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SISTEM PENDUKUNG KEPUTUSAN PENILAIAN KINERJA TENAGA PENDIDIK DENGAN METODE PROFILE MATCHING Yuwanda, Yuwanda; Apdillah, Dicky
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 1 (2025): February 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i1.2374

Abstract: The performance assessment of educators is an evaluation conducted through observation and monitoring of each main task of educators in the context of career development, rank, and position. The performance assessment of educators includes their ability to master knowledge, skills, and professional attitudes as educators. To determine the quality of the human resources of educators, one of the efforts that can be made is by conducting performance evaluations. As an educational institution, the quality of human resources it possesses greatly impacts the quality of its students. The purpose of this research is to analyze a decision support system using the profile matching method in the performance assessment of educators. The data input into the system includes the alignment of lesson implementation with the lesson schedule, punctuality, mastery of the material, and other aspects related to teaching. From the results of the system testing conducted, the scores obtained were as follows: Supriyati, S.Pd (4.25) with a very suitable predicate, Siti Malihatun Nikmah, S.PD (3.70) with a suitable predicate, Kusmini, S.Pd (3.60) with a suitable predicate, Singgih Peranowo, S.Pd (3.20) with a suitable predicate, Nursamsyiah, S.Pd (3.10) with a suitable predicate, Sunarso, S.Sn (2.90) with an unsuitable predicate. Based on these results, an evaluation can be conducted on Sunarso, S.Sn (2.90) regarding his teaching performance. Keywords: Profile Matching, Decision Support System, Educator Performance Assessment, Web. Abstrak: Penilaian kinerja tenaga pendidik merupakan penilaian yang dilakukan melalui pengamatan dan pemantauan pada setiap butir tugas utama tenaga pendidik dalam rangka pembinaan karir, kepangkatan, dan jabatannya. Penilaian kinerja tenaga pendidik meliputi kemampuan tenaga pendidik dalam menguasai pengetahuan, keterampilan, dan sikap profesional sebagai pendidik. Untuk mengetahui kualitas SDM tenaga pendidik, salah satu upaya yang dapat dilakukan adalah dengan melakukan penilaian kinerja. Sebagai sebuah institusi pendidikan, kualitas SDM yang dimiliki sangat berdampak pada kualitas peserta didik. Tujuan penelitian ini untuk menganalisa sebuah sistem pendukung keputusan dengan metode profile matching pada penilaian kinerja tenaga pendidik. Data yang di input ke dalam sistem ialah data kesesuaian pelaksanaan pembelajaran dengan jadwal pembelajaran, ketepatan waktu, penguasaan materi, dan lain-lain yang terkait pembelajaran. Dari hasil pengujian sistem yang dilakukan terdapat nilai perolehan Supriyati, S.Pd (4,25) predikat sangat sesuai, Siti Malihatun Nikmah, S.PD (3,70) predikat sesuai, Kusmini, S.Pd (3,60) predikat sesuai, Singgih Peranowo, S.Pd (3,20) predikat sesuai, Nursamsyiah, S.Pd (3,10) predikat sesuai, Sunarso, S.Sn (2,90) predikat tidak sesuai, dari hasil tersebut dapat dilakukan evaluasi terhadap Sunarso, S.Sn (2,90) atas kinerja pengajaran. Kata kunci: Profile Matching, Sistem Pendukung Keputusan, Penilaian Kinerja Tenaga Pendidik, Web.

Analysis of Fertilizer Requirements in Red Chili Cultivation Using an Artificial Neural Network Approach Marpaung, Mairani; Apdillah, Dicky; Ayyub, Muhammad Azwar Al
IJISTECH (International Journal of Information System and Technology) Vol 8, No 6 (2025): The April edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v8i6.387

Red chili farmers on the East Coast of North Sumatra still rely on manual calculations to determine the use of NPK Biru 16 Mutiara fertilizer, often leading to inaccurate and inefficient fertilizer application. This study proposes the Backpropagation method within Artificial Neural Networks (ANN) as a solution to analyze fertilizer needs more precisely. The method enables the system to learn from historical data and plant growth patterns, providing accurate recommendations for the type and amount of fertilizer required. The implementation of ANN in this context not only enhances agricultural efficiency but also supports environmental sustainability by minimizing excessive fertilizer usage.

