PAPER KULIAH BIOMETRIKA HUTAN
PEMODELAN SISTEM PENGATURAN
HASIL DALAM PENGELOLAAN HUTAN RAKYAT DI KABUPATEN JEPARA
Oleh
:
KELOMPOK 3 (KAMIS PAGI)
Harja
Septria E14130047
Sinta
Purnama E14130054
Wira
Nastainul Hakim E14130055
Mar’atul
Mardhiyyah E14130056
Aziz
Fajar Wahyudi E14130059
Rio
Firmansyah E14130061
Atrasina
Ghaisani E14130062
Mahda
Amalia E14130063
Reza
Aulia Gifari E14130065
Ryan
Azami
E14130066
Dosen :
Dr. Ir. Budi Kuncahyo, MS
DEPARTEMEN
MANAJEMEN HUTAN
FAKULTAS
KEHUTANAN
INSTITUT
PERTANIAN BOGOR
2016
PENDAHULUAN
Latar Belakang
Menurut
Departemen Kehutanan (1995), hutan rakyat adalah salah satu bentuk hutan
kemasyarakatan yang dimiliki oleh masyarakat atau rakyat, yang bertujuan untuk
meningkatkan kesejahteraan masyarakat, memenuhi kebutuhan masyarakat akan hasil
hutan serta pelestarian lingkungan hidup. Selanjutnya ketentuan luas lahan
minimal untuk hutan rakyat adalah sebesar 0.25 ha dengan penutupan lahan oleh
tajuk tanaman kayu-kayuan lebih dari 50% atau pada tahun pertama sebanyak 500
batang setiap hektarnya. Hutan rakyat selama ini hanya dilihat sebagai kumpulan
pohon-pohon yang tumbuh dan berkembang di atas lahan milik rakyat, sehingga banyak
dijumpai dalam kalkulasi ekonomi hutan rakyat yang muncul kepermukaan berkaitan
dengan hasil kayu saja.
Pengusahaan
hutan rakyat dalam perekonomian pedesaan memegang peranan penting bagi petani
pemilik lahan hutan rakyat maupun untuk tumbuhnya industri pengolahan kayu
rakyat dan banyak
diterapkan apa yang disebut “daur butuh”, yakni umur pohon yang dipanen ditentukan
oleh kebutuhan pendapatan karena semakin meningkatnya permintaan dari industri
pengolahan kayu seperti industri penggergajian dan industri mebel.
Kelestarian
hasil diharapkan dapat dicapai melalui pengaturan hasil. Pengaturan hasil hutan
memang diperlukan untuk menghitung volume kayu yang boleh ditebang pada setiap
tahun, agar jumlah tebangan selama periode tertentu sama dengan jumlah riap
dari seluruh tegakan. Pengusahaan hutan memerlukan waktu yang sangat panjang
untuk mencapai saat pemanenan.
Ada beberapa
metode pengaturan hasil dalam pengelolaan hutan yang lestari yaitu berdasarkan
luas, volume dan jumlah batang. Metode pengaturan hasil pada hutan rakyat
berbeda dengan pengaturan hasil pada hutan negara. Pengaturan hasil pada hutan
rakyat lebih sulit dari pengaturan hasil pada hutan negara. Hal ini terjadi
karena hutan rakyat memiliki keragaman yang sangat besar baik dalam struktur tanaman,
perilaku pemilik, dan luas lahan yang relatif kecil.
Metode pengaturan hasil yang biasa dipakai
pada hutan rakyat adalah metode jumlah batang. Pengaturan hasil pada hutan
rakyat menggunakan metode jumlah batang yaitu pengelolaan pohon demi pohon dari
berbagai struktur tanaman pada lahan milik yang bertujuan untuk kelestarian
pendapatan bagi setiap petani hutan rakyat. Nantinya dari pengaturan hasil
dengan menggunakan metode jumlah batang ini diharapkan dapat menghasilkan suatu
rumusan dasar pengaturan kelestarian hasil yang dapat dimengerti dengan mudah
oleh petani hutan rakyat.
