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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Buana Informatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) JAKPP : Jurnal Analisis Kebijakan & Pelayanan Publik Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Prosiding Seminar Nasional Sains dan Teknologi Terapan JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Reformasi : Jurnal Ilmiah Ilmu Sosial dan Ilmu Politik Journal of Local Government Issues JISKa (Jurnal Informatika Sunan Kalijaga) Journal of Information Systems and Informatics Mobile and Forensics Jurnal Teknologi Dan Sistem Informasi Bisnis JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Mediasosian : Jurnal Ilmu Sosial dan Administrasi Negara Automata Reswara: Jurnal Pengabdian Kepada Masyarakat Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Kawanua International Journal of Multicultural Studies Andalas International Journal of Socio-Humanities (AIJOSH) Jurnal INFOTEL Journal of Geosciences and Applied Geology Al-Mizan : Jurnal Ekonomi Syariah Jurnal Ilmiah Insan Mulia Journal of Elementary Education Research Jurnal Geosaintek
Ahmad Luthfi
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Neuroscience Social Sciences Other

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The Impact of Transformational Leadership on Employee Performance: An Intermediary Function of Organizational Commitment and Job Satisfaction Indriasari, Ratna; Permatasari, Marisa; Khair, Otti Ilham; Yusuf, Achmad; Susi, Susi; Luthfi, Ahmad
Kawanua International Journal of Multicultural Studies Vol 4 No 1 (2023)
Publisher : State Islamic Institute of Manado (IAIN) Manado, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30984/kijms.v4i1.580

Abstract

This study explores the impact of transformational leadership on employee performance. Qualitative descriptive analysis is used to identify problem patterns and relationships between concepts. Literature analysis supplements the research by examining relevant journals and articles. Findings demonstrate a significant positive influence of transformational leadership on employee performance, motivating employees to achieve organizational goals effectively and efficiently. Organizational commitment and job satisfaction serve as mediators between transformational leadership and performance. Transformational leadership enhances performance by fostering increased commitment and job satisfaction. Employees who exhibit attachment to the organization and job satisfaction tend to perform better. Overall, transformational leadership positively influences employee performance, with organizational commitment and job satisfaction acting as mediators in this relationship.
ANALYSIS OF THE MOBILE PAYMENT ONLINE SYSTEM APPLICATION OF THE PALOPO CITY REGIONAL GOVERNMENT BASED ON USER SATISFACTION Pakkaja, Ryan Alghazali; Luthfi, Ahmad; Haryono, Kholid
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 3 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i3.6949

Abstract

The electronic-based government system is now the best step for every region, and it certainly has a mission to educate the area regarding governance. Efforts have been made by the government to meet citizens' expectations for easier access to public services, which is the primary form of E-Government. Currently, the implementation of the existing E-Government concept can also be a new breakthrough in improving information technology-based services. One is the Mobile Payment Online System Application, built directly by the Palopo City Government through its strategic partner, Bank Sulselbar. However, special attention must still be given to implementing this application, especially to the system itself, which is less effective. Additionally, many individuals still take actions that are not in accordance with the procedures, as evidenced by the fraud committed by application users. This research uses qualitative methods that provide descriptive data results, describing the data occurring in the field. The data generated using quasi-experimental methods will be calculated using the same Likert scale. This research shows that the Mobile Payment Online System Application still needs to be socialized again to the users of this application and requires application development in terms of tool updates and system updates. This can be seen from the respondents' responses through the questionnaire results table and suggestions from these respondents. Thus, the Mobile Payment Online System Application is still ineffective for implementation in Palopo City.
IDENTIKASI JENIS FILE PADA ARTEFAK DIGITAL MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR Fawzan, Ihsan; Luthfi, Ahmad
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 2 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i2.6263

