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All Journal Jurnal Informatika dan Teknik Elektro Terapan JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Teknologi dan Informasi Jurnal Mnemonic INFORMASI (Jurnal Informatika dan Sistem Informasi) Journal of Information Systems and Technology (JISTech) Media of Computer Science Jurnal Pusat Kolaborasi Pengabdian Kepada Masyarakat JROCK (Journal Research on Computing Knowledge)
Syaban, Kharis
Universitas Sembilanbelas November Kolaka
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science

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Sistem Informasi Geografis Distribusi Mahasiswa Kuliah Kerja Nyata Universitas Sembilanbelas November Kolaka Arysespajayadi; Kharis Syaban
INFORMASI (Jurnal Informatika dan Sistem Informasi) Vol 13 No 2 (2021): INFORMASI (Jurnal Informatika dan Sistem Informasi)
Publisher : LPPM STMIK Indonesia Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37424/informasi.v13i2.127

Abstract

Kuliah Kerja Nyata merupakan salah satu mata kuliah yang wajib diselesaikan oleh mahasiswa disuatu perguruan tinggi sebagai bentuk pengabdian masyarakat. Sistem pendataan terhadap lokasi diperlukan sebuah sistem dalam bentuk informasi geografis. Sistem Informasi Geografis dapat menampilkan tempat secara langsung mengenai lokasi mahasiswa dan dosen pembimbing. Perancangan sistem menggunakan bahasa pemrograman PHP dan database My-SQL serta untuk sistem pemetaan menggunakan Google Maps API yang dapat menampilkan informasi geografis bumi melalui bantuan koneksi internet ke server Google. Data yang digunakan adalah data mahasiswa, dosen pembimbing, dan tempat mahasiswa kuliah kerja nyata. Hasil penelitian yang telah dicapai adalah sistem dapat menampilkan informasi tempat berupa rute menuju tempat, dosen pembimbing serta informasi nama mahasiswa yang mengikuti kegiatan Kuliah Kerja Nyata.
Implementasi Analytical Hierarchy Process Dan Metode Perbandingan Eksponensial Untuk Pemberian Reward Karyawan Suharsono Bantun; Rabiah Adawiyah; Kharis Syaban; Dimas Febriyan Priambodo; Nirsal Nirsal; Suci Pricilia Lestari; Jayanti Yusmah Sari
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 10 No 1 (2023): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v10i1.3082

Abstract

Giving employee rewards for a company is one of the agendas that must be considered carefully. This is because the provision of rewards can be an indicator to encourage employees to work harder for more optimal company performance, but in reality it is difficult to determine employees who deserve to receive rewards because many employees are entitled to receive rewards but the quota is limited. This is the difficulty faced by PT. YZZ especially in providing annual rewards, because in the calculation process it has 5 assessment criteria so that in this case a decision support system is needed to assist managers in providing recommendations for employees who are entitled to receive rewards using the Analytical Hierarchy Process (AHP) and Metode Perbandingan Eksponensial (MPES). Based on the results of the study, there are several alternatives that are recommended to receive rewards so that it can be suggested in giving employee rewards.
PERANCANGAN SMART TRASH BIN MENGGUNAKAN LOGIKA FUZZY BERBASIS ARDUINO DI SDN 5 MAWASANGKA, BUTON TENGAH Nurjannah, Nurjannah; Muchtar, Mutmainnah; Sarimuddin, Sarimuddin; Sya'ban, Kharis; Karim, Rahmat; Al Jum'ah, Muhammad Na'im
Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 3 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3.4358

Abstract

Smart Trash Bin is a technological innovation that integrates sensors and automation systems to enhance waste management efficiency. This study aims to design and implement a Smart Trash Bin using fuzzy logic based on Arduino at SDN 5 Mawasangka, Buton Tengah. In this research, the system utilizes ultrasonic sensors to detect the trash level inside the bin, servo motors to control the automatic lid of the trash bin, and DFPlayer Mini along with a speaker to provide audio notifications to users. Fuzzy logic method is employed to regulate the system's decisions in managing the trash bin operations based on environmental conditions. The study involves the stages of design, fabrication, and system testing in the elementary school environment. The test results indicate that the designed Smart Trash Bin can effectively manage waste with adequate accuracy. It is expected that the implementation of this Smart Trash Bin can help raise awareness of environmental cleanliness within the school and surrounding community
Expert System for Determining Diseases and Pests in Seaweed Using Forward Chaining (Case Study : Watorumbe Village, Mawasangka Tengah) Asriani, Ika; Muchtar, Mutmainnah; Ismail, Rima Ruktiari; Paliling, Alders; Sya'ban, Kharis; Karim, Rahmat
Media of Computer Science Vol. 1 No. 1 (2024): June 2024
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v1i1.175