Tujuan
Adapun
tujuan dibuatnya makalah ini adalah :
1.
Membandingkan skenario pengelolaan hutan rakyat
untuk mendapatkan keuntungan finansial yang terbaik antara tanaman monokultur
sengon, dan monokultur jati
2.
Menghasilkan skenario pengelolaan terbaik
METODOLOGI
Waktu
dan Tempat
Praktikum
Bometrika Hutan dilakukan setiap hari Kamis pukul 07.00 – 10.00 WIB yang
bertempat di RK X 301, Fakultas Kehutanan, Institut Pertanian Bogor.
Alat
dan Bahan
Alat
yang digunakan pada praktikum adalah alat tulis, seperangkat computer dengan
perangkat lunak (software) Ms. Word, Ms. Excel, dan Stella 9.0.2. Data jenis pohon Hutan Rakyat
Kabupaten Jepara Desa Damarwulan.
Prosedur
Kerja
Adapun
prosedur kerja dari praktikum ini adalah sebagai berikut:
1. Menentukan
topik yang akan dimodelkan
2. Mencari
literatur yeng terkait dengan topik pemodelan
3. Menganalisis
data pada literatur rujukan dan menentukan variabel yang terkait
4. Mengolah
data yang dibutuhkan
5. Merumuskan
kondisi yang mungkin terjadi
6. Membuat
simulasi model
Pemodelan Sistem
Untuk
pemodelan yang fleksibel dan multiguna dapat dilakukan dengan fase-fase sebagai
berikut (Purnomo 2012):
a.
Fromulasi Model Konseptual
Tahap ini merupakan tahapan untuk menentukan konsep
dan tujuan model system dibuat. Formulasi model konseptual berdasarkan kondisi
yang ditemukan dalam literatur, kemudian dibuat model system dalam komputer.
b. Spesifikasi Model
Tahap ini memiliki tujuan untuk
membangun suatu kuantitatif dari model yang diinginkan. Tahapan-tahapannya
yaitu menentukan struktur kuantitatif umum untuk model, menentukan unit waktu
dasar untuk simulasi, mengindentifikasi bentuk-bentuk fungsional dari persamaan
model, menduga parameter dari persamaan-persamaan model, memasukkan persamaan
model ke dalam komputer, menjalankan simulasi acuan, serta menetapkan persamaan
model.
c. Evaluasi Model
Tahap ini memiliki tujuan untuk
mengevaluasi kesesuaian model dengan tujuan yang telah ditentukan. Evaluasi
model dilakukan dengan menggunakan validasi secara kualitatif dengan tujuan:
1. Mengevaluasi
kewajaran dan kelogisan model
2. Analisis sensitivitas, dilakukan
untuk melihat kewajaran perilaku model jika dilakukan perubahan salah satu
parameter dalam model secara ekstrim.
d. Penggunaan Model
Tahap akhir analisis sistem ini
memiliki tujuan untuk menjawab pertanyaan-pertanyaan yang muncul pada awal
pembuatan model.
HASIL DAN PEMBAHASAN
Identifikasi
Isu, Tujuan, dan Batasan
a. Isu
yang diangkat ke dalam pemodelan simulasi ini adalah peningkatan pendapatan
petani hutan rakyat di Desa dengan mengembangkan kegiatan usahanya, sedangkan
tujuan dari penyusunan model ini adalah membuat model simulasi pengelolaan
hutan hutan rakyat dan menentukan model simulasi terbaik berdasarkan NPV dan
BCR yang diperoleh dari beberapa skenario pengelolaan hutan yang telah
dirancang. Pembuatan model ini memperhatikan potensi tegakan, perubahan volume
produksi, suku bunga, dan jangka waktu pengelolaan.
b.