Analysis of the Potential and Business Development Opportunities in Catfish Farming Using Artificial Neural Networks Rianda, Kiki Rizki; Apdillah, Dicky
IJISTECH (International Journal of Information System and Technology) Vol 8, No 6 (2025): The April edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v8i6.384

In recent years, there has been a significant increase in catfish consumption. The average consumer demand reaches 50 to 100 kg with a catfish harvest age of about 2.5 months. Catfish farming has not only increased the income of the community but has also transformed those who previously had no knowledge of how to farm catfish and the potential of utilizing yard land into successful catfish farmers. In connection with this, the author intends to recognize more deeply the potential and opportunities of catfish farming in Air Hitam Village, Kualuh Leidong District. In this research, the author applies the Learning Vector Quantization (LVQ) method, which is one of the approaches in Artificial Neural Networks. Learning Vector Quantization (LVQ) is a competitive layer training technique with a supervised learning approach, which uses a network structure with a single layer. The use of Artificial Neural Network (ANN) is a sophisticated way that can be applied to manage catfish farming business. The results showed that the use of the LVQ method in analyzing catfish farming data can help farmers make more informed decisions, predict business development, and increase yields and profits.

Analysis of Nutritional Needs In Elementary School-Aged Children In Remote, Underdeveloped, and Border Regions Using Android-Based Artificial Neural Network Method Febriani, Arisa; Apdillah, Dicky
IJISTECH (International Journal of Information System and Technology) Vol 8, No 6 (2025): The April edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v8i6.385

The nutritional needs of elementary school children are very important to support their growth, development, and learning abilities. Good nutrition is essential to support the growth of bones, muscles, and organs. In addition, protein, calcium, and iron intake are very important. Nutrition also affects brain function, including children's concentration and memory. One of the schools where various factors related to children's nutrition can be studied is State Elementary School 134633 Tanjung Balai. It is hoped that the analysis of nutritional needs in school children can provide an overview of food consumption patterns, nutritional status, and the factors that influence them. The system developed using the Artificial Neural Network (ANN) model with the Backpropagation algorithm successfully analyzed the nutritional status of children based on the data provided. By categorizing nutritional status into thin, fat, and normal, the system can provide adequate results for the nutritional analysis needs of Elementary School Children in the 3T Area.

Analysis of the Potential and Business Development Opportunities in Catfish Farming Using Artificial Neural Networks Rianda, Kiki Rizki; Apdillah, Dicky
IJISTECH (International Journal of Information System and Technology) Vol 8, No 6 (2025): The April edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v8i6.384

In recent years, there has been a significant increase in catfish consumption. The average consumer demand reaches 50 to 100 kg with a catfish harvest age of about 2.5 months. Catfish farming has not only increased the income of the community but has also transformed those who previously had no knowledge of how to farm catfish and the potential of utilizing yard land into successful catfish farmers. In connection with this, the author intends to recognize more deeply the potential and opportunities of catfish farming in Air Hitam Village, Kualuh Leidong District. In this research, the author applies the Learning Vector Quantization (LVQ) method, which is one of the approaches in Artificial Neural Networks. Learning Vector Quantization (LVQ) is a competitive layer training technique with a supervised learning approach, which uses a network structure with a single layer. The use of Artificial Neural Network (ANN) is a sophisticated way that can be applied to manage catfish farming business. The results showed that the use of the LVQ method in analyzing catfish farming data can help farmers make more informed decisions, predict business development, and increase yields and profits.

Analysis of Nutritional Needs In Elementary School-Aged Children In Remote, Underdeveloped, and Border Regions Using Android-Based Artificial Neural Network Method Febriani, Arisa; Apdillah, Dicky
IJISTECH (International Journal of Information System and Technology) Vol 8, No 6 (2025): The April edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v8i6.385

The nutritional needs of elementary school children are very important to support their growth, development, and learning abilities. Good nutrition is essential to support the growth of bones, muscles, and organs. In addition, protein, calcium, and iron intake are very important. Nutrition also affects brain function, including children's concentration and memory. One of the schools where various factors related to children's nutrition can be studied is State Elementary School 134633 Tanjung Balai. It is hoped that the analysis of nutritional needs in school children can provide an overview of food consumption patterns, nutritional status, and the factors that influence them. The system developed using the Artificial Neural Network (ANN) model with the Backpropagation algorithm successfully analyzed the nutritional status of children based on the data provided. By categorizing nutritional status into thin, fat, and normal, the system can provide adequate results for the nutritional analysis needs of Elementary School Children in the 3T Area.

