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All Journal JURNAL SISTEM INFORMASI BISNIS Jurnal Sains dan Teknologi E-Dimas: Jurnal Pengabdian kepada Masyarakat Jurnal Ilmiah FIFO JURNAL ILMIAH GEOMATIKA JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Pilar Nusa Mandiri Tekinfo | Scientific Journal of Industrial and Information Engineering Indonesian Journal of Artificial Intelligence and Data Mining JURNAL REKAYASA TEKNOLOGI INFORMASI ILKOM Jurnal Ilmiah J-SAKTI (Jurnal Sains Komputer dan Informatika) Building of Informatics, Technology and Science Jurnal Sistem Komputer dan Informatika (JSON) Madani : Indonesian Journal of Civil Society Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Journal of System and Computer Engineering Bulletin of Computer Science Research GANESHA: Jurnal Pengabdian Masyarakat PROFICIO: Jurnal Pengabdian Masyarakat Jurnal Pengabdian Masyarakat (ABDIRA) J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Informatika, Komputer dan Bisnis (JIKOBIS) Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Journal of Applied Agricultural Science and Technology Malcom: Indonesian Journal of Machine Learning and Computer Science International Journal of Economics and Management Research Journal of Digital Law and Policy Bulletin of Informatics and Data Science INTERNATIONAL JOURNAL OF SOCIETY REVIEWS (INJOSER) Science Information System and Technology West Science Nature and Technology Journal of Information System and Application Development International Journal of Economics and Management Research
Moh. Erkamim
Universitas Tunas Pembangunan Surakarta
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities 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 Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Nursing Public Health Social Sciences Other

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Komparasi Algoritme Random Forest dan XGBoosting dalam Klasifikasi Performa UMKM Moh Erkamim; Suswadi Suswadi; Muhammad Zidni Subarkah; Erni Widarti
Jurnal Sistem Informasi Bisnis Vol 13, No 2 (2023): Volume 13 Nomor 2 Tahun 2023
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol13iss2pp127-134

Abstract

The Covid-19 pandemic has greatly impacted the whole world, especially Indonesia. Various policies have been implemented starting from the implementation of lockdowns, restrictions on large-scale economic activities, and bans from leaving the region. The economic sector is a sector that has been affected quite a lot, one of which is Micro, Small, and Medium Enterprises (MSMEs). As a result of the Covid-19 pandemic, many MSMEs have suffered losses, so many investors have started to consider investing in MSMEs. Therefore, MSMEs need to know their business performance through potential analysis and financial reports to deal with the economic crisis during a pandemic. This study compares two algorithms namely Random Forest and XGBoosting in classifying the good or bad performance of MSME financial conditions. The performance of the developed algorithm will be improved using hyperparameter tuning to obtain the best parameter combination for each algorithm. In this study, the Random Forest algorithm has an accuracy value of 0.944 and an f1-score of 0.944, while the XGBoosting algorithm has an accuracy value of 0.944 and an f1-score of 0.950. Based on the model with the best evaluation metric, six important features are obtained: the 2021 profit and loss variable, 2020 cash, 2020 liabilities, 2020 capital, 2021 sales, and 2021 liabilities.
Penerapan Algoritma K-Nearest Neighbor untuk Analisis Sentimen Terhadap Isu Khilafah dan Radikalisme di Indonesia: Implementation K-Nearest Neighbor Algorithm for Sentiment Analysis on Khilafah and Radicalism Issues in Indonesia Legito Legito; Nindi Permata Riau; Adi Nugroho Susanto Putro; Eri Mardiani; Nofri Yudi Arifin; Sepriano Sepriano; Moh. Erkamim
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 3 No. 2 (2023): MALCOM October 2023
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v3i2.893