Tujuan pembuatan model: Memprediksi keuntungan
finansial pengusahaan hutan rakyat dengan skenario pengelolaan monokultur
sengon, monokultur jati pada suku bunga
saat ini yaitu 14% dan menduga pengaruh perubahan suku bunga terhadap kelayakan
usaha HTI tersebut
c. Batasan-batasan
yang digunakan dalam penyusunan model simulasi ini antara lain:
o Daur
adalah interval waktu (dalam tahun) antara penanaman sampai pemanenan, namun
dalam analisis ini ditetapkan daur sebagai jangka pengelolaan untuk analisis
adalah 8 tahun
o Struktur
tegakan adalah banyaknya pohon pada blok dengan luas 1 Ha, sebagai data luasan
analisisnya
o
Sistem yang akan disimulasikan dalam pengelolaan hutan rakyat adalah
sistem monokultur sengon dan sistem monokultur jati serta sistem monokultur
keduanya (jati dan sengon)
o Pemanenan
hasil hutan dilakukan dengan cara tebang
o Sektor
pengeluaran perusahaan tidak meliputi investasi alat untuk kegiatan pembangunan
hutan, penjarangan, dan pemanenan karena proyek diusahakan oleh masyarakat
petani.
o
Keuntungan finansial dilakukan dengan mencari nilai NPV.
Konseptualisasi
Model
Konseptualisasi
model dilakukan untuk mendapatkan gambaran menyeluruh terhadap model yang akan
dibuat. Konseptualisasi model dilakukan dengan mengidentifikasikan semua
komponen yang terlibat dalam pemodelan dan mengelompokannya ke dalam beberapa
bagian. Model simulasi pengelolaan hutan ini terdiri dari dari model utama dan
beberapa sub model yaitu:
1. Submodel dinamika tegakan jati
dan sengon
2. Submodel pengelolaan usaha
sengon
3. Submodel pengelolaan usaha jati
4. Model
pengelolaan usaha hutan rakyat di
Sub Model Dinamika
Tegakan Jati dan Sengon
Tabel 1 Hasil Inventarisasi hutan rakyat
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Peluang jenis pohon berdiameter <10 10-19="" 10="" 12="" adalah="" cm="" diameter="" ingrowth="" jati="" ke="" kelas="" p="" pindah="" sengon="" untuk="">
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)
10>
·
Peluang masing-masing pohon dalam kelas diameter
untuk mati (mortality) dalam setahun sebagai berikut :
Tabel
2 Mortality Sengon dan Jati
·
Peluang masing-masing pohon dalam kelas diameter
untuk pindah (upgrowth) dalam setahun sebagai berikut :
Tabel
3 Upgrowth jati dan sengon
·
Tiap tahun ke 35 dilakukan penebangan pada
seluruh pohon pada kelas diameter 50-59 cm dan diameter 60 cm Up
·
Rata-rata volume pohon pada kelas diameter 50-59
adalah 4 m3, 60 cm Up adalah 5 m3
Gambar 1 Submodel Struktur Tegakan Jati dan Sengon
Buongiorno dan
Giles (1987) dalam Bone (2010) mendefinisikan tegakan (stand) sebagai
luasan yang cukup kecil ditebang dalam periode waktu yang singkat, misalnya
satu tahun. Tegakan dapat berupa seluruh areal hutan atau bagian dari areal
hutan yang luas, yang dikelola dengan siklus tebang tertentu. Sedangkan
struktur tegakan (Oliver dan Larson 1990 dalam Labetubun 2004) adalah
penyebaran fisik dan temporal dari pohon-pohon dalam tegakan yang penyebarannya
tersebut berdasarkan jenis, pola penyebaran vertikal atau horisontal, ukuran
pohon atau pohon termasuk volume tajuk, indeks luas daun, batang, penampang
lintang batang, umur pohon atau kombinasinya.
