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Herri Setiawan
Universitas Indo Global Mandiri, Palembang
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Other

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PEMBINAAN DAN PENINGKATAN SKALA USAHA IRT-UM MELALUI PEMANFAATAN PEWARNA ALAM BENANG, KAIN DAN PURUN PADA KELOMPOK USAHA PERAJIN DI DESA BURAI, KECAMATAN TANJUNG BATU, KABUPATEN OGAN ILIR, SUMATERA SELATAN Setiawan, Herri; Viatra, Aji Windu; Dhamayanti; Febriyanti, Doris; Heriansyah, Rudi; Setiawan, Budi; Lestari, Sylvia Dwi
Jurnal Abdimas Mandiri Vol. 9 No. 1
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jam.v9i1.5307

Abstract

Penguatan usaha Industri Rumah Tangga Usaha Mikro (IRT-UM) menjadi bagian strategis dalam membangun ekonomi rakyat yang berdaya saing dan berkelanjutan. Keberhasilan usaha tersebut sangat bergantung pada keterampilan dan pengetahuan para pelaku usaha. Program Pembinaan Industri Rumah Tangga Usaha Mikro berbasis Kemitraan ini bertujuan untuk meningkatkan kapasitas usaha mitra IRT-UM Burai Indah dan Purun Warna Warni (Purwani) di Desa Burai, Tanjung Batu, Ogan Ilir, melalui pelatihan di berbagai aspek, seperti tata kelola kelembagaan, manajemen keuangan, digital marketing, branding, packaging produk, fotografi produk, serta produksi pewarna alami. Program ini melibatkan 40 peserta perajin kain songket dan purun dengan metode kombinasi penyampaian materi dan praktik langsung. Hasil program menunjukkan bahwa, baik dalam Pelatihan Digital Marketing, Tata Kelola Kelembagaan dan Manajemen Keuangan, maupun Branding dan Packaging yang dilaksanakan terhadap Mitra Burai Indah dan Purwani di Desa Burai menunjukkan hasil yang signifikan dalam meningkatkan kapasitas pengetahuan dan keterampilan peserta. Evaluasi kuisioner sebelum dan sesudah pelatihan memperlihatkan adanya peningkatan yang konsisten pada berbagai aspek, seperti tata kelola kelembagaan, manajemen keuangan, digital marketing, branding, packaging, serta fotografi produk, dimana pada masing-masing pelatihan memiliki hasil kuesioner yang secara konsisten menunjukan hasil skala diatas 4,0 (Sangat Memahami), baik pada Mitra Burai maupun Perwani. Dengan peningkatan skala produksi dan efisiensi biaya, produk mitra memiliki potensi untuk menjangkau pasar yang lebih luas, termasuk pasar global, sehingga berdampak positif terhadap perekonomian lokal serta keberlanjutan lingkungan.
ANALISIS SAMPEL MALWARE PADA SISTEM OPERASI WINDOWS 10 MENGGUNAKAN CUCKOO SANDBOX Adiyatma, Muhammad Rifki; Setiawan, Herri; ., Tasmi
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 3 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i3.6556

Abstract

Analisis malware merupakan langkah penting dalam mendeteksi, memahami, dan mengurangi dampak perangkat lunak berbahaya terhadap sistem komputer. Penelitian ini fokus sampel pada analisis malware pada sistem operasi Windows menggunakan Cuckoo Sandbox , sebuah platform open-source yang dirancang untuk menganalisis perilaku malware secara otomatis. Proses analisis sampel dilakukan dengan mengisolasi dalam lingkungan virtual yang terkendali, sehingga memungkinkan pemantauan aktivitas berbahaya tanpa risiko terhadap sistem host. Penelitian sampel ini meliputi tahapan pengumpulan malware, konfigurasi lingkungan pengujian, eksekusi sampel, dan analisis hasil. Berdasarkan hasil analisis, ditemukan bahwa sampel malware memiliki kemampuan untuk memodifikasi sistem file, memanipulasi entri registri, dan melakukan komunikasi jaringan dengan perintah server dan kontrol. Tingkat deteksi berdasarkan VirusTotal menunjukkan bahwa sebagian besar sampel dikategorikan sebagai malware berbahaya, dengan tingkat deteksi mencapai 67%. Temuan ini menunjukkan efektivitas metode analisis dinamis dalam mengungkap pola serangan malware serta pentingnya penggunaan lingkungan virtual dalam pengujian malware untuk meningkatkan keamanan dan mitigasi risiko
ANALISIS PERILAKU PENGGUNA TERHADAP AKSES INTERNET DI PT CHIYODA INTERNATIONAL INDONESIA MENGGUNAKAN MACHINE LEARNING Agustani, Adi; Setiawan, Herri; Tasmi, Tasmi
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 3 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i3.6594