Abstract

Seiring dengan majunya teknologi, media sosial merupakan salah satu alternatif untuk mendapatkan dan menyebarkan informasi dengan cepat. Salah satu media sosial yang saat ini digunakan yaitu Twitter. Terdapat banyak topik yang diperbincangkan salah satunya mengenai Khilafah. Khilfah merupakan suatu institusi politik yang tidak dapat diasingkan dari aktivitas politik, dimana munculnya setelah sepeninggal Rasulullah untuk dapat meneruskan kepemimpinannya. Khilafah biasanya dikaitkan dengan yang namanya Radikalisme. Opini tentang khilafah dan radikalisme tidak pernah berhenti diperbincangkan dikalangan masyarakat, oleh karena itu dibutuhkan analisa sentimen untuk menganalisa tanggapan masyarakat di Indonesia mengenai pernyataan khilafah tersebut. Analisa sentimen ini menggunakan Algoritma  K-Nearest Neighbor atau K-NN. Berdasarkan hasil yang telah dilakukan menunjukkan bahwa Algoritma  K-NN memperoleh hasil akurasi yang tinggi yaitu 92.11% dan 88,2% pada masing-masing kata kunci Khilafah dan Radikalisme dengan menggunakan 5000 data yang terdapat pada twitter.
Analysis of Threat Detection, Prevention Strategies, and Cyber Risk Management for Computer Network Security in Government Information Systems in Indonesia Loso Judijanto; Rifky Lana Rahardian; Hanifah Nurul Muthmainah; Moh. Erkamim
West Science Information System and Technology Vol. 1 No. 02 (2023): West Science Information System and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsist.v1i02.479

Abstract

This research investigates the landscape of threat detection, prevention strategies, and cyber risk management within Government Information Systems in Indonesia. A quantitative approach, employing Structural Equation Modeling - Partial Least Squares (SEM-PLS), was utilized to analyze data collected from 150 participants across diverse government institutions. The study assessed perceived cyber threats, the effectiveness of threat detection mechanisms, prevention strategy implementation, and cyber risk management practices. Findings revealed significant regional variations in threat perception and underscored the importance of both technological and human-centric approaches. The Structural Equation Model demonstrated satisfactory fit, with notable path coefficients indicating strong relationships among latent variables. The study contributes valuable insights to cybersecurity practices in the Indonesian government sector, informing policymakers and practitioners on strategies to enhance network security resilience.
Implementation of Digitalization of City Infrastructure for Improved Sustainability: Case Study on Smart City Project in Surabaya, Indonesia Loso Judijanto; Moh. Erkamim; Erlin Dolphina; I Wayan Karang Utama
West Science Nature and Technology Vol. 1 No. 02 (2023): West Science Nature and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsnt.v1i02.488

Abstract

The application of digitalization in urban contexts, particularly through Smart City initiatives, has become an important avenue to address the complexities of modern urban life. This study focuses on the Smart City Project in Surabaya, Indonesia, aiming to quantitatively analyze the impact of digitalization on sustainability indicators from a community perspective. A quantitative approach, including a survey of 190 residents and regression analysis, was used to comprehensively explore the relationship between demographic factors, perceptions of digital infrastructure and sustainability outcomes. The results showed statistically significant improvements in sustainability indicators, with waste reduction behavior and community satisfaction being particularly important. Regression analysis shows that age, income, and digital literacy significantly influence sustainability outcomes. These findings contribute to the growing body of knowledge on Smart Cities initiatives, offering insights for policymakers, urban planners, and community leaders to increase the effectiveness of digitalization in fostering sustainable urban environments.
Sosialisasi dan Pelatihan Pemanfaatan Elearning Menggunakan Web Conference Vera Wati; Moh. Erkamim; Wartono Wartono
E-Dimas: Jurnal Pengabdian kepada Masyarakat Vol 14, No 4 (2023): E-DIMAS
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/e-dimas.v14i4.13562