Struktur tegakan
dapat dibedakan atas struktur tegakan vertikal, struktur tegakan horizontal,
dan struktur tegakan spasial. Struktur tegakan vertikal adalah sebaran individu
pohon dalam berbagai lapisan tajuk, sedangkan struktur tegakan horisontal
didefinisikan sebagai banyaknya pohon per satuan luas pada setiap kelas
diameternya (Meyer et al. 1961; Davis dan Johnson 1987 dalam Bone,
2010). Dalam penelitian ini, karakteristik hutan rakyat sengon yang dimaksud
adalah struktur tegakan horisontal.
Menurut
Suhendang (1985) dalam Bone (2010), pengetahuan tentang struktur tegakan
berguna untuk penentuan kerapatan pohon pada berbagai kelas diameter, penentuan
luas bidang dasar tegakan, dan penentuan biomassa tegakan. Untuk pertimbangan
ekonomi, struktur tegakan dapat menunjukkan potensi tegakan minimal yang harus
tersedia, sedangkan untuk pertimbangan ekologis dari struktur tegakan akan
diperoleh gambaran mengenai regenerasi dari tegakan yang bersangkutan.
Pohon-pohon pada
tegakan hutan tidak seumur memiliki tinggi yang bervariasi sehingga akan
terlihat tidak teratur apabila dilihat dari penampang vertikal. Tipe distribusi
kelas diameter untuk tegakan tidak seumur ditandai oleh banyaknya jumlah pohon
berdiameter kecil yang disertai penurunan frekuensi terhadap kenaikan kelas
diameternya (Husch et al. 2003). De Liocourt, rimbawan Perancis, pada
tahun 1898 mempelajari distribusi diameter tegakan untuk hutan tidak seumur. Ia
menemukan bahwa rasio jumlah pohon pada kelas diameter berturut-turut cukup
konsisten dari kelas diameter terkecil sampai kelas diameter terbesar.
Struktur tegakan
menunjukkan sebaran umur atau kelas diameter dan kelas tajuk (Daniel et all 1992).
Komunitas tumbuhan terdiri dari kelompok tumbuh- tumbuhan yang masing-masing
individu mempertahankan sifatnya. Tegakan hutan cenderung homogen dan dapat
dibedakan secara jelas dengan tegakan di sekitarnya oleh umur, komposisi jenis,
struktur hutan, tempat tumbuh, dan keadaan geografis. Tegakan sengon dan jati merupakan
tegakan hutan seumur karena ditanam pada tahun yang sama. Sengon dan jati
merupakan jenis pionir serbaguna yang sangat penting di Indonesia. Jenis sengon
ini dipilih sebagai salah satu jenis tanaman industri di Indonesia karena
pertumbuhannya sangat cepat sedangkan jenis jati merupakan kayu komersil yang
membutuhkan waktu cukup lama untuk masa pertumbuhannya. Pada analisis
pengaturan hasil ditentukan dengan VI Kelompok Diameter pada setiap jenis pada
Tabel 1.
·
Sub Model
Pengelolaan Sengon
Hutan rakyat mulai
berkembang di masyarakat seiring kesadaran masyarakat akan manfaat menanam
pohon. Jenis pohon yang paling banyak masyarakat ditanam adalah sengon (Falcataria moluccana). Pengusahaan hutan
rakyat merupakan serangkaian kegiatan usaha yang meliputi kegiatan produksi,
pemanenan, pemasaran/distribusi dan industri pengolahan. Kegiatan tersebut
terkait dengan biaya yang dikeluarkan yang akan berpengaruh pada besar
pengeluaran. Pengeluaran yang ada setiap kegiatan menjadi pokok penting yang
berpengaruh pada manafaat yang akan diperoleh dari kegiatan pengusahaan hutan
rakyat tersebut.. Usaha sengon dilakukan pada lahan seluas 25 Ha dengan daur 8
tahun. Banyaknya sengon yang ditanam pada lahan jarak tanam 2 m x 3 m adalah
1666 bibit/Ha. Usaha hutan rakyat Sengon membutuhkan biaya untuk membangunnya.