Abstract

Akses internet merupakan faktor penting dalam kelancaran operasional perusahaan. PT Chiyoda International Indonesia yang sangat bergantung pada infrastruktur TI dan konektivitas internet, menjadi objek dalam penelitian ini. Tujuan utama penelitian adalah menganalisis pola perilaku pengguna dalam mengakses internet melalui penerapan teknik machine learning menggunakan metode K-Means berbasis Python . Data yang dianalisis berasal dari lebih dari 10.000 entri aktivitas internet selama enam bulan, mencakup lima departemen utama. Hasil analisis elbow plot menunjukkan bahwa tiga cluster merupakan jumlah optimal, dengan penurunan nilai inersia sebesar 65% dibandingkan konfigurasi awal. Klasterisasi menunjukkan bahwa 40% pengguna tergolong dalam intensitas tinggi (rata-rata 4,5 jam/hari), 35% intensitas sedang (3 jam/hari), dan 25% intensitas rendah (1,5 jam/hari). Analisis visualisasi cluster plot mengungkap perbedaan signifikan antar departemen, terutama dalam jenis aplikasi yang diakses. Departemen dengan intensitas tertinggi cenderung menggunakan aplikasi non-produktif seperti media sosial dan streaming . Temuan ini menjadi dasar penting bagi perusahaan dalam mengoptimalkan alokasi bandwidth dan menetapkan kebijakan pengawasan akses. Penelitian ini diharapkan memberikan kontribusi strategi dalam pengelolaan sumber daya digital secara efisien di era transformasi teknologi.
CNN-Based Identification of Longan Varieties Using Leaf Vein Patterns Pratama, M. Aditya Yoga; Setiawan, Herri; Purnamasari, Evi
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.6926

Abstract

Visual classification of longan seedlings remains challenging due to the similarity of characteristics among varieties, particularly in young leaves. This study applies the Convolutional Neural Network (CNN) method to classify five types of longan seedlings—Diamond River, Matalada, Merah, Itoh, and Pingpong—based on leaf vein patterns, which serve as distinctive features. The dataset consists of 1,000 high-resolution images, divided into 900 for training and 100 for testing. The training process includes preprocessing steps such as cropping to focus on vein patterns, resizing to standardize input dimensions, augmentation to enhance data variety, normalization to scale pixel values, and splitting into training and validation sets. Hyperparameter tuning was performed using a grid search, evaluating combinations of learning rate, batch size, and epochs. The best configuration was achieved at the 80th epoch, with a learning rate of 0,0001 and a batch size of 8. The model achieved a validation accuracy of 0,8444 and a loss of 0,3865. During testing, it reached an accuracy of 0,8000, with an average precision of 0,8266, recall of 0,8000, and f1-score of 0,7843. The best performance was observed in the Merah and Matalada classes, while the Diamond class remained challenging due to visual similarities. CNN proved effective for this task, though further improvement is needed for visually similar classes to enhance classification accuracy.
Klasifikasi Kelayakan Penerima Bantuan Sosial dengan Metode K-Nearest Neighbors Rosyad, Nyimas Siti; Setiawan, Herri; Irvani, Muhammad Haviz
Insect (Informatics and Security): Jurnal Teknik Informatika Vol. 11 No. 2 (2025): Oktober 2025
Publisher : Universitas Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33506/insect.v11i2.4918