Abstract

Permasalahan yang dihadapi dalam penelitian ini berkaitan dengan adanya isu yang timbul akibat kerusakan file digital dalam konteks hukum, serta kontribusi penelitian ini dalam mengatasi permasalahan tersebut. Virus, malfungsi sistem, dan malware menjadi beberapa penyebab terjadinya file rusak sehingga menghambat akses menuju data penting dalam proses hukum. Teknik  yang sesuai dalam menganalisis konten file dan mengidentifikasi pola menggunakan algoritma untuk mengatasi masalah yaitu menggunakan teknik content-based. Penelitian ini memanfaatkan algoritma K-Nearest Neighbor dalam machine learning untuk mendeteksi jenis file pada file yang rusak. Penelitian yang mengkaji tentang identifikasi  jenis file sudah pernah dilakukan sebelumnya, namun masih menggunakan dataset lama yaitu GovDocs yang dirilis pada tahun 2009 sehingga perlu adanya penelitian yang menggunakan dataset baru. Penelitian ini memperbarui dataset GovDocs ke dalam NapierOne, yang berkontribusi pada peningkatan aksesibilitas data yang relevan untuk analisis. Machine learning digunakan dalam penelitian ini untuk mengklasifikasikan data dan berhasil meningkatkan keterbacaan dokumen meskipun tanpa informasi header atau footer. Selain itu, penelitian yang penulis lakukan dalam mengidentifikasi jenis file ambigu dalam artefak digital menggunakan K-Nearest Neighbor memperoleh hasil yang tinggi dengan tingkat akurasi mencapai 86%. Secara keseluruhan, studi ini berkontribusi pada peningkatan aksesibilitas dan keandalan bukti digital dalam konteks hukum, khususnya terkait file yang mengalami kerusakan.
INTEGRASI DIGITAL FORENSIC READINESS DAN INFORMATION SECURITY MANAGEMENT SYSTEM PADA ORGANISASI PEMERINTAHAN: SYSTEMATIC LITERATURE REVIEW Agung Firmansyah, Rico; Prayudi, Yudi; Luthfi, Ahmad
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 2 (2025): JATI Vol. 9 No. 2
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i2.13126

Abstract

Transformasi digital di Indonesia dan berbagai negara membawa manfaat signifikan, seperti peningkatan layanan publik melalui e-government, e-payment dan layanan lainnya. Namun, transformasi ini menghadirkan tantangan dalam pengelolaan keamanan data digital dengan meningkatnya insiden seperti serangan ransomware, eksploitasi sistem, pelanggaran data, dan insiden keamanan siber lainnya. Information Security Management System (ISMS) standar dan framework yang mendukung tata kelola dan manajemen keamanan informasi, namun sering kali tidak mencakup Digital Forensic Readiness (DFR) yang menjadi framework esensial untuk menghadapi ancaman siber yaitu pengumpulan, analisis, dokumentasi bukti digital, respon terhadap insiden hingga preservasi dalam proses hukum jika dibutuhkan. Tidak diterapkannya DFR-ISMS berpotensi tidak dapat dilakukannya pengendalian dan respon pasca insiden. Mengintegrasikan DFR ke dalam ISMS menjadi solusi peningkatan efisiensi dan efektivitas pengelolaan insiden. Penelitian ini menggunakan pendekatan Systematic Literature Review (SLR) untuk mengidentifikasi tren, tantangan, dan peluang integrasi DFR dalam ISMS di e-government. Data dari 1.054 artikel Scopus difilter dan dianalisis menggunakan Protokol PRISMA, menghasilkan 64 artikel. Analisis SLR menghasilkan temuan negara terbanyak yang menganalisa topik ini dengan Metode Kuantitatif adalah Afrika Selatan, Ingris, Yunani dan China, sedangkan teori yang digunakan ISO 27043 sebagai basisnya serta FDR-ISMS sebagai frameworknya. Hasil analisa tersebut menunjukkan integrasi DFR dan ISMS sangat dibutuhkan untuk meningkatkan kesiapan keamanan siber, memperkuat akuntabilitas, serta meminimalkan risiko.
Forensic Investigation of Drug and Food Crimes in Digital Marketplace Meutia, Adinda; Luthfi, Ahmad
Journal of Information System and Informatics Vol 7 No 1 (2025): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i1.882

Abstract

This research holds great significance as it is anticipated to safeguard customers from harmful frug and food products in cyberspace and to enforce the law by offering solid evidence to bring criminals to justice. Furthermore, this research helps to better understand how crimes that take place in the marketplace are committed, which enables the implementation of more effective preventive measures. Besides, in order to combat cybercrime, the findings of this study may serve as the foundation for the creation of more effective digital forensic investigation techniques. In order to perform digital forensic investigations of drug and food offenses using the marketplace, this study aims to develop an efficient and successful model or implementation guideline. This seeks to methodically direct the inquiry process while adhering to relevant norms. The objective of this research endeavor is to provide a model or practical guideline that is both effective and efficient for using the marketplace to undertake digital forensic investigations of drug and food crimes. This seeks to methodically direct the research process while adhering to relevant criteria. The following stages make up the Design Science Research (DSR) method of research: The issue in this project is "How to conduct a digital forensic investigation for Drug and Food crimes using the marketplace so that it can be used as evidence in court?" Then, in order to adopt answers from related research and make adjustments linked to research difficulties, a literature review is conducted to locate prior research. A model or implementation guideline for performing digital forensic investigations of the marketplace is the type of solution or artifact anticipated in this project. The next phase is solution design, which involves using an existing forensic investigation framework to create an artifact design. Following every step of the framework, case study experiments are then conducted to test the artifact design. The examination of the artifact design by both experts and consumers is the last phase.
PEMBERDAYAAN DESA WANDANPURO: TRANSFORMASI LIMBAH BATANG TALAS MENJADI PELUANG EKONOMI BERKELANJUTAN Fiasari, Sinta Nur; Luthfi, Ahmad; Yosika, Diana Rosa; Mustikarini, Monika Grace; Prayoga, Diki
Reswara: Jurnal Pengabdian Kepada Masyarakat Vol 5, No 1 (2024)
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/rjpkm.v5i1.3771

