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All Journal Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Jurnas Nasional Teknologi dan Sistem Informasi JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Komputer Terapan IT JOURNAL RESEARCH AND DEVELOPMENT Seminar Nasional Teknologi Informasi Komunikasi dan Industri Indonesian Journal of Electrical Engineering and Computer Science Teknika Jurnal Nasional Teknik Elektro dan Teknologi Informasi Proceeding International Applied Business and Engineering Conference JITER-PM (Jurnal Inovasi Terapan - Pengabdian Masyarakat) Science, Technology, and Communication Journal
Dadang Syarif Sihabudin Sahid
Politeknik Caltex Riau
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Implementation And Performance Analysis Development Security Operations (DevSecOps) using Static Analysis and Security Testing (SAST) Wedy Freddy Santoso; Dadang Syarif Sihabudin Sahid
International ABEC 2021: Proceeding International Applied Business and Engineering Conference 2021
Publisher : International ABEC

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (624.294 KB)

Abstract

DevSecOps solves the problem by integrating the security of development operations through various development life cycles. benefits, implementation and challenges during the process. in addition to many documented web hacks. For the scope of work reported that the focus is on two widely used digital library systems: DSpace and Greenstone, in performing Static Application Security Testing (SAST) in addition to more traditional port scanning. Weaknesses were found and details how to make improvements to both systems to make them more secure. can ensure by considering more broadly on the forms of security problems found, to assist the development of software architecture in the future.
UKT (Single Tuition) Classification Prediction uses MKNN (K-Nearest Neighbor Modification) algorithm Dziki Adli; Dadang Syarif Sihabudin Sahid
International ABEC 2021: Proceeding International Applied Business and Engineering Conference 2021
Publisher : International ABEC

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Abstract

Islamic University of Sultan Syarif Kasim (UIN SUSKA) Riau Province has used an information system, namely the Sistem Registrasi (SIREG) to facilitate the registration of prospective students and also SIREG also provides a decision on determining the UKT of students who have been declared graduated. But there has never been an evaluation of SIREG's accuracy in determining the UKT. From these problems, a model is needed to be implemented to facilitate SIREG officers in conducting classifications to establish UKT new students. Using the MKNN method and supported by the K-Fold Cross Validation validation method, the classification results get an accuracy value of 71%
Using KNN Algorithms for Determining The Recipient of Smart Indonesia Scholarship Program Purwanto; Dadang Syarif Sihabudin Sahid
International ABEC 2021: Proceeding International Applied Business and Engineering Conference 2021
Publisher : International ABEC

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Abstract

The Smart Indonesia Card (KIP) scholarship program is a government scholarship program through the Ministry of Religion of the Republic of Indonesia which is given to students who have a good academic level but have a weak economic level. Sultan Syarif Kasim State Islamic University, Riau accepts new students every year, but the quota for the KIP scholarship program is limited. With the limited quota for the KIP program, a system is needed that is able to classify submission data from students who register for the KIP program, so that the selection process can be carried out, quickly, precisely, and in accordance with the required quota. In this study, the K-Modes and K-Nearest Neighbor (KNN) Algorithms were used by using the achievement variables, report cards, and national exam scores when high school, father's income, parental status, and homeownership status. Reprocessing is carried out before the testing stage, testing is carried out by performing the initial stages, namely clustering using the K-Modes algorithm, then validating or testing data by applying the Grid Search Cross-Validation (GSCV) method, and finally predicting using the KNN algorithm. The test resulted in a performance value of 66.79%.
Hotpoint Monitoring System Power Cable Termination Based On Internet of Things (IoT) Using Telegram Bot Muhammad Syahri; Agus Urip Ari Wibowo; Dadang Syarif Sihabudin Sahid
International ABEC Vol. 2 (2022): Proceeding International Applied Business and Engineering Conference 2022
Publisher : International ABEC