Abstract

Elearning UTP adalah sistem pembelajaran yang dapat digunakan dosen dengan memanfaatkan elektronik berbasis website. Elearning UTP menjadi platform dengan Moodle jenis LMS dengan menyediakan proses belajar mengajar yang komprehensif. Salah satu fitur yang tersedia yaitu web telekonferensi dengan BigBlueButton yang mendukung tatap muka virtual. Sebelum terselenggaranya pengabdian masyarakat sosialisasi platform elearning milik UTP, dosen masih memanfaatkan platform open source dengan fasilitas basic yang dibatasi fasilitasnya. Kurangnya pengetahuan dan pelatihan penggunaan menjadi faktor utama platform elearning UTP belum dikenali dan dimanfaatkan pada semua dosen. Sehingga tujuan dari kegiatan sosialisasi ini adalah memberikan pendampingan penggunaan web telekonferensi yang terintegrasi pada elearning UTP. Alasan lain yaitu mempermudah dosen dan mahasiswa UTP mengelola pembelajaran berbasis website karena terdokumentasi dalam satu platform milik institusi. Metode pelaksanaan dengan demonstrasi pelatihan penggunaan sistem dan tanya jawab antar pemateri dan peserta. Pemateri mengikuti instruksi pengelolaan pada kursus masing-masing. Kegiatan dihadiri 24 peserta yang diwakili dari masing-masing program studi, selain itu tim pemateri disampaikan 2 dosen, 1 pembawa acara serta 3 mahasiswa sebagai pendukung pelaksanaan. Sehingga kegiatan ini dapat berjalan dengan lancar, karena jika ada peserta mengalami kesulitan dapat dibantu oleh penyelenggara yang sudah dibekali pengetahuan penggunaan elearning UTP. 
PENGGUNAAN NETWORK ANALYSIS UNTUK PENENTUAN AKSESIBILITAS LOKASI SEKOLAH DI WILAYAH PERBATASAN NEGARA Studi Kasus: Kabupaten Malinau Muhammad Rizal Fernandita Pamungkas; Anindya Putri Tamara; Moh Erkamim; Shabrina Hapsari
Geomatika Vol. 29 No. 1 (2023): JIG Vol 29 No 1 Tahun 2023
Publisher : Badan Informasi Geospasial

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Kabupaten Malinau merupakan wilayah perbatasan negara yang memerlukan perbaikan kualitas pendidikan karena angka partisipasi sekolah mengalami penurunan pada jenjang sekolah menengah. Penelitian ini bertujuan untuk mengetahui tingkat aksesibilitas lokasi sekolah di Kabupaten Malinau dengan memanfaatkan network analysis. Data yang digunakan pada penelitian ini adalah data sekunder seperti data persebaran sekolah, persebaran permukiman, jumlah penduduk dan jaringan transportasi. Metode penelitian menggunakan sistem informasi geografis berbasis kriteria untuk menentukan tingkat aksesibilitas sekolah di Kabupaten Malinau. Tingkat aksesibilitas diukur berdasarkan jarak sekolah dengan pusat permukiman terdekat melalui jaringan jalan. Hasil penelitian menunjukkan 39,08% dari total jumlah sekolah di Kabupaten Malinau tergolong akses sulit dan akses sangat sulit. Sebagian besar persebaran sekolah tersebut terletak di wilayah perbatasan negara dengan kondisi akses jalan yang terbatas maupun akibat limitasi alam. Kondisi tersebut berdampak pada rendahnya rasio guru murid di Kabupaten Malinau. Penggunaan network analysis dapat membantu untuk mengurangi kesenjangan pembangunan di Kabupaten Malinau serta dalam perencanaan pembanguann fasilitas pendidikan dan jaringan transportasi.
Sportif.App as an Effort to Increase Sports Human Resources Readiness and Digitalization of Sports Data Information Management Fatkhul Imron; Joko Sulistyono; Moh Erkamim; Zandra Dwanita Widodo
International Journal of Economics and Management Research Vol. 2 No. 1 (2023): April : International Journal of Economics and Management Research
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/ijemr.v3i1.223

Abstract

This research is a continuation of community service activities entitled "Introduction and Training of the Sportif.App Application as an Effort to Increase the Readiness of Sports Human Resources and Digitalization of Sports Data Information Management at KONI Surakarta City." Through this tridharma activity, the writing team continued with research aimed at describing and analyzing the benefits of Sportif.App in increasing the readiness of sports human resources through digitizing sports data information management. The research method used is descriptive qualitative which is based on the results of interviews and observations. The Sportif.App application really helps sports human resources by providing data management services that are easy to access and provide information at any time. Administrative requirements can be integrated with sports databases (such as sports, achievements, coaches, referees, etc.), documented, and uploaded through the information system, including verification mechanisms and information about required administrative completeness, as well as monitoring data progress. In this way, sports human resources can work effectively and efficiently in reporting at any time without being limited by time and space. Keywords : Sportif.app, information management, sports data information
Pengembangan Fasilitas Internet Guna Peningkatan Pelayanan Administrasi Kemasyarakatan wartono; Vera Wati; Erni Widarti; Moh Erkamim; Muhammad Rizal Pamungkas Fernandita; Danarti Karsono
GANESHA: Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2024): Juli 2024
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Tunas Pembangunan Surakarta (UTP)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36728/ganesha.v4i2.3676