Abstract

Seaweed is a marine organism that plays a crucial role in both ecosystem and economy. However, it often faces attacks from diseases and pests that can jeopardize the productivity and sustainability of the seaweed industry. Hence, the development of an expert system to diagnose seaweed diseases and pests becomes imperative. This research aims to develop an Expert System for Determining Diseases and Pests in Seaweed using the Forward Chaining method, with a case study conducted in the Watorumbe Village, Mawasangka Tengah Sub-district, Southeast Sulawesi. The Forward Chaining method is employed to identify symptoms appearing in seaweed and determine potential diseases or pests. Testing is carried out with 30 data samples compared against expert diagnoses, resulting in an accuracy rate of 90%. Therefore, this system has the potential to assist seaweed farmers in diagnosing diseases and pests more quickly and accurately, thereby enhancing the productivity and sustainability of seaweed cultivation efforts.
Optimizing Information System Utilization through Strategic Planning using Ward-Peppard and Cassidy Methodology Kharis Syaban; Hamsinar, Henny
JISTech : Journal of Information Systems and Technology Vol. 2 No. 1 (2025): Juni 2025
Publisher : Perhimpunan Ahli Teknologi Informasi dan Komunikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71234/jistech.v2i1.32

Abstract

This research aims to optimize the utilization of information systems (IS) at Universitas Sembilanbelas November Kolaka through a strategic planning approach using the Ward-Peppard and Cassidy Methods. In the context of globalization and intense competition in higher education, appropriate strategies in IS management are crucial for institutional success. The Ward-Peppard and Cassidy Methods are used to design an IS strategic plan integrated with the organization's goals. The methodological steps include analysing the university's internal and external environment, identifying stakeholder needs and expectations, and formulating IS strategies that consider available resources and future development directions. A case study was conducted at Universitas Sembilanbelas November Kolaka, using a qualitative approach involving in-depth interviews with university leaders, administrative staff, and IS users. The research findings identify challenges in IS utilization, including a lack of integration between existing systems, the need for human resource skills development, and the maintenance of high-quality IT infrastructure. This study provides a comprehensive view of the IS strategies needed to enhance operational effectiveness and achieve the university's strategic goals. The practical implications of this research are the development of an action plan that can help the university manage and optimize their IS investments more effectively
KLASIFIKASI JENIS KAIN TENUN BUTON DENGAN METODE K-NN BERDASARKAN FITUR WARNA RGB DAN HSV SERTA EKSTRAKSI TEKSTUR DENGAN GLCM Sabi, Musini; Muchtar, Mutmainnah; Sya'ban, Kharis; Paliling, Alders; Miftachurohmah, Nisa; Karim, Rahmat
Jurnal Mnemonic Vol 8 No 1 (2025): Mnemonic Vol. 8 No. 1
Publisher : Teknik Informatika, Institut Teknologi Nasional malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/mnemonic.v8i1.13220