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Abstract

Electricity is energy that is needed in any field, both industry and ordinary people. To be able to produce good quality electrical energy, it is necessary to monitor and maintain electrical power equipment to prevent equipment damage that can interfere with the electrical energy distribution system to consumers. One of the disturbances that are often experienced is the Hotpoint at the terminal connection section between the conductor cable and the equipment at the substation. Hotpoint is an increase in the production of acoustic pulses (sound) and an increase in temperature that causes energy dissipation resulting in the heating of a localized area. This Hotpoint will cause damage to the equipment if it occurs for a long time. In this research, a Hotpoint monitoring system for 20 kV power cable termination based on the Internet of Things was built to monitor the temperature condition of the 20 kV power cable termination in real-time. This system uses the MLX90640 IR Thermal Camera sensor as the cable termination temperature gauge and the DHT22 temperature sensor to measure the 20 kV cubicle panel temperature. This temperature value will be compared to determine whether there is a Hotpoint at the termination of the 20 kV power cable. This system uses a MySQL database and HTTP protocol for communication between the Raspberry Pi4 and the website dashboard, then for notifications using the Telegram bot. The sensor accuracy test is carried out by comparing the temperature value between the DHT22 sensor and the Hygrometer with an average measurement value difference of -1.7%, while the MLX90640 and Fluke Ir 568 sensor accuracy tests have an average measurement value difference of -1.13%°C. Based on the sensor accuracy testing, it can be concluded that all sensors have a fairly good performance in measuring the required temperature parameters.
Penerapan Gamifikasi Pada Media Pembelajaran Untuk Meningkatkan Aktivitas Dan Hasil Belajar Siswa Kurnia Rahman Agus; Dadang Syarif Sihabuddin Sahid; Syabdan Dalimunthe
IT Journal Research and Development Vol. 7 No. 2 (2023)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/itjrd.2023.10068

Abstract

The demands of the learning process during the current pandemic force teachers and students to carry out digital transformation in the learning process. Especially in the new normal where the learning process is done online. Thus, the learning media made by the teacher must also be adapted to online media so that the learning process can be maximized and increase the activeness of students in learning while online. This study aims to create an online learning media by applying the concept of gamification. The method used in this research is R&D (Research and Development) using analysis, design, and development development models. Stages of analysis are carried out to determine the needs of students when learning online. Then in the design stage, the selection of media formats and media design is carried out, and finally at the development stage, the advanced process of making games with programming languages is carried out as a learning medium. The use of gamification learning media is very practical, which can be accessed by students through their devices at home via the internet network. In the learning process, this game can be used to assist teachers in achieving learning objectives so that they can increase learning activity and the value of students in one basic competency.
Pelatihan Pengelolaan Blog dalam Peningkatan Literasi Bidang Informatika untuk Santri SMAIT Imam Syafii 2 Pekanbaru Satria Perdana Arifin; Dadang Syarif Sihabudin Sahid; Yohana Dewi Lulu Widyasari; nina fadilah najwa; Khairul Umam Syaliman
JITER-PM (Jurnal Inovasi Terapan - Pengabdian Masyarakat) Vol. 1 No. 1 (2023): JITER-PM
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (343.078 KB) | DOI: 10.35143/jiterpm.v1i1.5892