Abstract

Social assistance distribution in Indonesia still faces various challenges, including inaccurate recipient data, complex bureaucracy, and lack of transparency, often resulting in misdirected aid. This study aims to optimize the application of the K-Nearest Neighbors (K-NN) method for classifying the eligibility of social assistance recipients by testing several data train-test split ratios and variations of the parameter k. The primary objective is to develop an accurate and reliable classification model to support policy-making in social assistance distribution at Kuto Batu Village, Palembang. The dataset includes citizens' socioeconomic attributes and undergoes preprocessing steps such as data cleaning, encoding, and handling missing values before being applied to the K-NN algorithm. Four data split scenarios are tested—80/20, 70/30, 60/40, and 50/50—to determine the optimal configuration. Evaluation results show model accuracies of 97.44%, 98.30%, 97.10%, and 98.00% for the respective splits. The 70/30 split yields the best performance with 98.30% accuracy, 100% precision, 98% recall, and 98.98% F1-score. This ratio is selected as the optimal configuration due to its balance between sufficient training data for pattern learning and adequate test data for evaluating model generalization. These findings demonstrate that the K-NN method is effective in objectively distinguishing eligible and ineligible recipients and has strong potential as the foundation for a decision support system to improve transparency and targeting accuracy in social assistance programs.
Digitalisasi Sistem Monitoring pH Air Pada Instalasi Pengelolaan Air Limbah Laboratorium BSPJI Palembang Satker Kementerian Perindustrian Berbasis Android Fajryn, Fikry; Setiawan, Herri; Sartika, Dewi
Jurnal Pengembangan Sistem Informasi dan Informatika Vol. 5 No. 2 (2024): Jurnal Pengembangan Sistem Informasi dan Informatika
Publisher : Training & Research Institute - Jeramba Ilmu Sukses

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47747/jpsii.v5i2.1738

Abstract

The wastewater management system is an important part of maintaining the cleanliness and quality of the environment. One of the parameters that need to be monitored regularly is the level of acidity or pH of the wastewater. This study aims to develop an Android-based wastewater pH monitoring system as a user interface and digitization process using Arduino and IoT modules as the leading processors. This application is also equipped with a real-time database that can be monitored at any time, pull report recaps using the Cloud Google Spreadsheet, and use the WhatsApp BOT as a chat notification that can notify the user if there is a drastic change in the pH value of wastewater from a predetermined standard value. This system consists of several pieces of hardware, namely a pH sensor, temperature sensor, Arduino module, IoT module, LCD, and a user interface using Android, which is simple and easy to read. In its implementation, this system can provide several benefits for wastewater management officers so that they can always monitor the pH level of wastewater in real-time through their Android devices without the need to be physically present to take and measure samples at the management location. This condition can improve efficiency in monitoring and facilitate taking actions and decisions if there is a significant change in the pH of the wastewater. In conclusion, using an Android-based wastewater pH monitoring system is very effective and efficient, especially for officers and analysts, and this Android-based wastewater pH monitoring system also has the accuracy of the measurement results. The accuracy of these measurement results is obtained from the results of a comparison of water pH measurement tests made with a pH meter at the Palembang BSPJI Laboratory, which has been accredited by the National Accreditation Committee (KAN) and has an Average Square Error of 0.02 where this value according to Standard IEC No.13b-23 is still within good tolerance limit is not more than 0.05. This states that the created water pH monitoring system produces valid and accurate data
Analisis Perbandingan Kinerja Web Server Nginx dan Litespeed Menggunakan Httperf Dengan Sistem Operasi Debian Cahyadi, Muhammad Leo; Setiawan, Herri; Mair, Zaid Romegar
Jurnal Pengembangan Sistem Informasi dan Informatika Vol. 4 No. 2 (2023): Jurnal Pengembangan Sistem Informasi dan Informatika (JPSII)
Publisher : Training & Research Institute - Jeramba Ilmu Sukses