Kegiatan pengelolaan diawali dengan persiapan lahan, kemudian dilakukan
pengadaan bibit, penanaman, pemeliharaan dan terakhir pemanenan. Biaya
persiapan lahan sebesar Rp 400.000/ha,- Biaya pengadaan bibit dengan harga per
bibit Rp 1.000,- adalah Rp 1.666.000/ha,-. Biaya penanaman sebesar Rp
300.000/ha,- meliputi biaya penanaman dan biaya pembuatan lubang .Setelah bibit
ditanam maka dilakukan pemeliharaan dengan biaya pemeliharaan sebesar Rp
945.000/ha,- ditambah biaya pupuk Rp 1.000.000/ha hingga tahun ketiga, kemudian
di tahun berikutnya hanya dilakukan pemupukan dengan jumlah lebih kecil
memerlukan biaya Rp 500.000/ha,- sampai akhir daur. Pemanenan dilakukan dengan
cara borongan dengan biaya Rp 5.000.000,-. Penjarangan dilakukan pada tahun
ketiga untuk memberikan ruang tumbuh yang lebih luas bagi sengon agar diperoleh
tegakan yang diinginkan. Jumlah penjarangan sengon dengan luas lahan 25 Ha
adalah 90 m3. Harga jual kayu sengon berumur 3 tahun per batang adalah Rp
375.000 Sehingga didapat pendapatan dari hasil penjarangan adalah Rp 33.750.000,-.
Jumlah kayu yang dipanen pada akhir daur sebanyak 400 m3 dengan harga per meter
kubik Rp. 800.000,- , sehingga pendapatan dari hasil pemanenan adalah Rp
320.000.000,- . Pendapatan total dari sengon adalah Rp 353.750.000,
Gambar
2 Submodel Pengelolaan Sengon
Submodel pengelolaan sengon merupakan kumpulan komponen
biaya atau pengeluaran yang diperuntukkan untuk kegiatan usaha rakyat sengon
meliputi kegiatan pemeliharaan tegakan (pemupkan, pembelian bibit dan perawatan
tanaman), kegiatan teknis (pemanenan, penjarangan, pengangkutan, penanaman).
·
Sub Model
Pengelolaan Jati
Usaha jati
(Tectona grandis) dilakukan pada
lahan seluas 25 Ha dengan daur 20 tahun. Banyaknya jati yang ditanam dengan jarak
tanam 6 m x 2 m adalah 833 bibit/Ha. Usaha hutan rakyat jati membutuhkan biaya
untuk membangunnya. Kegiatan pengelolaan diawali dengan persiapan lahan,
kemudian dilakukan pengadaan bibit, penanaman, pemeliharaan dan terakhir
pemanenan. Biaya persiapan lahan sebesar Rp 400.000/ha,- Biaya pengadaan bibit
dengan harga per bibit Rp 5.000,- adalah Rp 4.165.000,-/Ha. Biaya penanaman
sebesar Rp 300.000/ha,- meliputi biaya penanaman dan biaya pembuatan lubang
.Setelah bibit ditanam maka dilakukan pemeliharaan dengan biaya pemeliharaan
sebesar Rp 945.000,- ditambah biaya pupuk Rp 1.000.000 hingga tahun ketiga,
kemudian di tahun berikutnya hanya dilakukan pemupukan dengan jumlah lebih
kecil memerlukan biaya Rp 500.000,- sampai akhir daur. Pemanenan dilakukan
dengan cara borongan dengan biaya Rp 5.000.000,-. Penjarangan dilakukan pada
tahun ketiga untuk memberikan ruang tumbuh yang lebih luas bagi sengon agar
diperoleh tegakan yang diinginkan. Jumlah kayu yang dipanen pada akhir daur
sebanyak 130 m3 dengan harga per meter kubik Rp. 4.000.000,- , sehingga
pendapatan dari hasil pemanenan adalah Rp 520.000.000,- .
Gambar 3 Submodel Pengelolaan Jati
Submodel pengelolaan
sengon merupakan kumpulan komponen biaya atau pengeluaran yang diperuntukkan
untuk kegiatan usaha rakyat sengon meliputi kegiatan pemeliharaan tegakan
(pemupkan, pembelian bibit dan perawatan tanaman), kegiatan teknis (pemanenan,
penjarangan, pengangkutan, penanaman).