Abstract

Salah satu kompetensi dan profil lulusan Program Studi Sistem Informasi Politeknik Caltex Riau adalah pengelolaan teknologi. Perlu rasanya untuk memperkenalkan kepada masyarakat, khususnya kepada pelajar sekolah menengah atas untuk lebih mengetahui salah satu kompetensi tersebut yang ada di program studi sistem informasi. Salah satunya adalah dengan melakukan pelatihan kepada siswa-siswa SMAIT Imam Syafii 2 Pekanbaru. Ruang lingkup pelatihan adalah teknik dasar pengelolaan blog yang mana materi yang akan disampaikan meliputi teknik pembuatan artikel menggunakan media digital wordpress, menggunakan SEO dan mempublikasikan hasil tulisan yang telah dibuat. Hasil akhir dari pelatihan ini adalah siswa SMAIT Imam Syafii 2 bisa membuat blog dan mampu mengembangkan literasi di bidang informatika oleh siswa dan mengenal dengan baik mengenai salah satu kurikulum yang ada di Program Studi Sistem Informasi.
Implementasi SEM-Multiple Linear Regression dalam Prediksi Jumlah Pendaftaran Mahasiswa Baru di Perguruan Tinggi XYZ Amelia Rahmadhani; Dadang Syarif Sihabudin Sahid; Yohana Dewi Lulu Widyasari
Jurnal Nasional Teknologi dan Sistem Informasi Vol 9, No 2 (2023): Agustus 2023
Publisher : Jurusan Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v9i2.2023.150-162

Abstract

Bagi perguruan tinggi swasta (PTS), tidak menutup kemungkinan semakin banyak mahasiswa baru yang diterima, maka PTS tersebut akan terus eksis. Sebaliknya, jika PTS gagal menambah atau bahkan menurunkan jumlah mahasiswa baru setiap tahunnya, hal itu bisa berubah dengan tidak mampu beroperasi lagi bagi PTS dikarenakan pendapatan mereka satu-satunya hanya dari biaya kuliah mahasiswa. Tujuan penelitian ini diantaranya penentuan faktor-faktor yang mendukung prediksi pendaftaran mahasiswa di perguruan tinggi berdasarkan data sebelumnya, mengimplementasikan Multiple Linear Regression terhadap pendaftaran mahasiswa di perguruan tinggi, dan menganalisis tingkat akurasi hasil prediksi pendaftaran mahasiswa di perguruan tinggi. Penelitian ini menggunakan algoritma Multiple Linear Regression. Sebelum melakukan tahap prediksi, terlebih dahulu menentukan faktor-faktor yang mempengaruhi jumlah penerimaan mahasiswa baru menggunakan Structural Equation Modeling (SEM) dengan faktor promosi, biaya Pendidikan, tingkat kelulusan, informasi pendafataran, jenis kelamin dan nilai akreditasi. Berdasarkan hasil SEM didapat faktor promosi, biaya Pendidikan, tingkat kelulusan, informasi pendafataran, dan nilai akreditasi, dapat dilanjutkan ke tahap berikutnya karena faktor tersebut berpengaruh signifikan terhadap mahasiswa baru, sedangkan hasil prediksi menggunakan Multiple Linear Regression didapat bahwa nilai prediksi untuk tahun berikutnya adalah 486 orang calon mahasiswa baru, dengan hasil perhitungan MSE adalah 2657,79 dan MAE adalah 42.29, dimana semakin kecil hasil nilai MSE dan MAE yang diperoleh maka kesalahan pada sistem juga semakin sedikit serta R2 adalah 0.9280 (92,80%) menandakan bahwa pengaruh semua struktur eksogen pada struktur endogen kuat.
Pengenalan Kepribadian Seseorang Berdasarkan Pola Tulisan Tangan Menggunakan Jaringan Saraf Tiruan Mutia Fadhilla; Maksum Ro’is Adin Saf; Dadang Syarif Sihabudin Sahid
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 6 No 3: Agustus 2017
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Graphology is a study of representing personality based on handwriting. Individual’s handwriting is unique and has own feature that it can be analyzed to understand personality. Graphology is used in some fields such as staffing, determining interest and talent. Some researches in graphology using artificial intelligence have been studied before. However, most of the researches still used one handwriting feature and did not classify into personality type. In this study, using some features of handwriting, i.e. left margin, right margin, size, and slant to classify personality type. Personality is classified based on Myers-Briggs Type Indicator (MBTI) using Back Propagation and Learning Vector Quantization method. The result shows that Learning Vector Quantization has better performance, with 90% accuracy, than Back Propagation, which has 82% accuracy.
Integrated production facilities clustering and time-series forecasting derived from large dataset of multiple hydrocarbon flow measurement Rangga, Adityapati; Widyasari, Yohana Dewi Lulu; Sahid, Dadang Syarif Sihabudin
Science, Technology and Communication Journal Vol. 2 No. 2 (2022): SINTECHCOM Journal (February 2022)
Publisher : Lembaga Studi Pendidikan and Rekayasa Alam Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59190/stc.v2i2.207