Abstract

Kain tenun Buton – Sulawesi Tenggara merupakan bentuk kreativitas tradisional masyarakat Buton dengan berbagai motif dan makna tersendiri. Namun, banyaknya jenis kain tenun Buton membuat tidak semua orang, termasuk masyarakat Buton, dapat mengenali jenisnya. Penelitian ini mengklasifikasikan citra kain tenun Buton menggunakan metode k-nearest neighbor (K-NN) dengan fitur warna RGB, HSV, dan GLCM. Dari hasil pengunjian yang telah dilakukan dengan menggunakan 150 citra uji, hasil cropping 2 loba yang terbagi ke dalam 10 kelas berbeda memperoleh nilai akurasi tertinggi yaitu 96% ketika menggunakan fitur RGB, 93,33% ketika menggunakan fitur HSV dan 88% ketika menggunakan fitur GLCM, pada masing-masing nilai k = 1 dan 2. Selain itu, pengujian juga dilakukan untuk 20 citra hasil cropping 4 loba dan memperoleh nilai akurasi tertinggi sebesar 95% ketika menggunakan fitur RGB pada nilai k = 1 dan 2, serta 100% ketika menggunakan fitur HSV pada nilai k = 3 dan 5. Akurasi yang cukup rendah yaitu sebesar 25% didapatkan ketika menggunakan fitur GLCM pada nilai k =1 sampai 5. Hasil ini menunjukkan bahwa metode K-NN dengan fitur warna RGB dan HSV memberikan akurasi tinggi dalam klasifikasi kain tenun Buton, sehingga dapat menjadi solusi efektif untuk identifikasi jenis kain secara otomatis
Pelatihan Penggunaan Aplikasi Penjualan Berbasis Barcode Pada Apotek Alwina II Kota Baubau Sarimuddin; Mutmainnah Muchtar; Rima Ruktiari Ismail; Muliyadi; Rahmat Karim; Kharis Sya’ban; Sunyanti; Hamid Wijaya; Muh. Na’im Al Jum’ah; Dirman
PUSAKA ABDIMAS Vol. 1 No. 1 (2024)
Publisher : Yayasan Serumpun Karang Konservasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61548/pa.v1i1.32

Abstract

Dalam era digital, penggunaan aplikasi penjualan menjadi sangat penting bagi apotek untuk meningkatkan efisiensi dan akurasi dalam proses administrasi penjualan serta manajemen persediaan. Kegiatan pengabdian ini bertujuan untuk meningkatkan efisiensi administrasi penjualan di Apotek Alwina Farma 2 Kota Bau-Bau melalui pelatihan penggunaan aplikasi penjualan berbasis barcode. Tim Pengabdian kepada Masyarakat (PkM) dari Universitas Sembilanbelas November (USN) Kampus B Buton Tengah mengembangkan aplikasi ini dan memberikan pelatihan intensif kepada para pegawai apotek. Evaluasi kegiatan dilakukan menggunakan lima item pertanyaan untuk mengukur pemahaman dan kemampuan operasional peserta terhadap aplikasi yang telah dikembangkan. Hasil evaluasi menunjukkan bahwa secara keseluruhan, para peserta mampu memahami dan mengoperasikan aplikasi penjualan berbasis barcode dengan baik. Pelatihan yang diberikan terbukti efektif dalam meningkatkan efisiensi proses administrasi penjualan di apotek, khususnya di Apotek Alwina Farma 2 Kota Bau-Bau. Diharapkan dengan adanya aplikasi ini, berbagai apotek lainnya juga dapat menerapkan teknologi serupa untuk meningkatkan efisiensi dan akurasi dalam proses penjualan dan manajemen persediaan.
Evaluasi Model Ensemble Learning pada Identifikasi Faktor Risiko Diabetes Mellitus Syaban, Kharis; Mardiawati
Jurnal Teknologi dan Informasi (JATI) Vol 15 No 2 (2025): Jurnal Teknologi dan Informasi (JATI)
Publisher : Program Studi Sistem Informasi, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jati.v15i2.16238