Perhitungan NPV
Gambar
4 Submodel Perhitungan NPV Sengon
Gambar
5 Submodel Perhitungan NPV Jati
Analisis finansial memiliki tujuan
untuk memantau aliran kas sehingga dapat menghindari keterlanjuran investasi
yang memakan dana relatif besar tapi tidak memberikan keuntungan yang maksimal
(Gittinger 1986). Indikator yang digunakan untuk analisis finansial diantaranya
adalah Net Present Value (NPV), Benefit Cost Ratio (BCR) dan Internal
Rate of Retur (IRR). Paper ini, penulis membandingkan skenario pengelolaan
hutan rakyat yang dapat menghasilkan keuntungan terbesar bagi petani. Skenario
pengelolaan hutan rakyat yaitu monokultur Jati, monokulktur Sengon. Untuk
mengetahui keuntungan dari masing-masing skenario, penulis menggunakan
perhitungan Net Present Value (NPV). Net Present Value (NPV) yaitu selisih
antara Present Value dari investasi dengan nilai sekarang dari
penerimaan-penerimaan kas besih di masa yang akan datang (Umar 1997).
Berdasarkan hasil simulasi
didapatkan hasil perhitungan NPV Sengon sebesar
RP 392.660.460 per daur yaitu 9 tahun sedangkan nilai NPV Jati jika
dihitung dalam daur yang sama sebesar Rp
249,750,005. Secara perhitungan, pengusahaan hutan rakyat dengan jangka waktu
yang cepat lebih menguntungkan dengan usaha sengon,karena NPV yang didapat
lebih besar. Hasil perhitungan NPV tersebut kumulatif selama 10 tahun, dengan
biaya-biaya yang telah di asumsikan oleh penulis. NPV diperoleh dari selisih
dari Present Value Benefit (total pendapatan) dengan Present Value Cost (total
pengeluaran), Suku bunga yang digunakan sebesar 14%.
Gambar
6 Hasil NPV Sengon
Gambar
7 Hasil Perhitungan NPV Jati
Evaluasi Model
Evaluasi
model merupakan tahapan dimana dilakukaknya pengamatan kelogisan model dan
membandingkanya dengan dunia nyata atau model andal yang serupa jika ada
(Purnomo2012). Submodel pengeluaran dari masing-masing skenario memiliki input
yang berbeda-beda, serta submodel pendapatan dari skenario jati dan skenario
sengon yang berbeda dimana tanaman jati dipanen saat berumur 20 tahun sedangkan
pohon sengon dipanen pada saat pohon cukup besar (seperti tebang butuh) sekitar
9 tahun.
Penggunaan Model
Skenario yang telah dibuat akan
menghasilkan data yang berhubungan dengan nilai uang, diperlukan pertimbangan
yang penting dalam pengambilan keputusan atas suatu kebijakan ekonomi. Dalam hal
ini suku bunga berpengaruh nyata terhadap keuntungan finansial, dengan membuat
suatu model maka dapat diprediksi suku bunga yang terbaik.
SIMPULAN
Simulasi
pengelolaan hutan rakyat dengan berbagai asumsi yang telah dibuat dalam model
diatas menghasilkan keuntungan finansial yang tertinggi pada tanaman sengon dengan
NPV sebesar Rp 392,660,460.00 per 9 tahun.NPV jati pada daur 9 sebesar Rp
499,500,000.00. Model pengusahaan rakyat tanaman sengon lebih dianjurkan karena
jangka waktu panen yang cepat dan NPV yang tinggi dibandingkan dengan jati
dengan asumsi waktu yang sama.
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alam bekas
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B. 2006. Potensi Kelembagaan Hutan Rakyat [Prosiding].Seminar Hasil Litbang Hasil Hutan 2006:14-23.
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LAMPIRAN