Abstract

Balai Desa Banyurip di Kecamatan Jenar, Kabupaten Sragen, masih minim dalam pemanfaatan internet di balai desanya untuk pelayanan publik. Hal ini disebabkan oleh sulitnya sinyal di area blank spot tersebut, akibat kondisi geografis yang menantang dan kurangnya infrastruktur pendukung seperti BTS (Base Transceiver Station). Padahal Balai Desa merupakan pusat layanan publik dan kegiatan pemerintahan desa, seperti pengelolaan, pembuatan, dan pembauatan surat pengantar dokumen kependudukan, pengurusan izin usaha, program pembangunan, penyaluran bantuan sosial, serta kegiatan sosial dan budaya. Sehingga untuk mengatasi hal ini, tim pengabdian mengembangkan fasilitas internet guna meningkatkan pelayanan administrasi kemasyarakatan. Metode pelaksanaan kegiatan dengan melakukan proyek insiatif untuk menyediakan perangkat keras, konfigrurasi akses internet yang dibutuhkan, serta pelaksanaan monitoring. Pelaksanaan kegiatan pengabdian menjadi 2 tahapan utama, yaitu tahapan analisis pemecahan masalah dan pelaksanaan pengabdian kepada masyarakat pada mitra. Sehingga dihasilkan, pemasangan berhasil dilakukan secara gratis tanpa biaya langganan, dengan kecepatan 50 Mbps tanpa batasan kuota dan tersedia selama jam operasional Balai Desa Banyurip. Pengaturan ini memastikan penggunaan fasilitas internet secara efektif selama jam kerja pelayanan. Pemasangan fasilitas internet terletak pada lokasi yang strategis yaitu bagian depan pada kantor pelayanan. Internet ini menggunakan dedicated 1:1 simetris, yang berarti kecepatan unggah dan unduh sama cepatnya. Fasilitas ini dapat meningkatkan efisiensi administrasi dan mendukung berbagai kegiatan masyarakat dengan akses internet yang andal dan stabil
Sentiment Analysis of Shopee App Reviews Using Random Forest and Support Vector Machine Suswadi, Suswadi; Erkamim, Moh.
ILKOM Jurnal Ilmiah Vol 15, No 3 (2023)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v15i3.1610.427-435

Abstract

During the COVID-19 outbreak, Indonesian marketplaces were significantly impacted including Shopee app. It is necessary to evaluate the features and services of the Shopee application by looking at the feedback given by the public in Google Play Store reviews. This is what prompted research to be conducted from Kaggle data in the form of Shopee reviews. From this data, sentiment analysis is carried out utilizing the Support Vector Machine (SVM) and Random Forest methods. This method are used to classify reviews based on positive and negative sentiments. The results showed that the level of classification accuracy in the Random Forest model is 82.21%. While the SVM model provides a higher level of accuracy of 84.71%. Data exploration on positive and negative sentiment classes is used to find insight into this problem. In positive sentiment, words that often appear such as “belanja”, “aplikasi”, and “barang” are found. As for the negative sentiments, namely “ongkir”, “kirim”, “aplikasi”. These words can be used to be a quality improvement or evaluation for the Shopee company.
IDENTIFICATION OF POTATO LEAF DISEASES USING ARTIFICIAL NEURAL NETWORKS WITH EXTREME LEARNING MACHINE ALGORITHM Erkamim, Moh.; Septarini, Ri Sabti; Tonggiroh, Mursalim; Nurhayati, Siti
Jurnal Pilar Nusa Mandiri Vol. 20 No. 1 (2024): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v20i1.5307

