten search times, and make the most of available space. AI analyzes real-time data, proposes open places, and projects demand in the future. Infrastructure costs, stakeholder cooperation, and system compatibility continue to be issues, nevertheless. To maintain user confidence, privacy, and ethical usage in the study of smart parking systems, in-depth literature reviews are essential. The systematic literature review (SLR) method was used to examine AI-based smart parking solutions, such as wireless sensor networks, ultrasonic sensor nodes, reservation-based systems, intelligent parking guidance, IoT-based on-street infraction monitoring, central parking management systems, and energy-efficient automated solutions. Budgetary restrictions, stakeholder participation, interoperability concerns, data privacy, security, and moral ambiguities are all problems. To test scenarios, understand rules, processes, and algorithms in limited contexts, researchers need to develop reliable outdoor sensor and data technologies for outside application.
BER Performance Analysis Over AWGN Channeling For GFSK Modulation To Transmitting Unstructured Data Nanang Cahyadi
Journal of Informatics and Communication Technology (JICT) Vol. 4 No. 2 (2022)
Publisher : PPM Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52661/j_ict.v4i2.139

Abstract

The first step to enable the optimize the use of information exchange radio-based could be started by providing research on supporting devices. Research on supporting devices and their application, especially in providing service to exchange text-based information is crucial and opens up chances to solve the rest challenges such as signal power, data transfer speed, and security. This research aims to evaluate signal behavior from design information text-based exchange using radio transmission. To achieve the goal, this research adopts a quantitative methodology by comparing theoretical results and simulation results of the design. tuning samples per symbol could give better BER with lower EbNo. The data also demonstrated great results that show using 2 samples per symbol could deliver the best performance that has lower BER and lowest EbNo compared to the rest of the data, including the estimated BER using coherent FSK. It affects the GFSK signal not only very smoothly compared to the FSK signal, but also being able to achieve a minimum BER with the IEEE standard without requiring excessive energy by simply setting samples per symbol at 2. This can be seen from the results of BER 10-3 with energy EbNo was 6.5 dB.
A Comparative Study and Analysis of Forensic Artifacts of WhatsApp and Telegram on Android Devices Rana Zaini Fathiyana; Yudiansyah -; Nanang Cahyadi; Dinda Jaelani Hidayat
Journal of Informatics and Communication Technology (JICT) Vol. 4 No. 2 (2022)
Publisher : PPM Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52661/j_ict.v4i2.143

Abstract

Numerous instant messaging are available for mobile devices as a cheaper alternative over operator-based text messaging via SMS. Furthermore, instant messaging allow the user to exchange textual messages, images, audio, and videos. However, the ease offered by instant messaging also had a negative impact including making instant messaging as a criminal land. This paper focuses on conducting forensic data analysis of two popular instant messaging applications on Android smartphones; WhatsApp and Telegram. In this analysis, we use open-source tools and software applied on non-rooted Android devices. By using the result, an analyst will be able to read, and reconstruct the chronology of the messages and the list of contact and also know the difference in data structures obtained from these two instant messaging applications.
A Literature Review for Understanding the Development of Smart Parking Systems Nanang Cahyadi; Pietra Dorand; Nurwan Reza Fachrur Rozi; Laksamana Aidzul Haq; Refsi Indra Maulana
Journal of Informatics and Communication Technology (JICT) Vol. 5 No. 1
Publisher : PPM Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52661/j_ict.v5i1.196

Abstract

Smart parking systems that use AI, data analytics, and IoT are a result of urbanization and rising automobile utilization. These systems are designed to enhance user experience, shorten search times, and make the most of available space. AI analyzes real-time data, proposes open places, and projects demand in the future. Infrastructure costs, stakeholder cooperation, and system compatibility continue to be issues, nevertheless. To maintain user confidence, privacy, and ethical usage in the study of smart parking systems, in-depth literature reviews are essential. The systematic literature review (SLR) method was used to examine AI-based smart parking solutions, such as wireless sensor networks, ultrasonic sensor nodes, reservation-based systems, intelligent parking guidance, IoT-based on-street infraction monitoring, central parking management systems, and energy-efficient automated solutions. Budgetary restrictions, stakeholder participation, interoperability concerns, data privacy, security, and moral ambiguities are all problems. To test scenarios, understand rules, processes, and algorithms in limited contexts, researchers need to develop reliable outdoor sensor and data technologies for outside application.
Enhancing SQL Injection Attack Prevention: A Framework for Detection, Secure Development, and Intelligent Techniques Nanang Cahyadi; Syifa Nurgaida Yutia; Pietra Dorand
Journal of Informatics and Communication Technology (JICT) Vol. 5 No. 2 (2023)
Publisher : PPM Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52661/j_ict.v5i2.233