Analysis of Fertilizer Requirements in Red Chili Cultivation Using an Artificial Neural Network Approach Marpaung, Mairani; Apdillah, Dicky; Ayyub, Muhammad Azwar Al
IJISTECH (International Journal of Information System and Technology) Vol 8, No 6 (2025): The April edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v8i6.387

Red chili farmers on the East Coast of North Sumatra still rely on manual calculations to determine the use of NPK Biru 16 Mutiara fertilizer, often leading to inaccurate and inefficient fertilizer application. This study proposes the Backpropagation method within Artificial Neural Networks (ANN) as a solution to analyze fertilizer needs more precisely. The method enables the system to learn from historical data and plant growth patterns, providing accurate recommendations for the type and amount of fertilizer required. The implementation of ANN in this context not only enhances agricultural efficiency but also supports environmental sustainability by minimizing excessive fertilizer usage.

PENERAPAN ALGORITMA EDGE DETECTION DAN CLUSTERING MENGIDENTIFIKASI PENGENALANWAJAH DALAM E-ABSENSI Rahmadani, Desy; Apdillah, Dicky
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 2 (2025): May 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i2.3035

Abstract: Absence is usually used to see the level of employee discipline. The discipline of each employee is usually assessed as an indicator to determine whether the employee is allowed to apply for a salary increase and so on. To be able to monitor the presence of employee attendance activities, an attendance system is needed that can record employee attendance and absence. Over time, the attendance system has developed. Various types of attendance systems have also developed, such as using barcode and fingerprint methods. Problems with the barcode attendance system arise when employee members do not carry cards or other tools that have been given barcodes, then employees will not be able to take attendance, while the shortcomings of the fingerprint method when someone's fingerprints are injured or dirty will interfere with the scanning process on the sensor. Employees are required to take attendance every working day. The purpose of attendance in an agency, especially to see the performance of the employee, will also improve the quality of the agency itself. In this study, only the edge detection and clustering algorithms were used with the data inputted into this system being photo image data. In testing using edge detection, it produces percentage values such as in the first test, the percentage level of photo similarity is 47.32%, in the second photo test, the percentage level of photo similarity is 57.27%, in the third photo test, the percentage level of photo similarity is 57.75%, in the third photo test, the percentage level of photo similarity is 77.14%. Keywords: Edge Detection Algorithm, Clustering, Identifying Face Recognition, E-Attendance, Web Abstrak: Absensi biasanya digunakan untuk melihat tingkat kedisipinan pekerja. Kedisipinan masing-masing pegawai atau karyawan biasanya dinilai sebagai indikator untuk menentukan apakah karyawan tersebut boleh untuk mengajukan kenaikan gaji dan lain sebagianya. Untuk dapat memantau adanya aktivitas kehadiran pegawai atau karyawan maka diperlukan sebuah sistem absensi yang dapat mencatat absensi kehadiran dan ketidakhadiran karyawan.Seiring berjalannya waktu sistem absensi kian berkembang. Berbagai jenis sistem absensi pula telah berkembang seperti dengan menggunakan metode barcode dan sidik jari. Permasalahan pada sistem absensi barcode muncul ketika anggota karyawan tidak membawa kartu yang atau alat lainnya yang telah diberi barcode, maka karyawan tidak akan bisa melakukan absensi sedangkan kekurangan dalam metode sidik jari ketika sidak jari seseorang terluka atau kotor akan menggangu proses scanning pada sensor. Pegawai atau karyawan diharuskan untuk melakukan absen setiap hari kerja. Tujuan absensi di instansi khususnya untuk melihat kinerja pegawai atau karyawan tersebut yang akan meningkatkan juga mutu dari instansi itu sendiri. Dalam penelitian ini hanya menggunakan algoritma edge detection dan clustering dengan data yang diinputkan dalam sistem ini ialah data citra foto. Dalam pengujian menggunakan edge detection menghasilkan nilai persentase seperti pada uji pertama terlihat tingkat persentase kemiripan foto ialah 47,32%, pada uji foto ke dua terlihat tingkat persentase kemiripan foto ialah 57,27%, pada uji foto ke tiga terlihat tingkat persentase kemiripan foto ialah 57,75%, pada uji foto ke tiga terlihat tingkat persentase kemiripan foto ialah 77,14%. Kata Kunci : Algoritma Edge Detection, Clustering, Mengidentifikasi Pengenalan Wajah, E-Absensi, Web