Abstract

Diabetes Mellitus (DM) adalah penyakit kronis dengan angka kejadian yang terus meningkat, terutama di negara berkembang. Mengidentifikasi faktor risiko DM merupakan langkah penting dalam upaya pencegahan dan deteksi dini. Studi ini menganalisis performa dari sejumlah pendekatan ensemble learning—meliputi bagging, boosting, stacking, dan voting—dalam upaya meningkatkan akurasi dan kestabilan prediksi risiko diabetes melitus. Analisis dilakukan menggunakan dataset PIMA Indians Diabetes yang telah melalui tahapan pra-pemrosesan dan diuji melalui eksperimen komputasi. Model dasar seperti Logistic Regression, Support Vector Machine, dan Random Forest dikombinasikan dengan teknik ensemble untuk meningkatkan keandalan prediksi. Evaluasi dilakukan dengan metrik akurasi, Mean Squared Error (MSE), dan R² Score. Hasil menunjukkan bahwa semua metode ensemble mencapai akurasi tinggi sebesar 97%, namun memiliki perbedaan dalam R² Score—Gradient Boosting memiliki nilai tertinggi (0.65), diikuti oleh Stacking (0.63) dan AdaBoost (0.64). Ini menunjukkan bahwa meskipun akurasi konsisten, kemampuan model dalam menjelaskan variabilitas target bergantung pada teknik ensemble yang digunakan. Penelitian ini mengonfirmasi bahwa ensemble learning meningkatkan kinerja prediktif dibandingkan model individu dan memiliki potensi besar dalam skrining diabetes berbasis komunitas, sebagaimana dibahas dalam literatur terbaru.
Pengembangan Sistem Informasi Seleksi Penerimaan Bantuan Langsung Tunai Menggunakan Metode K-Nearest Neighbor Hardianto; Kharis Syaban; Ery Muchyar Hasiri
JISTech : Journal of Information Systems and Technology Vol. 1 No. 2 (2024): Desember 2024
Publisher : Perhimpunan Ahli Teknologi Informasi dan Komunikasi Indonesia

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

Abstract

The implementation of the Cash Transfer Assistance (BLT) program in Indonesia aims to assist economically disadvantaged communities, especially during crises such as the pandemic. However, the selection process for BLT recipients often faces challenges related to accuracy and efficiency, particularly in determining eligible recipients based on various economic and social criteria. This research develops an information system based on the K-Nearest Neighbor (K-NN) method to address these issues. The system is designed to classify BLT candidates by considering several variables, such as family income, number of dependents, employment status, housing conditions, and family health. The optimal K value was determined through trial and error to achieve the highest accuracy. The system was tested using both training and testing data, and the evaluation results showed an accuracy rate of 85%. This information system not only processes data quickly but also provides transparent and objective results, making it useful for village authorities to efficiently select BLT recipients. By implementing the K-NN algorithm, this system is expected to offer a practical solution for village governments in improving the accuracy of aid distribution to eligible communities.
Sistem Pendukung Keputusan Seleksi Peserta Pelatihan di UPTD BLKK Kolaka dengan Metode TOPSIS Hidayatullah, Muh. Ilham; Sunyanti, Sunyanti; Syaban, Kharis
Journal Research on Computing Knowledge Vol. 1 No. 2 (2025): Maret 2025
Publisher : Fakultas Teknologi Informasi

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

Abstract

The participant selection process for training at UPTD BLKK Kolaka remains manual, resulting in inefficiency and potential subjectivity in decision-making. This paper formulates a Decision Support System (DSS) utilizing the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique to resolve this issue. This method is selected for its ability to yield optimal participant recommendations by evaluating proximity to both positive and negative ideal solutions. The system is constructed utilizing PHP and MySQL for the storage of participant data and computation outcomes. The research phases encompass needs analysis, system design, implementation, and testing using Black Box Testing. The outcomes of manual and system calculations demonstrate consistency in preference values, confirming that the TOPSIS method effectively identifies the most appropriate training participants. This approach accelerates the selection process, enhancing transparency and objectivity. The deployment of a TOPSIS-based Decision Support System is anticipated to enhance efficiency and precision in decision-making, guaranteeing that chosen participants fulfill the requisite requirements
Co-Authors Al Jum'ah, Muhammad Na'im alders paliling Arysespajayadi Arysespajayadi Asriani, Ika Dimas Febriyan Priambodo Dirman Ery Muchyar Hasiri Hamid Wijaya Hardianto Henny Hamsinar Hidayatullah, Muh. Ilham Ismail, Rima Ruktiari Jayanti Yusmah Sari La Ode Hasnuddin S. Sagala Mardiawati Miftachurohmah, Nisa Muh. Na’im Al Jum’ah Muliyadi Mutmainnah Muchtar Nirsal Nirsal Nisa Miftahurochmah Nurjannah Nurjannah Rabiah Adawiyah Rahmat Karim Resitha Sampe Membunga Rima Ruktiari Sabi, Musini Sarimuddin, Sarimuddin Suci Pricilia Lestari Suharsono Bantun Sunyanti Sunyanti, Sunyanti