Abstract

Limbah batang talas (lompong) yang melimpah di Desa Wandanpuro, Kabupaten Malang, belum dimanfaatkan secara optimal oleh masyarakat, membuatnya kehilangan nilai praktis. Namun, melalui pengelolaan yang tepat, limbah lompong memiliki potensi besar untuk diubah menjadi produk makanan berkualitas tinggi, menciptakan peluang pendapatan yang signifikan bagi warga lokal. kegiatan pengabdian kepada masyarakat ini bertujuan untuk melatih masyarakat Desa Wandanpuro dalam mengolah limbah batang talas bernilai ekonomis dan yang berkelanjutan kepada masyarakat, meningkatkan keterampilan kewirausahaan, dan memperluas pemahaman tentang branding serta pemasaran digital. Dengan pendekatan partisipatif, melibatkan aktifitas masyarakat dalam semua tahapan, pengabdian masyarakat ini berhasil membangun pemahaman dan antusiasme di kalangan warga. Hasilnya menunjukkan bahwa pemberdayaan masyarakat yang dilakukan di Desa Wandanpuro yaitu masyarakat paham akan manfaat dari batang talas sehingga mereka terampil dalam mengolah limbah batang talas menjadi produk yang memiliki nilai jual. Harapannya, melalui sosialisasi dan pelatihan yang diberikan, masyarakat akan terus mengembangkan inisiatif ini, menciptakan ekonomi yang berkelanjutan sesuai dengan Prinsip Pembangunan Berkelanjutan (SDGs).
Digital Forensic Analysis of UAV Flight Data Using Static and Dynamic Methods in Coal Mining Area Halim, Muhammad Yusuf; Luthfi, Ahmad
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1061

Abstract

Unmanned Aerial Vehicles (UAV) have become vital tools in industrial sectors such as coal mining for site inspections and operational monitoring. However, unauthorized UAV flights present security risks that necessitate forensic investigation. This study examines a forensic case involving a DJI Mini 3 UAV suspected of crossing company boundaries. Using the Conceptual Digital Forensics Model for the Drone Forensic Field, both static and dynamic forensic acquisition methods were applied. Static acquisition recovered 53 photographs, 11 videos, 11 audio files, 10 deleted photos, 4 deleted videos, and 3 unidentified log files. Dynamic acquisition yielded 64 media files including 63 photographs (.JPG and .jpg) with 10 deleted, 14 videos (.MP4, .MOV, .SWF) with 6 deleted, 11 audio files, 4 plain text files, 31 deleted files, 3 EXIF metadata records containing GPS coordinates, and 3 unidentified log files. The GPS data from EXIF metadata was visualized in Google Earth to map flight paths and confirm boundary violations. These findings demonstrate that dynamic acquisition retrieves a more comprehensive artifact set than static acquisition. This study highlights the importance of UAV digital forensics in supporting security investigations and ensuring compliance with industrial UAV policies.
Predicting Smart Office Electricity Consumption in Response to Weather Conditions Using Deep Learning Wahyuzi, Zikri; Ahmad Luthfi; Dhomas Hatta Fudholi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 1 (2024): February 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i1.5530

Abstract

This study investigates the intricate relationship between electricity consumption in smart office environments, temporal elements such as time, and external factors such as weather conditions. Using a data set that encompasses electrical consumption statistics, temporal data, and weather conditions, the research employs preprocessing, visualization, and feature engineering techniques. The predictive model for electric energy usage is constructed using deep learning architectures, including Long Short-Term Memory (LSTM), Bidirectional Long Short-Term Memory (Bi-LSTM), Gated Recurrent Unit (GRU), and Bidirectional Gated Recurrent Unit (Bi-GRU). Evaluation metrics reveal that the LSTM model outperforms others, achieving minimal Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE). The study acknowledges the limitations of the data set, particularly when comparing electricity usage during work hours and outside working hours in a residential context. Future research aims to address these limitations, considering detailed meteorological data, missing data imputation, and real-time applications for broader applicability. The ultimate goal is to develop a predictive model that serves as a valuable tool for improving energy management in smart office settings, optimizing electricity usage, and contributing to long-term firm profitability.
Unresolved Psychological Problem in Dennis Lehane’s Shutter Island Ahmad Luthfi; Rika Handayani
Andalas International Journal of Socio-Humanities Vol. 4 No. 2 (2022)
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/aijosh.v4i2.42