STUDI KOMPARATIF MIKROKONTROLER AVR, PIC, DAN ARM DALAM APLIKASI IOT BERDASARKAN LITERATUR 2019–2024 Siregar, Raja Syahmuda; Panjaitan, Rahmadani Fitri; Afni Dwi Pertiwi, Riki Wirayuda; Pertiwi, Afni Dwi; Apdillah, Dicky
Jurnal Komputer dan Teknologi Vol 4 No 2 (2025): JUKOMTEK JULI 2025
Publisher : Yayasan Pendidikan Cahaya Budaya Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64626/jukomtek.v4i2.460

Perkembangan teknologi Internet of Things (IoT) mendorong penggunaan mikrokontroler sebagai komponen utama dalam berbagai perangkat pintar. Di antara berbagai jenis mikrokontroler, AVR, PIC, dan ARM menjadi platform yang paling sering digunakan dalam proyek IoT karena ketersediaan, dokumentasi, dan fleksibilitasnya. Penelitian ini bertujuan untuk membandingkan karakteristik, kelebihan, dan keterbatasan ketiga mikrokontroler tersebut berdasarkan studi literatur yang diterbitkan antara tahun 2019 hingga 2024. Penelitian ini menggunakan metode Systematic Literature Review (SLR), yaitu pendekatan terstruktur untuk mengidentifikasi, mengevaluasi, dan mensintesis seluruh temuan penelitian yang relevan terkait dengan suatu pertanyaan atau topik tertentu. Kajian literatur ini bukan sekadar pencarian referensi umum, melainkan merupakan proses ilmiah yang terarah dan sistematis dengan tujuan untuk memperoleh pemahaman yang menyeluruh, objektif, dan dapat direproduksi. Data dikumpulkan melalui kajian sistematis terhadap artikel ilmiah yang relevan dari beberapa database, termasuk Google Scholar, IEEE Xplore, dan portal SINTA. Hasil kajian menunjukkan bahwa mikrokontroler ARM unggul dalam kinerja dan skalabilitas, sementara AVR dan PIC lebih menonjol dari segi kesederhanaan implementasi dan efisiensi biaya. Temuan ini diharapkan dapat membantu peneliti dan praktisi dalam memilih platform mikrokontroler yang sesuai dengan kebutuhan aplikasi IoT mereka

Pelatihan Media Pembelajaran Assemblr Edu Berbasis Augmented Reality Terintegrasi Framework Oktaviana Nirmala Purba; Saragih, Sri Rahmah Dewi; Apdillah, Dicky
CARADDE: Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 2 (2024): Desember
Publisher : Ilin Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31960/caradde.v7i2.2717

Program Kemitraan Masyarakat (PKM) dilakukan peneliti di SMP Swasta Triyadikayasa. Tujuan dari pengadaan PKM yang dilakukan peneliti adalah untuk melihat ketrampilan dari hasil pengembangan bahan ajar yang diintegrasi framework menggunakan aplikasi Assemblr Edu serta respon dan tanggapan siswa dalam menggunakan Augmented Reality. Kegiatan pada tahap implementasi ini masuk dalam kegiatan ketrampilan yang dilakukan oleh tim pelaksana PKM di sekolah mitra yakni SMP Swasta Triyadikayasa Aeksongsongan. Kegiatan implementasi ini dilakukan secara berkelanjutan, hingga dapat dirasakan tidak hanya oleh para guru, namun juga oleh para siswa. Metode yang digunakan dalam kegiatan ini adalah persiapan, pembekalan/sosialisasi, pelatihan, penerapan teknologi, pendampingan & evaluasi, keberlanjutan program. Adapun partisipasi mitra dalam pelaksanaan kegiatan ini sifatnya tidak hanya pasif menerima, tetapi juga aktif melakukan. Maka pelatihan ini kolaboratif, saling mengisi antara peserta dan narasumber. Pada keberlanjutan program diharapkan kepada sekolah mitra SMPS Triyadikayasa setelah selesainya pelaksanaan Program yang dilakukan oleh Tim PKM, pihak mitra tetap melakukan keberlanjutan program berupa: (1) implementasi guru kepada siswa terkait pelaksanaan pelatihan dan pendampingan program; (2)Aplikasi dapat digunakan di setiap mata pelajaran terkhusus Matematika dengan pengembangan selanjutnya ke matapelajaran Biologi, Fisika, Kimia dll; (3)Mendukung untuk singkronisasi pada aplikasi yang sudah ada seperti Raport, AKM dan lainnya.

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