Abstract

SQL injection attacks (SQLIAs) pose increasing threats as more organizations adopt vulnerable web applications and databases. By manipulating queries, SQLIAs access and destroy confidential data. This paper delivers three contributions around improving SQLIA detection research: first, a literature review assessing current detection/prevention systems to produce an SQL injection detection framework; second, specialized deep learning models optimizing session pattern analysis and feature engineering to enhance performance; third, comparing proposed models against previous defenses to surface promising research directions. Results highlight opportunities like real-time systems generalizing across attack variants through emerging techniques. Additionally, with attack complexity rising, systematized SQLIA investigation is warranted. Despite extensive study, current perspectives lack cohesive guidance informing mitigation strategies. Therefore, a framework is proposed holistically mapping knowledge gaps around contemporary SQLIAs, seminal threats in web applications, and security solutions. Furthermore, a multi-faceted framework examines research trends divided into hardening existing apps, detecting attacks on production systems, and integrating secure development practices. Literature suggests comprehensive resilience requires concurrent strength across these areas. Finally, future work remains in integrated frameworks, deep reinforcement learning adoption, automated AI auditing, and differential privacy to advance real-world SQL injection detection and prevention.
A Literature Review for Understanding the Development of Smart Parking Systems Cahyadi, Nanang; Dorand, Pietra; Rozi, Nurwan Reza Fachrur; Haq, Laksamana Aidzul; Maulana, Refsi Indra
Journal of Informatics and Communication Technology (JICT) Vol. 5 No. 1
Publisher : PPM Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52661/j_ict.v5i1.196

Abstract

Smart parking systems that use AI, data analytics, and IoT are a result of urbanization and rising automobile utilization. These systems are designed to enhance user experience, shorten search times, and make the most of available space. AI analyzes real-time data, proposes open places, and projects demand in the future. Infrastructure costs, stakeholder cooperation, and system compatibility continue to be issues, nevertheless. To maintain user confidence, privacy, and ethical usage in the study of smart parking systems, in-depth literature reviews are essential. The systematic literature review (SLR) method was used to examine AI-based smart parking solutions, such as wireless sensor networks, ultrasonic sensor nodes, reservation-based systems, intelligent parking guidance, IoT-based on-street infraction monitoring, central parking management systems, and energy-efficient automated solutions. Budgetary restrictions, stakeholder participation, interoperability concerns, data privacy, security, and moral ambiguities are all problems. To test scenarios, understand rules, processes, and algorithms in limited contexts, researchers need to develop reliable outdoor sensor and data technologies for outside application.
Enhancing SQL Injection Attack Prevention: A Framework for Detection, Secure Development, and Intelligent Techniques Cahyadi, Nanang; Nurgaida Yutia, Syifa; Dorand, Pietra
Journal of Informatics and Communication Technology (JICT) Vol. 5 No. 2 (2023)
Publisher : PPM Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52661/j_ict.v5i2.233

Abstract

SQL injection attacks (SQLIAs) pose increasing threats as more organizations adopt vulnerable web applications and databases. By manipulating queries, SQLIAs access and destroy confidential data. This paper delivers three contributions around improving SQLIA detection research: first, a literature review assessing current detection/prevention systems to produce an SQL injection detection framework; second, specialized deep learning models optimizing session pattern analysis and feature engineering to enhance performance; third, comparing proposed models against previous defenses to surface promising research directions. Results highlight opportunities like real-time systems generalizing across attack variants through emerging techniques. Additionally, with attack complexity rising, systematized SQLIA investigation is warranted. Despite extensive study, current perspectives lack cohesive guidance informing mitigation strategies. Therefore, a framework is proposed holistically mapping knowledge gaps around contemporary SQLIAs, seminal threats in web applications, and security solutions. Furthermore, a multi-faceted framework examines research trends divided into hardening existing apps, detecting attacks on production systems, and integrating secure development practices. Literature suggests comprehensive resilience requires concurrent strength across these areas. Finally, future work remains in integrated frameworks, deep reinforcement learning adoption, automated AI auditing, and differential privacy to advance real-world SQL injection detection and prevention.
Rainfall Prediction Using Random Forest and Decision Tree Algorithms Raniprima, Sevierda; Cahyadi, Nanang; Monita, Vivi
Journal of Informatics and Communication Technology (JICT) Vol. 6 No. 1 (2024)
Publisher : PPM Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52661/jict.v6i1.253

Abstract

Weather
Co-Authors Adelia Rahaguna, Rahma Putri Aisyah Novfitri Alva Nurvina Sularso Angga Setiawan Atilla Pramudya Nugroho Dea Wemona Rahma Dharma Putra, I Made Raditya Dinda Jaelani Hidayat Faiq Rizky Firmansyah Glenn Frekly S. Tapa Ngale Haq, Laksamana Aidzul Kamelia Laksamana Aidzul Haq Lia Hafiza Maulana, Refsi Indra Muhamad Roihan Muhammad Agung Pratama Muhammad Nurhadi Nurul Ilmi, Nurul Nurwan Reza Fachrurrozi Pietra Dorand Qilbaaini Effendi Muftikhali Rahmadi Rahmadi Rana Zaini Fathiyana Refsi Indra Maulana Setiadi, Didi Sevierda Raniprima Sevirda Raniprima Sherfina Salsabila Syamsutizar, Muhammad Genta Syifa Nurgaida Yutia Vivi Monita Yudiansyah Yudiansyah Yulta Kadang Yus Natali