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All Journal Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Teknik: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Paradigma: Jurnal Filsafat, Sains, Teknologi, dan Sosial Budaya
Habibullah Akbar
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Religion Arts Humanities Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences

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Evaluation of the Implementation of E-Government Public Service Aduan Konten Using E-Govqual, Importance Performance Analysis and Heuristic Evaluation (case study: Ministry of Communication and Information, APTIKA directorate) Nila Rusiardi Jayanti; Gerry Firmansyah; Nenden Siti Fatonah; Budi Tjahjono; Habibullah Akbar
Budapest International Research and Critics Institute-Journal (BIRCI-Journal) Vol 5, No 3 (2022): Budapest International Research and Critics Institute August
Publisher : Budapest International Research and Critics University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33258/birci.v5i3.6640

Abstract

In the current condition of society that is critical in responding to everything, more public services are needed professional, effective, simple, transparent, timely, responsive. Efforts to improve the quality of public services cannot be separated from service evaluation. In order to improve the quality of public services, the Directorate General of Informatics Applications of the Ministry of Communications and Informatics established the Public Service for Aduan konten at the Directorate of Information Application Control (PAI) as a pilot project. So to evaluate the quality of public services, a bureaucratic reform program is carried out at the PAI Directorate through efforts to develop a zone of territorial integrity free from corruption and a clean bureaucratic area to serve. One of the evaluations carried out is for measuring service performance as mandated in the Regulation of the Minister of Administrative Reform Number 14 of 2017 concerning the Community Satisfaction Survey (SKM) on the Implementation of Public Services. This study aims to determine the service quality of the Content Complaint website using the e-Govqual method, while the IPA and heuristic evaluations are to determine the attributes that are priorities for improving service quality, as recommendations to public service providers for Aduan konten. To assess the service quality of the content complaint website, 6 dimensions and 21 e-Govqual attributes are used. Of the 300 respondents who were used as research samples, this study shows the results of the analysis of the level of conformity of the 6 dimensions are 98.03% (<100%) meaning that the public services provided by the Aduan konten website are not satisfactory to users or still not in accordance with user expectations. The result of the average value of the gap between expectations and performance shows the number -0.05 or < 0. With this gap, it can be said that the quality of public service performance of Aduan konten perceived by the public still does not meet what is expected. Attributes that need improvement are those in quadrant A (3 attributes) and quadrant C (8 attributes). Recommendations are given based on the literature/theory for attributes that need to be improved to improve the quality of public services for Aduan konten.
DETEKSI BANJIR AREA PERKOTAAN BERBASIS CITRA DIGITAL CONVOLUTIONAL NEURAL NETWORK (VGG19) Habibullah Akbar; Diah Aryani; Muhamad Bahrul Ulum
Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol. 2 No. 3 (2022): November : Jurnal Teknik Mesin, Elektro dan Ilmu Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (992.245 KB) | DOI: 10.55606/teknik.v2i3.798

Abstract

Geographically and demographically, Indonesia has natural conditions that have the potential for floods disaster. There are at least 16,771 islands and 65,017 rivers that fill the archipelago. Unfortunately, the ever-increasing urban population accompanied by a lack of awareness and preparation for protecting the environment has resulted in a higher risk of flooding in urban areas. This study utilizes digital imagery to detect flood conditions in urban areas. In terms of access, digital images are available in urban CCTV monitoring systems as well as office areas, housing, and from people who have smartphones. The detection method used in this study is the VGG19 model which consists of 16 convolution layers and 3 standard classification layers. All convolution layers are divided into 5 blocks followed by a MaxPooling layer for each block to reduce the resolution of the input image. In the last layer, SoftMax layer is used to estimate the probability between flood labels and normal conditions. There are 4 parameters that were optimized during the VGG19 model training process, namely Batch Size, Learning Rate, Dropout and Epoch (training repetition). To test the proposed model, public datasets are used, namely the Roadway Flooding Image Dataset and Road Vehicle Images Dataset. The best flood detection results (or normal conditions) achieve the accuracy of 98.78%. As for the other three performance metrics, namely precision, recall and F1-score, they reach 99%. These results are generated by the VGG19 model with a Batch Size parameter of 20, a Learning Rate of 1e-5 (0.00001), 50% Dropout and 100 Epoch. The achievement values of the four metrics can be considered quite good, so that the VGG19 model has the opportunity to be developed for flood detection applications in order to monitor urban flood conditions.
Penerapan Analisis Asosiasi Untuk Mengetahui Pola Pembicaraan Depresi Pada X Rifqi Adi Prasetya; Munawar; Habibullah Akbar; Popong Setiawati
Paradigma: Jurnal Filsafat, Sains, Teknologi, dan Sosial Budaya Vol. 31 No. 2 (2025): Paradigma: Jurnal Filsafat, Sains, Teknologi, dan Sosial Budaya
Publisher : Universitas Insan Budi Utomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33503/paradigma.v31i2.2557

Abstract

Penelitian ini bertujuan untuk mengidentifikasi pola pembicaraan yang mencerminkan gejala depresi pada media sosial X dengan menerapkan metode association rule mining. Dengan meningkatnya penggunaan media sosial sebagai wadah ekspresi emosional, studi ini berupaya mengungkap hubungan antar kata yang sering muncul bersamaan dalam konteks depresi. Penelitian ini menggunakan pendekatan Knowledge Discovery in Database (KDD) yang mencakup tahapan seleksi data, pre-processing, transformasi data, data mining, interpretasi hasil, dan validasi pakar. Data dikumpulkan melalui tools Tweet Harvest dengan kata kunci seperti “capek”, “sedih”, “stress”, “sengsara”, “lelah”, “gelisah” dan “putus asa”, menghasilkan 21.020 tweet, yang kemudian diproses dan dianalisis menggunakan algoritma Apriori dan FP-Growth. Hasilnya menunjukkan 12 aturan asosiasi yang menggambarkan ekspresi emosi negatif dengan intensitas tinggi, seperti asosiasi antara “hidup” dan “sengsara” serta “sedih” dan “banget”, yang mencerminkan fokus pada diri sendiri, kelelahan emosional, dan persepsi negatif terhadap hidup sebagai indikasi umum dari depresi. Validasi pakar mengonfirmasi bahwa pola-pola tersebut memiliki relevansi klinis. Apriori terbukti lebih efisien dari segi waktu dan penggunaan memori dibanding FP-Growth. Temuan ini menunjukkan bahwa pola bahasa di media sosial dapat menjadi indikator dini gejala depresi.
Co-Authors Budi Tjahjono Diah Aryani Gerry Firmansyah Muhamad Bahrul Ulum MUNAWAR Nenden Siti Fatonah Nila Rusiardi Jayanti Popong Setiawati Rifqi Adi Prasetya