Abstract

Potato plants have an important role in providing a source of carbohydrates for society. However, potato production is often threatened by various plant diseases, such as leaf disease, which can cause a decrease in yields. Identification of diseases on potato leaves is currently mostly done by farmers manually, so it is not always efficient and accurate. So the aim of this research is to identify diseases on potato leaves with artificial neural networks using the ELM (Extreme Learning Machine) approach and the GLCM (Gray Level Co-Occurrence Matrix) method for feature extraction. The GLCM approach functions to obtain texture features on objects by measuring how often certain pairs of pixel intensities appear together at various distances and directions in the image. Meanwhile, the ELM algorithm is used for image identification by adopting a one-time training method without iteration, which involves randomly determining weights and biases in hidden layers, thus allowing training to be carried out quickly and efficiently. Evaluation of the model by looking for the level of accuracy produces a value of 84.667%. The results show that the model developed is capable of accurate identification.
Co-Authors A. Bamban Yuuwono Adi Candra, Adi Adi Nugroho Susanto Putro Adi Nur Khofid Aini, Delvi Nur Alfry Aristo Jansen Sinlae Ali Zainal Abidin Alaydrus Allesandro Umbu Balla Rundi Anindya Putri Tamara Argia Putri Ramadhani Arisantoso Arisantoso Asih Lestari, Asih Batubara, Ana Uzla Cantikasari, Yuliana Danarti Karsono Daniarti, Yeni Destriana, Rachmat Dwi Susilo Utami Edhi Prayitno, Edhi Egidius Fkun Eri Mardiani Erlin Dolphina Erni Widarti Farid Fitriyad Fatihah, Syalaysa Imani Fatkhul Imron Faustina Yuniastuti Faustina Yuniastuti Fitriyad, Farid Fitriyadi, Farid Fitriyadi, Farid Handayani, Nurdiana Hanifah Nurul Muthmainah Heriyani, Nofitri Hidayati , Diyah Nur I Gede Iwan Sudipa I Wayan Karang Utama Imam Setyo Nugroho Indriastiningsih, Erna Irfan AP Joko Sulistyono Judijanto, Loso Khofid, Adi Nur Khoirun Nisa Legito . legito, Legito Lilik Suhery, Lilik Loso Judijanto Maharani, Annissa Tiara Mohammad Imam Shalahudin Muhammad Muharrom Muhammad Rizal Fernandita Pamungkas Muhammad Rizal Fernandita Pamungkas Muhammad Syarif Hartawan Muhammad Zidni Subarkah Mulyadi Mulyadi Mustakim Mustakim Muthmainah, Hanifah Nurul Naylah Dzakiah Ngakan Kompiang Adi Suardana Ni Kadek Sri Devi Putri Swambini Ni Kadek Wintan Purnama Sari Ni Ketut Tri Srilaksmi Ni Komang Triana Andini Ni Made Ayu Nadia Putri Damayanti Nindi Permata Riau Nirma Ceisa Santi Nofri Yudi Arifin novi yona sidratul munti Nugraha, Tegar Wijanarko Surya Nurhayati Nurhayati Pamungkas, M Rizal Fernandita Pamungkas, Muh. Rizal F. Pamungkas, Muhammad Rizal Fernandita Rahmat Catur Haryadi Rahmat Catur Haryadi Ramadhani, Argia Putri Rifky Lana Rahardian Riyanto, Umbar Rundi, Allesandro U.B. Rundi, Allesandro Umbu Balla Said Thaufik Rizaldi Saifuddin Saifuddin Saifuddin Saifuddin Sandra Dewi Saraswati Sapto Priyadi Sepriano Sepriano Septarini, Ri Sabti Setyawati, Nisrina Yulia Shabrina Hapsari Shalahudin, Mohammad Imam Siti Nurhayati Sitti Rachmawati Soares, Teotino Gomes Subarkah, Muhammad Zidni Sulhatun Sulhatun Sulistiyawati, Anggun Supartini Supartini Suswadi Syahputra, Ridwan Angga Tami, Nanda Putri Tanniewa, Adam M Tino Feri Efendi Tonggiroh, Mursalim Tyas Soemarah Kurnia Dewi Tyas SOEMARAH KURNIA DEWI Utama, I Wayan Karang Vera Wati Wardani, Qurrotul Ain Putri Kusuma Wartono Wartono Wartono Wartono Wartono, W Wati, Vera Winalia Agwil Wiyono wiyono Yanuardi Yanuardi Yuri Rahmanto Zandra Dwanita Widodo Zandra Dwanita Widodo Zilrahmi, Zilrahmi