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47747/jpsii.v4i2.1739

Abstract

The correct web server used by a website system can ensure that the website can always run properly. Currently, many web servers can be used to run website systems; the two most popular ones are Nginx and Litespeed. This research compares the performance of the two web servers by configuring Nginx and Litespeed on the same server. Then, using httperf testing as a tool in this study. There are research parameters, namely how the performance is in managing Throughput, Connection, and Reply. The flow in comparing the two web servers is by serving user requests; the testing load is in the form of connection number and rate. These results are based on the response time needed to serve each web server client request; Nginx and Litespeed have strong performance in handling heavy web traffic. Nginx tends to be superior in handling client requests quickly, with an average of 0.33 ms, compared to the Litespeed web server, which has an average of 0.34 ms
Penggunaan Metode Signature Based dalam Pengenalan Pola Serangan di Jaringan Komputer Setiawan, Herri; Munandar, M. Agus; Astuti, Lastri Widya
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 3: Juni 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021834200

Abstract

Masalah keamanan jaringan semakin menjadi perhatian saat ini. Sudah semakin banyak tools maupun teknik yang dapat digunakan untuk masuk kedalam sistem secara ilegal, sehingga membuat lumpuh sistem yang ada. Hal tersebut dapat terjadi karena adanya celah dan tidak adanya sistem keamanan yang melindunginya, sehingga sistem menjadi rentan terhadap serangan. Pengenalan pola serangan di jaringan merupakan salah satu upaya agar serangan tersebut dapat dikenali, sehingga mempermudah administrator jaringan dalam menanganinya apabila terjadi serangan. Salah satu teknik yang dapat digunakan dalam keamanan jaringan karena dapat mendeteksi serangan secara real time adalah Intrusion Detection System (IDS), yang dapat membantu administrator dalam mendeteksi serangan yang datang. Penelitian ini menggunakan metode signatured based dan mengujinya dengan menggunakan simulasi. Paket data yang masuk akan dinilai apakah berbahaya atau tidak, selanjutnya digunakan beberapa rule untuk mencari nilai akurasi terbaik. Beberapa rule yang digunakan berdasarkan hasil training dan uji menghasilakan 60% hasil training dan 50% untuk hasil uji rule 1, 50% hasil training dan 75% hasil uji rule 2, 75% hasil training dan hasil uji rule 3, 25% hasil training dan hasil uji rule 4, 50% hasil training dan hasil uji untuk rule 5. Hasil pengujian dengan metode signatured based ini mampu mengenali pola data serangan melaui protokol TCP dan UDP, dan monitoring yang dibuat mampu mendeteksi semua serangan dengan tampilan web base.AbstractNetwork security issues are becoming increasingly a concern these days. There are more and more tools and techniques that can be used to enter the system illegally, thus paralyzing the existing system. This can occur due to loopholes and the absence of a security system that protects it so that the system becomes vulnerable to attacks. The recognition of attack patterns on the network is an effort to make these attacks recognizable, making it easier for network administrators to handle them in the event of an attack. One of the techniques that can be used in network security because of a timely attack is the Intrusion Detection System (IDS), which can help administrators in surveillance that comes. This study used a signature-based method and tested it using a simulation. The incoming data packet will be assessed whether it is dangerous or not, then several rules are used to find the best accuracy value. Some rules used are based on the results of training and testing results in 60% training results and 50% for rule 1 test results, 50% training results and 75% rule 2 test results, 75% training results and rule 3 test results, 25% training results and the result of rule 4 test, 50% of training results and test results for rule 5. The test results with the signature-based method can recognize attack data patterns via TCP and UDP protocols, and monitoring is made to be able to detect all attacks with a web-based display.
Pengenalan Pola Serangan pada Internet of Thing (IoT) Menggunakan Support Vector Mechine (SVM) dengan Tiga Kernel Tasmi, Tasmi; Antony, Ferry; Dhamyanti, Dhamyanti; Setiawan, Herri; Oklilas, Fali
Jurnal PROCESSOR Vol 18 No 2 (2023): Jurnal Processor
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/processor.2023.18.2.1457