Abstract

In the complex, mature, and large oilfields, there is a need for Integrated solution in order to have a helicopter view of entire facilities throughput. The real time metering information provides an on-demand daily data and trend. However, it is rarely being connected to analytics solution for business intelligence such as, prediction, optimization, decision support and forecast. This paper cover about exploratory data analysis of large dataset of multiple hydrocarbon facilities metering within integrated network, performing multi-feature data clustering and making a time-series forecasting techniques. K-means and PCA are combined to make cluster of production facilities which resulted with gas processing cluster, high oil producer, high water processing station, and the lowest performer in term in hydrocarbon processing. Furthermore, VAR and LSTM are compared as forecasting tools for day-to-day fluid prediction, to maintain normal operational scenario.
Research trends in spatial modeling of PM2.5 concentration using machine learning: a bibliometric review Wahyuni, Retno Tri; Hanafi, Dirman; Tomari, M. Razali; Sihabudin Sahid, Dadang Syarif
Indonesian Journal of Electrical Engineering and Computer Science Vol 37, No 2: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v37.i2.pp1317-1327

Abstract

Spatial modeling is commonly used to map research variables, including particulate matter 2.5 (PM2.5) concentrations, in specific areas. The article that surveys publications on the application of machine learning in spatial modeling of PM2.5 using bibliometric methods has not been identified yet. This paper aims to analyze trends in applying machine learning in the spatial modeling of PM2.5 using bibliometric methods. The review was conducted on publications indexed in the Scopus database over the decade (2014–2023) comprising 335 articles. The analysis included co-authorship and co-occurrence using VOSviewer. From the two stages of analysis, it can be concluded that research on this topic has constantly increased over the past 10 years, with the highest productivity coming from researchers in China. This research topic is multidisciplinary, with most publications appearing in environmental science. The research also shows a very high collaboration rate of 0.98. A deeper examination of the keywords reveals the most commonly used machine learning techniques by researchers. The random forest method is the most frequently found in the analyzed documents, followed by deep learning, long short-term memory (LSTM), extreme gradient boosting (XGBoost), and ensemble model.
Co-Authors Agus Urip Ari Wibowo Amelia Rahmadhani Apriantoni Apriantoni Bayu Hanif Pratama Dedi Irawan Dirman Hanafi Dziki Adli Fadhilla, Mutia Haryana Hairi Indah Lestari Indah Lestari Indah Lestari, Indah Juni Nurma Sari Juni Nurma Sari Kartina Diah Kusuma W Khairul Umam Syaliman Kurnia Rahman Agus Lulu Widyasari, Yohana Dewi Maksum Ro’is Adin Saf Mohd. Yasin, Suhaila Muhammad Ihsan Zul Muhammad Syahri Mutia Fadhilla Najwa, Nina Fadilah Okfalisa Okfalisa Purwanto Purwanto maspur Rahmadhani, Amelia Rangga, Adityapati Romi Fadli Syahputra Saf, Maksum Ro’is Adin Saktioto Saktioto Satria Perdana Arifin Sellya Meizenty Stefant Cristian sugianto Syabdan Dalimunthe Syamsudhuha Syamsudhuha Tomari, M. Razali Vepy Asyana Wahyu Candra Wahyuni, Retno Tri Wawan Kurniawan Wedy Freddy Santoso Winnie Alison Yasin, Suhaila Mohd. Yohana Dewi Lulu Widyasari