Abstract

This article explains hallucination as a psychological problem undergone by Andrew Laeddis, the main character of Dennis Lehane’s Shutter Island. Viewed from Sigmund Freud’s psychoanalytical theory (id, ego, and superego), self-defense mechanism theory by Anna Freud, and hallucination theory, this article shows how the main character faces the hallucination and how his efforts fail. The results of the study reveal that Andrew Laeddis faces three types of hallucination: visual hallucination, auditory hallucination, and temporal illusion. Andrew Laeddis also applies two self-defense mechanisms: denial of reality and regression. Since the id is more dominant than the ego, the doctors do not succeed in curing him of the hallucination. In other words, Andrew Laeddis experiences an unresolved psychological problem; which is hallucination.
Enhancing Disease Diagnosis Coding: A Deep Learning Approach with Bidirectional GRU For ICD-10 Classification Priwibowo, Aqge; Dewa, Chandra Kusuma; Luthfi, Ahmad
JURNAL INFOTEL Vol 17 No 2 (2025): May
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i2.1320

Abstract

The health insurance claim in hospitals involves selecting specific ICD-10 codes for primary diagnosis texts. With rising claim volumes, the need for faster, more accurate coding is critical. This study develops a deep learning model to classify diagnosis texts into relevant ICD-10 codes using 9,982 original medical records from a national referral hospital under the Indonesian Ministry of Health. The classification method employs a BiGRU layer architecture, known for its effectiveness in handling sequential data, such as diagnosis texts. BiGRU operates bidirectionally, enhancing the model’s ability to capture the context from both past and future sequences. In this architecture, the BiGRU layer serves as the classification layer, stacked above the BERT layer, which functions as the vector embedding layer, converting text into numerical representations for the model. The results of the study demonstrate a promising solution for codifying primary diagnosis texts, achieving a precision of 82.18% and a recall of 81.59%. Despite the strong performance of the model, further improvements are possible. Interestingly, the study also observed that the size of the class volume per ICD-10 code is not the only factor affecting classification performance, as some classes with smaller volumes exhibited better classification results. However, merging rare classes did not improve performance and even worsened it, suggesting that better ways to handle underrepresented classes are needed. Experiments with different embedding layers, such as IndoBERT and BioClinicalBERT, and hyperparameter tuning yielded minimal performance gains, suggesting the need for alternative optimization strategies.
Co-Authors Abdul Aziz Achmad Yusuf Agung Firmansyah, Rico AHMAD FAISOL Aini, Hana Nur Amali, Adityal Chisabul Amitama, Emilia Bunga Anggraini, Friska Apriyani, Mirna Ariwibisono, FX Bambang Sugiantoro Bin Wallang, Muslimin Dedy Afrizal Denny Vitasari Dewa, Chandra Kusuma Dhomas Hatta Fudholi diana, ros Didik Sudyana Dila Erlianti Ekareesakul, Kittipan Eko Yuli Handoko Erinaldi, Erinaldi Fachrudin, Kurnia Arfiansyah Fawzan, Ihsan fFaizal, Arif Fiasari, Sinta Nur Hafrida, Lis Halim, Muhammad Yusuf Hananfajri, Muhammad Hardika Dwi Hermawan Hijeriah, E. Maznah Hildawati Hildawati, Hildawati I Made Arie Widyasthana Wartana Putra Ildrem Syafri Imam Riadi Indriasari, Ratna Kasnelly, Sri Khair, Otti Ilham Kholid Haryono Kurniawan, Andang Kusuma Dewa, Chandra Latif Syaipudin Lian Agustina Setiyaningsih M. Said Marisa Permatasari, Marisa Maulana, Bagus Andrai Mawarni, Dinda Iga Meutia, Adinda Muhammad, Aldila Syariz Munawwaroh, Nasywa Zunaibatul Munjayyanah, Munjayyanah Mustikarini, Monika Grace Nilma, Nilma Nur Widiyasono, Nur Nurhalisa, Sabrina Nuril Anwar, Nuril Pakkaja, Ryan Alghazali Paputungan, Irving Vitra Poespitohadi, Wibisono Pratama, Syahrul Pravitasari, Norma Prayoga, Diki Priwibowo, Aqge Purnamasari, Rika Afriyanti Putra, I Made Arie Widyasthana Wartana Ramadani, Erika Ramadiniyati, Suci Rika Handayani Rike Nursafitri Rizky Achmad Almayda Almayda Rosa, Nauviana Pita Salwa, Nikmatus Shaleha, Annisa Amalia Sopaheluwakan, Ardhasena Sri Widayati Sumarni Sumarni Suroningsih Suroningsih, Suroningsih susi susi Tuharea, Ibnu Rohan Wahyuzi, Zikri Widarta, Agung Eka Yosika, Diana Rosa Yudi prayudi Zainul’ID, Ahmad Bagus Zubizaretta, Zaid Dzulkarnain