Abstract

Internet of things (IoT) technology is very popular these days around the world, with the development of IoT technology raises the impact of security threats and attacks on IoT devices. One of the most is the theft of data and information, one form of threat in IoT is malware. This research uses attacks in the form of bontet to detect attacks on the Internet of Things IoT) and uses Machine Learning to perform data detection of attacks on IoT devices. The method used in this research is Support Vector Mechine (SVM) by comparing three kernels namely Liner, polynominal and Radial Basis Function (RBF). This method is used to determine the level of accuracy in the detection process and compare between kernels. The results obtained are the accuracy value of 0.997 for the liner kernel, meaning that this kernel is able to separate the classes well, while the Polynomial kernel accuracy value of 0.993 is good in separating classes even though the value is smaller than the liner. Meanwhile, the RBF (Radial Basis Function) kernel has an accuracy of 1.0 (100%).
Pemberdayaan UMKM Kain Tenun Songket dan Kain Jumputan Binaan LPP-PEKKA Yayasan Masjid Agung Palembang untuk Meningkatkan Skala Produksi dan Pewarna Alami S.Si., M.Kom, Dr. Shinta Puspasari,; Setiawan, Herri; Viatra, Aji Windu; Yustini, Tien; Dhamayanti; Heriansyah, Rudi; Alie, Marzuki
Jurnal Abdimas Mandiri Vol. 7 No. 3
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jam.v7i3.3477

Abstract

Program Pembinaan Usaha Mikro Kecil dan Menengah (UMKM) Berbasis Kemitraan ini memiliki tujuan pembinaan, pemberdayaan, dan pemanfaatan bahan alami pewarna bahan kain di LPP-PEKKA Yayasan Masjid Agung Palembang. Program yang dirancang meliputi pelatihan Digital Marketing, Pelatihan Branding dan Packaging Produk, Pelatihan Manajemen Keuangan, dan Pelatihan Ketrampilan Produksi Pewarna Alami yang diikuti oleh 50 peserta UMKM LPP-PEKKA yang merupakan para pengerajin kain jumputan dan kain tenun songket Palembang. Metode pelatihan berupa penyampaian materi oleh narasumber, praktek langsung oleh para peserta, dan evaluasi kegiatan dengan pengisian kuesioner oleh peserta pelatihan. Hasil kegiatan menunjukkan adanya peningkatan pemberdayaan mitra yang mengalami peningkatan pengetahuan terkait materi pelatihan yang diberikan. Skor rata-rata peningkatan pengetahuan peserta sebesar 10%. Capaian luaran kegiatan PkM juga diukur dari peningkatan penerapan Iptek yang mendukung mitra UMKM LPP-PEKKA untuk memasarkan produk secara digital. Program ini diharapkan dapat meningkatkan skala produksi dan pewarna alami kain tenun songket dan kain Jumputan sebagai produk budaya tradisional Palembang sekaligus sebagai usaha untuk pelestarian budaya daerah. Dengan peningkatan pengelolaan keuangan dan peluang pasar produk hasil UMKM melalui pemasaran digital yang mampu menjangkau pasar global diharapkan dapat berdampak pada peningkatan perekonomian anggota UMKM LPP-PEKKA serta kelestarian lingkungan dengan pemanfataan pewarna alami yang ramah lingkungan dan aman bagi masyarakat
Co-Authors ., Tasmi Adiyatma, Muhammad Rifki Agustani, Adi Agustanti, Sri Primaini Ahmad Haidar Mirza Aji Windu Viatra Alie, Marzuki Antony, Ferry Budi Setiawan Cahyadi, Muhammad Leo DEWI SARTIKA Dhamayanti Dhamayanti Dhamayanti Dhamayanti, Dhamayanti Dhamyanti, Dhamyanti Edward, Edward Fajryn, Fikry Fakhry Zamzam Herry Pintardi Chandra Husnawati Husnawati Indah Permatasari Irvani, Muhammad Haviz Istiyanto, Jazi Eko Jazi Eko Istiyanto Lastri Widya Astuti, Lastri Widya Lestari, Sylvia Dwi Munandar, M. Agus N, Ashari S N, Ashari S Nurwijayanti Oklilas, Fali Pratama, M. Aditya Yoga Prayuda, Randy Purnamasari, Evi Purwo Santoso Ramadhan, Boy Gilang Ratnawidjaja, Soehendra Retantyo Wardoyo Rosyad, Nyimas Siti Rudi Heriansyah, Rudi S.Si., M.Kom, Dr. Shinta Puspasari, Santoso, Purwo Sarisstia, Tika Solekhan, Ahmad Tasmi, Tasmi Tien Yustini, Tien Zulhipni Reno Saputra Els